A review on rutting in asphalt concrete in Saudi Arabia: mitigation strategies, innovations, and future directions
-
Abstract
Rutting in asphalt concrete is a widespread phenomenon affecting the strength and overall performance of pavements, especially in regions with intense environmental variabilities and transitions, where excessive temperatures and heavy traffic loads exacerbate pavement deformation. This study reviews and synthesizes research on the causes, consequences, and mitigation strategies for rutting with a particular emphasis on Saudi Arabia’s asphalt pavements. Key factors contributing to rutting, advanced asphalt mixtures, and environmental conditions were extensively discussed. Moreover, the work explores the current pavement design requirements, particularly in Saudi Arabia, highlighting unique policies aimed at addressing rutting issues. Comparisons with other nations with relatively distinct climatic challenges were equally addressed to provide a broader understanding of global exceptional practices. The review also identifies key areas for future research, coupled with the development of superior asphalt mixtures, the incorporation of revolutionary components, and the implementation of tracking technology. By consolidating knowledge on rutting in Saudi Arabia, this review aims to inform and guide ongoing and future efforts to enhance pavement overall performance and durability in the region. In the end, recommendations were proposed based on materials, environmental impact, sustainability, and soil conditions that are essential for effective utilization in Saudi Arabia and other countries in the Arabian Peninsula.
1 Introduction
The economy of a country is tied heavily to well-designed, well-constructed, well-maintained, and integrated transportation systems. Despite the availability of alternative means of transportation, the road network still dominates the largest percentage of the transportation domain, and it is the most common mode adopted by the majority of the public due to its flexible features [1]. Across the world, nations have invested and continue to invest heavily in providing sustainable and well-integrated road network systems for the public [2]. This resource allocation keeps increasing yearly as the population and demand for road infrastructure keep evolving, especially in developing countries [3]. Also, this increasing demand cannot be overcome with a limited budgetary allocation for road infrastructure [2]. These roads, especially asphaltic concrete roads, exhibit certain phenomena of failure, including cracks and permanent deformation (rutting), which need concurrent and continuous repair works [4].
The ultimate functionality of pavement is to provide a finished medium that allows smooth and safe movement of vehicles and other road users [5]. The pavement usually acts as a system that receives, distributes, and transfers external loads among the successive layers forming the system, with the top layer being the strongest, capable of resisting these processes [6]. During this load transfer mechanism, several actions usually take place, leading to periodic deformation. Over time, especially toward the end of the flexible pavement life span, materials composing the pavement experience aging, leading to deterioration within the pavement resulting from the combined effects of stresses and other environmental factors [7]. This gradual phenomenon, weakening the existing bonding between aggregate minerals and bitumen, results in complete segregation, which evokes other modes of failure, such as rutting, fatigue cracks, and low-temperature cracking. [8]. The quality and performance of road pavement are negatively impacted by these failures [9].
Generally, in cold climates, asphalt is hard and brittle; in warmer climates, it is soft and ductile. The phenomenon of rutting is more prevalent in summer with a high rise in temperature. This poses the challenge of design and construction in the hotter regions, which is predominantly the case in almost the entire Gulf region [6]. However, some early scholars [10], 11] argued that rutting is solely due to the repetitive impact of axle loads on the surface of asphalt. Considering both perspectives, Rutting is still regarded as a serious threat to the safety of vehicles and other road users. Deeper rutting may lead the driver to lose control while driving at relatively high speeds, especially during maneuvering for lane changes. Also, the higher the depth of the rut, the higher the expectation of water accumulation, which is also a nuisance to the life of the road [6].
Due to the high temperature usually observed Gulf region, combined with heavy and frequent axle loads, rutting may occur on most of the highways within the first two years after construction [12]. In the Kingdom of Saudi Arabia (KSA), the complexities and factors bearing on the concrete pavement are significantly impacted by its harsh climatic conditions. Also, the accelerated temperatures, which regularly surpass 40 °C can set off thermal growth and contraction within the pavement system [13]. Moreover, the frequent occurrence of sandstorms poses abrasive risks to the surfaces of pavements, necessitating the usage of resilient substances and defensive methodologies. The arid environment additionally contributes to soil-related difficulties, particularly the life of expansive soils that exhibit swelling and contracting inclinations in response to variations of moisture levels, which in turn influences the stability of pavements [14].
In general practice, the design of flexible pavement considers the effect of allowable rutting at the top layers without giving attention to the subgrade layer. Emphasis should be given to the generalized formations of layers while attending to the persistent effect of rutting in pavements, taking into account the impact of loadings, materials, and environmental conditions. While for the asphaltic concrete pavement, researchers have presented limited and reviewed arguments on rutting with specific consideration of the rigid pavement to factors leading to the rutting, methods of testing, and prediction. Also, to extend the impact of the rutting phenomenon into clearer terms, it is imperative to understand how external load distribution can be related to the depth of rutting within the asphaltic pavement; this remains a subject of debate among researchers.
Therefore, the novel framework of this paper focused on a deeper and generalized review of the failure mechanism, causes, factors affecting, methods of measurement, mitigation strategies, monitoring methods, design methods, quality control measures, construction practices, material properties, and existing prediction approaches on permanent deformation of asphaltic pavement. Aiming at proposing and selecting a suitable and reliable approach for the adoption by researchers and practitioners in the construction domain, particularly in Saudi Arabia.
1.1 Structure and scope of the review
To enrich and authenticate the content of this review work, the papers considered were scoped to only those published in Scopus-indexed journals. 1,626 papers were published and are available from 1976 to 2024 in the said database. All papers chosen for bibliometric analysis were relevant to terminologies related to permanent deformation for visualizing trends, comparisons, and other key points in the research, as shown in Figure 1. Additionally, Figure 2 shows the research trend from 2014 to 2024 on rutting analysis from a global perspective. It can be noticed that in 2020 alone, there was a lot of concern and attention toward studies of a rutting phenomenon, followed by the year 2023 with 141 and 136 publications, respectively. However, to confine and limit the possibility of biased opinions or non-reliability of data sources, this study considers excluding any unpublished articles and proprietary data, this is regardless of the richness of their content.
The keyword terms used in the literature on the rutting analysis.
Research trend on rutting analysis from 2014 to 2024.
2 Mechanism of permanent deformation in asphaltic pavements
Traditionally, permanent deformation is often termed as general distortions observed at the pavement surface. However, a recent definition categorizes this phenomenon as ruts or just longitudinal stress. This is because rutting mainly occurs in the transverse surface profile as broadly presented in Figure 3. Continuous permanent deformation in asphalt pavements takes time to develop, which is greatly influenced by the continuous loading stress exerted by the layers. The rutting is mainly formed by volume reduction and tangential deformations in any of the layers of pavement, including the subgrade. Although the percentage is slight or insignificant in comparison to the topmost layers [5]. However, some further studies claimed to be of considerable percentage [15], 16].
![Figure 3:
Permanent deformation of asphalt concrete under repeated loading [17].](/document/doi/10.1515/rams-2025-0173/asset/graphic/j_rams-2025-0173_fig_003.jpg)
Permanent deformation of asphalt concrete under repeated loading [17].
Permanent deformation usually results in material segregation, volume reduction, and lateral plastic flow, which constituted the main part of the research conducted related to the analysis of rutting within the asphaltic pavement [18]. Plastic deformation within pavement leads to its rapid structural failure and also influences the level of service, state of safety, and servicing life it offers, through the accumulation of repetitive and dynamic loading along with temperature variations, especially in hotter regions of the Arabian Peninsula [19]. Vertical compressive stresses induced by the layers of asphalt give more insight into the mechanism of rutting [15]. For easy identification and analysis, rutting has been categorized into different forms, among which are: gradual debonding between the coated aggregate from the surface of the pavement (wearing) caused due to environmental and traffic volume [20], plastic deformation of lower layers due to successive load transmission (structural), caused due to normal stress imposed by the wheel load. The latter is very alarming and affects the subgrade layer, which leads to a reduction in volume and possible lateral deformation with disordered and unlevelled densification across the thickness of the composing layers (instability) [21]. This is attributed to the nature and properties of the materials composing the asphaltic pavement [15].
Asphalt concrete pavements use bituminous and polydisperse granular materials, with bitumen acting as a cementing agent to transmit wheel loads to underlying layers, which eventually dissipate [22]. Furthermore, it experiences aging due to traffic, weather variation, moderate rutting, spalling, and aggregate pavement, causing minor structural damage and deterioration over time [23]. Because the asphalt concrete mixture is simple to build, it is frequently used to pave roads and highway surfaces. Demand for long-lasting asphalt pavement is high because it lowers the cost of maintenance and public works [24]. In addition to degrading the enjoyment of the pavement ride, rutting puts road users’ safety in great danger. Following rain and snow, water can collect in the ruts, causing vehicles to hydroplane uncontrollably, thereby increasing the risk of accidents [25]. Permanent surface deformation usually has higher intensity within the loading zone, and its distribution decreases with depth within the asphalt [15]. However, certain work presented counters the above findings; suggesting that the permanent strain developed is evenly distributed within the fibre of the lower zone of the layered pavement [26]. Thus, when designing pavement structures, it is critical to precisely assess the rutting resistance of asphalt mixtures [27].
These internal mechanisms can be studied only at the microstructural level. The most closely agreed hypothesis claimed that attending an equilibrium state by aggregated particles necessitates the movements of the particles [28]. These internal processes of attaining equilibrium by particles are permanent and irreversible upon the relief of loading. At the same microscopic level, this type of rutting is formed due to the breakage of the temporary void network by particle reorientation, which can be fully explained in terms of rheology [6]. Conversely, the rheology of asphaltic pavement, especially at the microstructural level, is complex to understand. The closest explanation is done by earlier work of [29], 30] describing it as resulting from the filling of void spaces by the asphalt binders which wears away the aggregate coating and affects the relative distance between the mass number of aggregates in the mix. While the repositioning of granular particles initiate the flow of asphaltic cement into the new void created.
3 Field measurement of rutting in asphaltic pavement
To have a realistic understanding of rutting, physical measurement is notably important at the macro-structural level. This is paramount, especially in construction monitoring and repair works of roads [26].
3.1 Manual method
Traditional field measurements are conducted at 6-m intervals for all road carriageways, with mean values representing the depth of the rut of the road. The process involves identifying rutting areas on pavement surfaces, which can be crests or valleys, depending on loading impact and contact area between axle and surface. The process then proceeds with marking all the spotted areas. The measurement is then conducted with the help of a straightedge metal of a defined length, usually 3.6 m, to establish a reference line about the condition of the pavement as shown in Figure 4. The depth of the rut is measured by any suitable scaled measuring instrument at the centre of the area of concern [5], 15]. The typical process is described extensively in [31]. The outcome of this fieldwork would then be compared with the American Association of State Highway and Transportation Officials AASHTO recommendations (Table 1) on rutting, which is based on the impact and severity [32].
![Figure 4:
Description of field measurement of rutting depth [31].](/document/doi/10.1515/rams-2025-0173/asset/graphic/j_rams-2025-0173_fig_004.jpg)
Description of field measurement of rutting depth [31].
AASHTO Specification criteria and severity level of rut depth [32].
| S/No | Mean depth (mm) | Level of severity |
|---|---|---|
| 1 | 6–13 | Low |
| 2 | 14–25 | Medium |
| 3 | >25 | High |
3.2 Automatic/wire model algorithm method
Recent advancement in technology renders the manual method of rutting measurement obsolete due to some deficiencies and challenges, including time-consuming, prone to inaccurate data collection, and labour-intensive. To deal with these challenges, a newly improved and semi-automatic method was invented and has been in use for over a decade by countries of the Arabian Peninsula. The method involves the usage of an automatic road analyzer, as shown in Figure 5a and b. The data collected will then be simulated by already installed Wire Model Algorithms (WMA). The wire model algorithm is connected directly to the upper levels of the pavement section in the transverse direction, and a rut depth is measured using these points as referenced [33]. The procedures depend on the number of lanes and the widths of the carriageway. After the collection is completed, the average value is considered the rut depth.
![Figure 5:
Automated method of rutting measurement. (a) Automatic road analyzer vehicle complete setup, collecting data from the site [33]. (b) A typical profile of rut depth obtained from the wire model algorithm [33].](/document/doi/10.1515/rams-2025-0173/asset/graphic/j_rams-2025-0173_fig_005.jpg)
4 Factors affecting rutting
Rutting mostly occurs at the premature phase of pavement, which eventually affects the performance of the pavement during its lifespan. The main factors contributing to permanent deformations include repetitive axle load, mix design deficiencies, the quality of materials from which the asphalt is made up, and environmental conditions. Factors that are mainly related to the quality of materials composing the concrete asphalt affecting the rutting are within a controllable level by transportation agencies. The control can be attained through careful selection, grading, mixing, and placement of the asphalt mix. Therefore, adopting proper and standard processes of quality control on materials will minimize the rate at which the rutting occurs [34]. While factors, especially temperature variation, are difficult to control. This is due to the spontaneous processes involved. In Saudi Arabia, during the months of summer, usually from June to August, the surface temperature of asphalt pavement can rise very high, often between 60°C and 70°C. Some areas, especially in urban zones or where dark-colored surfaces are common, can even experience temperatures above 75 °C. This is an outlier from the normal air temperature, which is usually around 45 °C–50 °C. Considering similar hot and dry regions like parts of the UAE, Kuwait, or southern Arizona in the US, the pavement temperatures there are often about the same or just a bit higher. The main reasons are the intense sunlight, low humidity, and strong solar radiation. When asphalt gets this hot, the binder, which holds the pavement together, softens faster. This can lead to problems like rutting, especially if there is a lot of traffic driving over it.
4.1 Traffic loading
Traffic loading is among the most detrimental factors contributing to the rutting problem in asphaltic pavement. Its impact is quite inevitable during the lifespan of the pavement, especially during the aging process [34]. Road surfaces are designed to receive and serve as resistance to traffic loading, which involves the combined effect of axle contact stresses induced by the surface of the pavement through repeated load from the axle load, vehicular speed, and the volume of the traffic [35], 36]. It was claimed from field experiments that increasing the axle pressure and weights of the vehicles directly results in a rapid rutting phenomenon regardless of the intended and expected traffic on the road [30], 37]. Lowered vehicular speed tends to result in a wider range of loading periods with less frequency, while the accumulated load with relatively higher speed at the same load repetition is considered to have less impact on permanent deformation [38]. To fully understand how the speed is related to and influences the rutting of asphalt, it is necessary to apply and relate it to the viscoelastic processes in determining the response of rolling load. The speed is always a function of the instantaneous duration of the loading relationship. Therefore, high speed exerts less response from the elastic modulus of asphaltic pavement [38]. On the other hand, continuous and load repetition tend to contribute to rapid rutting.
Saudi Arabia’s (SA) roads are influenced by various vehicle types, including passenger cars, commercial trucks, buses, and heavy vehicles. Passenger cars, particularly during peak hours, significantly impact traffic flow. Buses, particularly public ones, influence traffic dynamics in Saudi Arabia [39]. During peak hours, heavy-duty vehicles add traffic load, impacting road longevity and congestion patterns. These vehicles, including construction machinery and oversized transport vehicles, create hotspots in infrastructure projects, necessitating custom-made engineering interventions. Table 2 and Figure 6 provide information on vehicle types on traffic loads [40].
Impact of different vehicle types on traffic loads.
| Vehicle type | Traffic load contribution | Typical load (tons) | Impact on road surface |
|---|---|---|---|
| Passenger cars | High (urban areas) | 1.0–2.5 | Moderate (varied loads) |
| Light commercial | Medium | 2.5–7.5 | Significant (frequent use) |
| Heavy-duty trucks | High (intercity) | 10.0–30.0 | High (heavy loads) |
| Buses | Medium to high | 8.0–12.0 | Significant (frequent stops) |
| Specialized heavy | Low (sporadic) | 15.0–60.0 | Very high (localized stress) |
General category vehicles in the globe.
4.2 Traffic patterns and their influence on rutting
Traffic patterns play a greater role in the deterioration of roads, particularly in terms of rutting [2]. As urban regions expand, the landscape samples round road modifications, impacting traffic accessibility and probably exacerbating rutting issues [41]. Roads with higher traffic flow are more likely to reveal in rutting than roads with less traffic [42]. Factors such as vehicle detection, tracking, and extraction of traffic flow parameters are vital for monitoring traffic styles and predicting potential rutting problems [43]. Additionally, the AASHTO Joint Undertaking Force on rutting has highlighted the importance of studies on traffic and environmental elements in assessing and mitigating rutting in asphalt concrete pavement [23].
Moreover, with the continuous growth of the Saudi Arabian transportation infrastructure, the use of revolutionary materials may contribute to sustainable road construction practices [44]. Traffic patterns and rutting on Saudi Arabian roads are complex issues requiring comprehensive expertise to mitigate and protect the country’s road infrastructure [45], 46]. With over 6 million cars on the roads and a high incidence of street traffic injuries, Saudi Arabia faces challenges related to road maintenance [47], 48]. This is why the Saudi Arabian Ministry of Transportation (MOT) collects statistics on pavement situations to evaluate avenue quality [49]. The relationship between the global Roughness Index (GRI) and pavement distresses like cracking and raveling has been studied, highlighting the significance of monitoring road conditions for effective upkeep. Information on traffic flow characteristics and driver behavior is critical for mitigating rutting problems and ensuring the longevity of Saudi Arabian roads. Moreover, a comprehensive evaluation of Road traffic accidents (RTAs) in Saudi Arabia found that certain towns like Riyadh, Ash Sharqiyah, Makkah, and Jeddah have better prices for RTA involvement, mortality, and morbidity [50].
4.3 Climate and environmental factors
Generally, asphalt mixes are sensitive to temperature variation; the rapid variation of temperature contributes to the effect of rutting. Asphalt mixes respond instantaneously when exposed to varied temperature scales [51]. This makes the strengths and moduli varied [52]. The variation permits the asphaltic mix to expand and contract, which contributes toward more rutting [53]. Temperature is a leading factor in causing the transition of asphalt binder from a highly viscous fluid, viscoelastic fluid, to a viscoelastic solid [54]. These transitions contribute towards weakening the structural strengths and reducing the serviceability through plastic deformation [55]. Rutting tends to be more excessive in an environment with relatively high temperatures, which directly affects the viscoelastic properties of asphalt mix [56]. The viscosity range of asphaltic material usually gives it a wide range of transitioning behaviour, transforming from a low Newtonian fluid to a highly viscoelastic material [2]. Thus, the elastic and plastic properties tend to be high at low temperatures [16], 57]. This reaffirms the findings that asphalt with less viscosity tends to produce a mix with less stiffness and is highly vulnerable to rutting [10]. Usually, the recoverability of asphalt is limited to a state of viscoelastic, while deformation in the plastic state ends up being irrecoverable [58], 59].
With exposure to a dynamic combination of loading rate and elevated temperature, bonding between the aggregate and binding material in asphalt tends to become weak, leading to rapid aging [60]. A stiffer mix, which resulted from the highly viscous asphalt, tends to lower the rate of permanent deformation. However, a hard grade of asphalt may be problematic at low temperatures, resulting in low-temperature cracks [61]. Therefore, during the designing and construction process, a balanced system should be established, factoring all parameters before concluding on the final selection of grade to be implemented for the asphaltic mix, which will withstand the exposure of both hot and cold temperatures [62]. However, based on the research carried out in the Canadian region of Quebec, a conclusion was reached that a strong relationship ceases to exist between the viscosity level of asphaltic pavement and the rutting effect [63]. This is exceptional and confined within the study area, with evidence in the record of the lower average annual temperature of the region from the World Index program database. Therefore, these dual behaviors of asphalt mix should be studied thoroughly in order to optimally reduce the impact of cracking due to stresses at lower levels of temperature and permanent strain deformation at higher temperatures.
Apart from the impact of temperature change on asphalt pavement, it is worth noting that pavement also contributes to climate change, which affects the temperature in return. Two scenarios are responsible for the contribution: the first is the amount of carbon emission released during the production process, and the life cycle stages of the pavements. The second is the coverage it offers to a significant portion of green areas, especially in metropolitan areas, where heat absorption and desorption are considerably higher in asphalt compared to the naturally preserved soil [64]. Figure 7 shows the temperature mechanism of Asphalt.
![Figure 7:
Temperature mechanism on asphalt [77].](/document/doi/10.1515/rams-2025-0173/asset/graphic/j_rams-2025-0173_fig_007.jpg)
Temperature mechanism on asphalt [77].
Saudi Arabia exhibits a predominantly arid climate distinguished by notably high temperatures, limited humidity, and scarce precipitation for most months of the year. Data on air and marine temperatures provide clear evidence that the climate is changing on both a global and regional scale [65]. In every region of the world, variations in temperature and rainfall are thought to be the primary indicators of climate change [66]. Climate conditions in the region pose significant challenges to asphalt pavement, including elevated temperatures, lack of moisture, and a lack of high-quality construction materials. Marginal materials need improvement with Portland cement or stabilizers, making upgrades unfeasible in severe dry desert climates [67]. To address these difficulties, specialized asphalt blends with adjusted binders and additives are frequently employed in Saudi Arabia to boost durability and resilience against the severe climate. Table 3 gives the temperature, humidity, and precipitation ranges of some cities in the Kingdom of Saudi Arabia, which are based on seasonal disparities and weather patterns.
Temperature, humidity, and precipitation range in Saudi Arabia.
| S/N | City | Temperature variation (°C) | Humidity variation (%) | Average precipitation (mm) | Authors |
|---|---|---|---|---|---|
| 1 | Riyadh | 10 to 45 | 10 to 30 | 100 to 150 | [68] |
| 2 | Jeddah | 20 to 35 | 60 to 80 | 50 to 100 | [13] |
| 3 | Mecca | 25 to 40 | 50 to 70 | 50 to 100 | [69] |
| 4 | Medina | 15 to 40 | 20 to 40 | 50 to 100 | [70] |
| 5 | Dammam | 15 to 45 | 30 to 60 | 50 to 100 | [71] |
| 6 | Tabuk | 5 to 35 | 20 to 40 | 50 to 100 | [72] |
| 7 | Abha | 0 to 30 | 50 to 70 | 200 to 300 | [73] |
| 8 | Najran | 10 to 40 | 20 to 40 | 100 to 150 | [74] |
| 9 | Hail | 0 to 35 | 20 to 40 | 50 to 100 | [71] |
| 10 | Al-Khobar | 15 to 45 | 30 to 60 | 50 to 100 | [75] |
| 11 | Yanbu | 20 to 40 | 50 to 70 | 50 to 100 | [76] |
| 12 | Buraidah | 5 to 40 | 20 to 40 | 50 to 100 | [77] |
| 13 | Al-Jubail | 15 to 45 | 30 to 60 | 50 to 100 | [68] |
| 14 | Al-Qassim | 5 to 40 | 20 to 40 | 50 to 100 | [78] |
| 15 | Ha’il | 0 to 35 | 20 to 40 | 50 to 100 | [79] |
| 16 | Al Bahah | 10 to 30 | 50 to 70 | 200 to 300 | [80] |
| 17 | Arar | −5 to 40 | 10 to 30 | 50 to 100 | [73] |
| 18 | Ta’if | 10 to 35 | 50 to 70 | 100 to 150 | [81] |
4.4 Material properties
4.4.1 Asphalt grade
As mentioned in the preceding section, some of the factors responsible for influencing the rate of rutting are within the control level of experts and are mainly related to the quality control of the asphalt mix. Likewise, the asphalt grade penetrations fall within this category. It was affirmed that soft asphaltic concrete mix tends to be more vulnerable to rutting, while the hard grade is resistant to rapid rutting; this does not favor the uniform adoption of asphalt with a high penetration grade [82].
4.4.2 Aggregate gradation
Laboratory and field experiments reveal that permanent deformation usually appears in the wearing course layer, which constituted the largest percentage of aggregates [83]. Therefore, the characteristics of aggregates are crucial for determining and controlling the level of rutting in the asphalt. Surface texture, size distribution, contact distribution, shape, and gradation of aggregate contribute immensely to the rutting of asphaltic concrete pavement [84]. It is common knowledge that aggregates with a higher roughness index tend to provide high internal friction resulting from the interlocking and grip through contact among the individual particles in a mix of asphalt cement [85]. This, in the longer run, tends to decrease the rate of possible rutting, and a stronger binder is also expected from the mix [86]. Higher stability of the asphalt mix is expected in a mix with a high content of irregularly shaped aggregates [87]. This is in contrast to the asphalt produced with average, rounded particles [88].
Fieldwork conducted in essence to unveil the effect of the shape and texture of fine aggregate indicates that replacing crushed and well-graded fine aggregate with natural sand for the production of asphaltic cement contributes to increasing permanent deformation [89]. This is majorly related to the relative circular shape of the aggregate composing natural sand [90]. With a relatively larger size, crushed coarse aggregate with less natural sand content is proven to resist permanent deformation when compared with the mix made with relatively smaller-sized aggregates and more content of natural sand [91], 92]. However, subsequent increases of larger size aggregates tend to produce a tougher mix [93]. It was also claimed that particle size distribution contributes to determining the tenderness of the asphaltic concrete mixture [94]. As the tenderness increases, the tendency of rutting is relatively high due to the dominance of rounded, uncrushed aggregate, which makes the accumulation of filler materials difficult [95], 96]. Also, medium-sized aggregate gives high rutting resistance compared to fine and coarser-sized aggregate [97], 98].
Laboratory test conducted on rutted and un-rutted samples of asphalt that have been in service for five years indicates that aggregate texture has a significant impact when the air void is above 2.5 %, with increased rutting rates in samples with less content of crushed coarse and fine aggregate [92]. Other works reaffirming similar findings through laboratory tests include [88], 99]. The modeled result obtained from the cyclic creep test conducted to ascertain the effect of aggregate gradation and asphalt contents revealed that susceptibility increases, which leads to rutting when the cement binder used in the preparation of the asphalt mix is beyond the optimum content [82].
4.4.3 Binder type and content
Although it is crucial to the designing and mixing of asphaltic concrete pavement, the type and specification of binder play a lesser role compared to the proportions and gradation of aggregates when the rutting effect is considered [100]. Increasing bitumen beyond the predetermined optimum content will lead to an increase in the probable permanent deformation of asphaltic pavement to more than half of the initial value [92]. This has been expounded upon by [29]. Also, filling the air needed and tying void spaces with cement content exposes asphaltic pavement to the potential of permanent deformation. This is equivalent to filling void spaces with lubricants; the resulting flow of lubricant-like cement content renders the asphaltic pavement very fragile to induce permanent deformation [101].
A larger portion of filler materials with an average size greater than the thickness of the asphalt film initiates and serves the primary function of interlocking the aggregate by creating the bonding. Although there is broader evidence of rutting resistance when aggregate with reduced sphericity is employed for the asphalt mix, which contributes significantly to retarding the failure of pavement. Thus, the exact and actual percentage of rutting is controversial even with an abundance of works in the current literature, which originated from many factors such as the type of polymers (Elastomers, Plastomers, and rubber) used as the main modifiers, their function, etc. the work of [102] have deeply discussed how these factor influences the choice of desirable modifiers. While the choice of aggregate targeting for improved interlocking is addressed by [103].
Although it depends on the mix proportion and size of the filler materials, filler materials with an average size less than the asphalt film contribute as a binder material in the pool of suspended asphalt binder [104]. However, filler-asphalt agglomeration gives a stiffer mix with high resistance to rutting [105]. To obtain a mix with high resistance, the expected optimum content of filler material should be within the range of (4–8%) [106]. The usage of residual air void ratio between the ranges of 3–5 % in the pavement after compaction is recommended by the Federal Highway Administration (FHWA) Technical Advisory [107]. A concluding evidence from the fieldwork in Saudi Arabia indicates that roads constructed with high cement content as binder material tend to be more susceptible to rutting compared to roads with a lesser amount of cement content as binder [108].
The mechanical performance of an asphalt mixture is influenced by aggregate form, length, angularity, and texture. Well-graded aggregates improve burden transfer and resistance to rutting, while asphalt binder properties also impact performance. Table 4 summarizes various properties of aggregates central to the rutting evaluation process, while Table 5 outlines some characteristics of the asphalt binder and their effect on rutting resistance. Table 6 also summarizes the testing and the parameters assessed. Further analysis of material properties can be shown in Figure 8, to highlight the material that has the highest proportion in the study related to rutting analysis in the last decade. And also Figure 9 depicts the research activity for each material property.
Factors analyzed and their impact on aggregate properties.
| Factors | Description | Ref. |
|---|---|---|
| Graduation | Optimal particle size distribution for load distribution and interlocking. | [109], [110], [111] |
| Shape and texture | Influence on pavement surface friction and resistance to deformation. | [112], [113], [114], [115] |
| Angularity | Impact on aggregate interlocking and rutting resistance. | [112], 114], 116] |
| Aggregate source | Long-term durability and rutting performance implications. | [117] |
Asphalt binder characteristics.
| Factors | Description | Ref. |
|---|---|---|
| Viscosity | Crucial for binder-aggregate adhesion and mix workability. | [118] |
| Stiffness | Resistance against permanent deformation under traffic loads. | [119] |
| Temperature susceptibility | Adaptation to varying environmental conditions for consistent performance. | [120] |
Evaluation methods and the parameter measured.
| Evaluation techniques | Parameters measured | Authors |
|---|---|---|
| Field observations | Rut depth measurements, pavement distress analysis | [17], 46] |
| Laboratory testing | Aggregate gradation, shape analysis, binder rheology, performance tests | [121] |
| Numerical simulations | Pavement modeling, stress analysis, rutting prediction | [98] |
Influence and significance related to material properties.
Research activity related to properties of materials.
4.5 Pavement design
Pavement design is essential and pivotal in determining the quality of pavements to be laid. Optimal decisions on concrete materials and the computation of multi-layered systems (subgrade, subbase, base, and surface courses) to accommodate traffic loads and endure environmental exposures must be considered while designing [40]. Therefore, in the design process of these layers, one gets to blend aspects of geotechnical engineering, materials science, and structural analysis to determine the best thickness and/or material composition of the layers. Newer pavement design also incorporates the aspects of sustainability, where recycling of materials and use of advanced construction methods, which enhance low impacts on the environment, are also taken into account [122]. Thus, pavement design can be considered accurate based on both the demands of the economy and the enabling technical capabilities. It aims to provide good transportation facilities that can meet the needs of the general public and enhance growth. Figure 10 shows the number of publications per pavement design.
Pavement design approaches and key performance indicators.
Pavement design methodologies in Saudi Arabia encompass diverse processes to cope with distresses like rutting, cracking, and roughness. The Mechanistic-Empirical Pavement Design Guide “Manual” (MEPDG) software is utilized to calibrate designs based on material properties, climate, and traffic volumes throughout regions in KSA [45]. Additionally, evaluating sustainability factors for specific pavement types, along with cold In-place Recycling (CIR) and traditional asphalt, aids in selection-making for road carriageways [23]. In regions with intricate soils like Sabkha, finite detail simulations using Plaxis 3D software assist in optimizing pavement structures with geo-grid reinforcement to mitigate important responses like fatigue and rutting traces [98]. The evolution of pavement design methods, specifically via the MEPDG, has been instrumental in enhancing roadway design practices [123].
A review of rutting in asphalt concrete pavement highlighted the significance of layout equations for flexible pavements in retaining the serviceability index [124]. In addition, the important factors to be considered that influence pavement design in Saudi Arabia consist of material properties, roadbed traits, climate, and traffic volumes. The soil conditions in certain regions necessitate modern solutions like geo-grid reinforcement to enhance the overall performance and durability of pavements [125]. Moreover, the environmental impact of sustainability considerations plays a crucial role in deciding on environmentally friendly construction materials for pavement production. A radar plot of Figure 10 reveals the impact of different pavement design approaches on key performance indicators.
5 Factors influencing rutting resistance in pavement design
One of the essential factors influencing rutting resistance in pavement design is the properties of the asphalt binder [126]. The type and characteristics of the binder play a significant role in determining the performance of the pavement below repetitive loading and high temperatures [127]. Binder rutting parameters may be used to explain the rutting resistance of both unmodified and changed binders [128]. For example, the stiffness and viscosity of the binder can impact its ability to face up to permanent deformation, making it important to select binders with appropriate resistance to rutting. Binder stiffness and viscosity affect rutting resistance, as the right selection of binders is essential for overall performance under excessive temperatures. In fact, extraordinary binder rutting parameters can explain resistance in diverse binder kinds.
Aggregate characteristics also contribute to the rutting resistance of asphalt pavements from the same perspective [129]. This concern is quite interesting, because the type, gradation, and quality of aggregates available for use in the mixture can have a considerable impact on the performance and serviceability of the pavement structure [130]. These studies have shown that aggregate gradation and type have the potential to impact the mix’s resistance to permanent deformation. Hence, the need to consider the aggregate’s properties while designing pavements to achieve an optimal rutting-resistant pavement is crucial. When comparing design parameters associated with rutting resistance, it is essential not to forget the pavement structure and thickness [131]. The thickness of each layer within the pavement shape performs a vital function in dispersing loads, dealing with stresses, and stopping rutting deformation [10]. The Mechanistic-Empirical Pavement Design Manual (MEPDG) emphasizes the significance of considering climate-associated parameters, which include hourly air temperature, in the course of the layout life to ensure the best possible performance and rutting resistance [132]. Pavement shape and layer thickness are important for load distribution and pressure management; also, proper layer thickness is essential for preventing rutting deformation. The attention to weather-associated parameters is important for the lengthy period of overall performance and rutting resistance.
5.1 Construction practices
Construction practices for asphalt pavements in Saudi Arabia are known for a meticulous method tailored to the use of climatic and geological situations by emphasizing durability and performance. These practices combine materials such as asphalt mixtures designed to withstand the region’s severe temperatures and heavy traffic loadings [133], 134]. The creation of strategies prioritizing proper compaction, surface guidance, and drainage is conducted to ensure lengthy structural integrity and resistance to moisture-caused damage [135]. Also, adherence to stringent fine control measures, which include periodic testing and inspection, is a common practice that meet international requirements and contribute to the safe and efficient movement of products and people across the network.
Sustainable practices in pavement creation are being embraced within the United States of America to promote environmental responsibility and beautify assignment outcomes [136]. The utilization of plastic waste additive to asphalt pavements in warm climate conditions in Saudi Arabia has been reviewed by [137]. Furthermore, the usage of industrial and agricultural wastes in roller-compacted concrete pavement mixes containing RAP aggregates has been studied to emphasize sustainability in pavement construction [138]. In asphalt concrete materials, efforts have been made to establish standards for controlling rutting in sloped pavements using finite detail technique simulations [139]. Additionally, the layout of warm-mix recycled asphalt concrete without preheating the reclaimed material has been explored, showcasing mechanical overall performance blends applicable to common practices in Portugal [140]. While asphalt pavement recycling has turned out to be a common exercise globally, research has targeted the consequences of growing older and recycling dealers on binders with high RAP contents to recognize their multiscale homes [141].
The construction of pavement layers using foamed asphalt (FA) has gained considerable interest in recent years, particularly in areas with excessive temperatures, which includes eastern Saudi Arabia [142]. Research has shown that FA can successfully stabilize nearby sebkha soils to be used as base or subbase material in asphalt structures [142]. Additionally, research has explored the incorporation of recycled asphalt pavements (RAP) into Portland cement concrete, even though extra studies are required in this area [143]. In Saudi Arabia, the use of foamed asphalt for road base construction has been investigated as an alternative to standard crushed aggregate mixes [67]. Another research focused on comparing the overall performance of foamed asphalt pavement mixes using marginal first-class construction materials like marl and RAP materials for nearby applications [67].
5.2 Examination of compaction techniques, layer thickness, and quality control measures
Compaction strategies, layer thickness, and quality control measures are crucial for durable and long-lasting asphalt concrete infrastructure in Saudi Arabia. Engineers use vibratory rollers and pneumatic tyre rollers for unique mix designs and layer thickness requirements. Adherence to industry standards and quality assessment methods, such as stiffness or strength, contributes to the durability and sustainability of street networks.
However, tools such as the lightweight deflectometer (LWD) are known to be useful in identifying the modulus of deformation of pavement layers [144], 145]. Exposing layer thickness with heavy vibratory rollers has provided better results for compaction and general formulas to determine the compaction degree of soil and subgrade quality [146]. The first pass cushion and double-layer continuous paving technology have been reviewed for their interlayer bonding effect, emphasizing the measures to be taken during construction for possible best bonding and evenness in thick cement-stabilized base layers [147]. Besides, density achieved through compaction of hot mix asphalt layers plays a critical role in the establishment of long-term behavior of pavement, and numerous works have been devoted to the methods of evaluating compaction quality in laboratory and field tests to improve pavement resistance against different types [148].
Schmitt’s work showed that on the flexible bases, thicker lift aggregates were easier to compact than thinner ones, while on the rigid sub-base, the smaller lifts were easier to compact than the large ones, reflecting the effect of layer thickness on compaction [149]. Additionally, modern technologies of compaction, including intelligent compaction (IC) and dynamic compaction, offer several prospects in numerous areas. By utilizing IC technology, every square meter of a roadway can be measured to control compaction uniformity in soils and asphalt pavements better, leading to reduced maintenance costs and increased service lives on roadways [150]. On the other hand, dynamic compaction is one of the traditional ground improvement methods that aims at increasing the bearing capacity and decreasing the compressibility of thick strata using an energy impact producer falling directly on the surface by heavy pounders; modern advancements include the MARS system that optimizes the energy used in impacting the ground [151]. These novel approaches offer work’s advantages, discussed earlier, including increased output, anticipation for continual adaptations in the compaction process, and a decrease in spatial variability. Also, it helps achieve material density, which consequently allows for the consistent enhancement in the quality of construction results and rationalization of expenses in the long run.
The research conducted in Saudi Arabia, which centered on structural pavement layout techniques, included compaction, layer thickness, and great management measures for asphalt concrete pavements [152]. It utilizes the Mechanistic-Empirical Pavement Layout Manual (MEPDG) software program to predict pavement distress based on fabric properties, roadbed characteristics, weather, and visitor masses in distinct areas of Saudi Arabia [153]. Additionally, a study emphasizes the significance of IC as an effective technique for controlling compaction during asphalt pavement construction [154]. Furthermore, the look highlighted the importance of non-stop monitoring and exceptional management measures, featuring an original high-quality management scheme based on cloud computing for real-time processing and feedback [155]. These findings contribute to improving the sturdiness and overall performance of asphalt concrete pavements in Saudi Arabia through optimized compaction strategies and exceptional control measures. Table 7 summarizes the compaction approach, layer thickness, quality control, and climate considerations.
Summary of the key aspects for consideration.
| Aspect | Description |
|---|---|
| Compaction techniques | Diverse compaction strategies are employed, such as vibratory rollers and pneumatic tyre rollers, tailored to precise mix designs and layer thickness requirements. |
| Layer thickness | Layer thickness is cautiously controlled and adjusted primarily based on the challenge specifications and traffic masses to ensure the most advantageous pavement performance. |
| Quality control measures | Ordinary density testing, moisture content assessment, and temperature tracking in the course of construction are applied to maintain desired compaction stages. |
| Climate considerations | Saudi Arabia’s numerous climates, ranging from extraordinarily hot to colder conditions, necessitate strong compaction strategies for durable and long-lasting street infrastructure. |
| Adherence to standards | Adherence to enterprise standards and specs is important in achieving high asphalt compaction and basic pavement durability. |
6 Models for predicting permanent deformation
In general, the models so far developed for rut analysis have unique features in terms of accuracy, generality, data requirement, and format of presenting the output. The basis for establishing predictive models for determining the rutting phenomenon correlates with the difficulties associated with the classical relationship between the variables, which cannot be determined either by laboratory tests or fieldwork. In the laboratory, the rutting phenomenon is usually based on the loading testing through creep, dynamic, and repeated conditions, which resulted in uniaxial, tri-axial, and sometimes diametric strain [156].
6.1 Empirical models for rutting determination
For the empirical model, the parameters under consideration are traffic conditions and the prevailing weather of the environment [157]. Several studies indicated that the permanent deformation is attributed to the outcome of majorly repeated loading [158], [159], [160], [161], [162]. Table 8 gives a more detailed description of some recent empirical models developed for determining permanent deformation.
Empirical model for rutting analysis.
| S/No | Ref. | Parameters | Model | Laboratory test |
| 1 | [163] |
ε
p
= permanent plastic strain Repeated axial
N = number of load T = temperature σ = stress level, psi η = viscosity, Pas Ac = asphalt content, % |
logε p = −9.473 + 0.532logN + 1.798logT + 0.838logσ-0.672logη + 0.448logAC | Repeated load |
| 2 | [10] |
εp(N) = permanent strain for Nth repetition
er = resilient strain N = number of repetitions α, μ = characteristics of materials based on intercept and slope coefficients |
ε p = CσN a | Axial creep test |
| 3 | [164] |
N = number of repetitions
εp = plastic strain testing εr = resilient strain T = temperature |
|
Repeated load testing |
| 4 | [165] |
εp = permanent strain Multi-step
N = number of load cycles Aa = material property functions of resilient modulus and applied stress m = material parameter |
|
Multi-step cycles dynamic tests |
| 5 | [166] |
εp(N) = permanent strain per pulse
α = 1 − S load tests S = slope of the line on a log-log plot of permanent strain vsN e = peak haversine load strain for a load pulse of duration(d) |
ε p (N) = e r μN −a | Uniaxial repeated load tests |
| 6 | [55] |
ε
vp
= viscoelastic strain
σ = stress level t = time of loading A, n, and mare creep (time hardening)model parameters |
ε vp = Aσ n t m | Dynamic triaxial (creep) test results |
| 7 | [167] | Δ
p−AC
= Accumulated permanent deformationh
AC
= is the thickness of the layer AC
ε p−AC = is the accumulated deformation in layer AC |
Δ p-AC = ε p−AC × h AC | Triaxial compression Test |
Aside aforementioned empirical approaches for modeling rutting in asphaltic pavement, the most prominent model is the layer strain model. This model relies on the laboratory test results, model, and adopts the linear and non-linear elastic theory to visualize the pavement structure and quantify the significance of the depth of the rutting. The complexity associated with the implementation of the non-linear approach ceased its wider usage despite having promising outcomes when compared with the linear method [100]. For computation purposes, each of the layers is usually sliced into several slices, and the stress induced by each slice is then calculated at the centre of its slice. This gives ease with which the rutting can be determined based on the specific number of repeated loads. While the laboratory data is employed to determine the strain experienced by each layer. The summation of strain obtained from slices in each is then combined to give permanent deformation of each layer, and this can be related to the formula below.
where:
Above equation (i) is the conventional representation of the model. It is worth noting that this approach has been used and modified by many researchers to fit certain conditions. To explore more about this approach shell methodology, which establishes the relationships between the stiffness of material and that of bitumen, and the VESYS Elastic approach, which uses elastic or viscoelastic methods to determine responses from the material characteristics such as stress, strain, and deflection, were developed based on the assumption of this approach [10], 168].
6.2 Machine learning models
Machine learning models usually consist of underlying algorithms that allow the computer to learn from the input data. The approach of machine learning can be categorized as supervised, which uses both input and output from model training, and unsupervised, which considers input data for model development [13]. More accurate and reliable solutions are achieved alternatively through the implementation of Machine learning models, especially for solving complex engineering problems [169]. The very primary essence of developing machine learning models for asphaltic concrete pavement is to assist road engineers in having a real glance at the future pavement condition using current and available data so that proper resources can be allocated for maintenance. These models are essential elements for pavement maintenance management systems (PMMS) [170]. Most of the pavement condition assessments rely heavily on the historical field information of the asphalt pavement, and costlier methods of data collection; these challenges give a machine learning approach a competitive advantage over other conventional approaches for predicting the likely future condition of the pavement [171]. However, overfitting is prone to occur, especially when an Artificial Neural Network is used for the prediction. The overfitting phenomenon usually occurs when the training data used is smaller compared to the testing data employed. This is to indicate that the model could hardly understand new, subsequent data entirely accurately based on the training phase it undergoes [55].
However, many studies have been conducted using artificial neural networks (ANN), among them is the work that obtained a fitting and precise result of a non-linear modeling function for predicting rutting in the asphalt pavement by using the backpropagation algorithm of the artificial neural network [172]. Also, a neural network backpropagation approach was used for modeling the pavement condition index [173]. Correlation with the findings using artificial neural networks and genetic programming, and laboratory results was observed [174]. Machine learning techniques have been applied to create rutting prediction models, the use of facts from the long-term Pavement performance database [2]. The accuracy of any machine model is pivoted on the number of parameters and the approaches involved in modeling the pavement performance; therefore, it is very crucial to select sufficient and relevant parameters and then overlap them with suitable methods for the analysis [175]. Previous studies have adopted computational techniques such as PCA, ANNs, and regression analysis to determine a rutting depth predictive model [176], [177], [178], [179], [180]. These models exhibit relatively high accuracy levels and contain superior performance. They not only support the interpretation of the possible factors that may affect rutting, but more importantly, they assist in decision-making about pavement maintenance or repair strategies using predicted rutting severity or the possible rutting development trends.
In Saudi Arabia, numerous monitoring techniques and equipment are employed to evaluate rutting on highways. The Mechanistic-Empirical Pavement Design Guide (MEPDG) software is utilized to predict pavement distress like rutting primarily based on fabric homes, roadbed traits, weather, and site visitors masses [45]. The Ministry of Transport (MOT) collects pavement condition statistics by the use of the road floor Tester (RST) vehicle, measuring roughness (ROU), rutting (RUT), cracking (CRA), and raveling (RAV) to analyze the relationship between global Roughness Index (IRI) and pavement damage, which includes rutting [181], 182]. Moreover, the Pavement maintenance control machine (PMMS) in Riyadh makes use of visible tests, structural capacity roughness, and skid resistance to evaluate pavement situations, with the International Roughness Index (IRI) presenting quick and cost-effective statistics on avenue roughness, aiding in assessing rutting and different distress types [46].
6.3 Numerical methods for modelling
Some of the numerical approaches employed for the modelling permanent deformation include multi-layer elastic theory, Finite Difference Method (FDM), Discrete Element Method (DEM), and Finite Element Method (FEM) which were revealed to be more robust and flexible for adoption in modelling irregularly shaped and more complex aggregates forming asphaltic system. The ability to manage varieties of loading options, a wide range of material numeration, and unlimited boundary conditions to analyze permanent deformations related to the behaviours of viscoelastic material are some features of these numerical models [183].
7 Control and mitigation strategies of rutting through the addition of admixtures
In an attempt to minimize the effect of rutting, several works have been conducted to add new additives or modify the conventional content of the mix to control the rutting effects. Generally, an admixture with high modulus gives a better rutting resistance capacity when compared to a control mix [178]. Confining the content of uncrushed aggregate to a maximum of 15 % of the total volume of the pavements was recommended as a remedy for maximizing the rate of permanent deformation [184]. Adding glass fiber to an optimum percentage of 8 of the total volume of the binder gives an enhanced value of resistance to rutting [112]. Also promising result of rutting resistance was observed when the mix was modified with epoxy resin as an admixture [185]. Due to its availability and binding properties, an optimal dosage of 2.5 % of the total weight of aggregate, hydrated lime probes to be an agent of resistance to rutting [186]. Even 1.5 % was claimed to suffice for the control mix [187]. Incorporating hydrated lime within the mix of asphalt as a replacement for limestone filler indicates a promising result for resisting permanent deformation. It is also comparatively cheap to other additive minerals such as polymers [37]. Retarding the rate of deformation during the summer period is increased by the addition of lime due to its higher stiffness properties, which help in strengthens the bonding between aggregate and asphalt [187].
The susceptibility of asphalt mix caused due to high temperature can be reduced by implementing polymer-modified bitumen, which in turn reduces the rate of permanent deformation [33]. A comparative experiment was conducted on limestone and basalt Super-pave asphalt mixtures to determine the rutting depth using a dynamic creep test in which the purely blended Super-pave mix was blended with 1 % by weight of the basalt aggregate with hydrated lime to act as filler. The blended mix exhibits high resistance capability at varied subjected temperatures and constant loading [188]. Local contractors also consider the addition of polymeric material as crucial to the resistance of rutting, thus resulting in a considerable reduction of maintenance and rehabilitation costs [189]. And selection process depends entirely on all the classes of polymer i.e., Plastomers, Elastomers, reclaimed rubber, and Fibres, etc., used for rutting control as an additive to the asphalt mix. Their compatible properties are the main factor to consider while selecting a suitable polymer [54].
Although not popular due to the difficulties and other technical considerations while working with them, geo-grid materials were found to be a promising material for solving the pavement distress caused by rutting in asphaltic pavements. The type and location of geo-grid material within the pavement layers determine its effective functionality [98], 190], 191]. Also, reinforcing the soil subgrade with an appropriate geo-grid material protects the layers and renders plastic deformation immaterial within the layers [192]. Aiding sustainability in pavement construction brought about the usage of other waste as either binder or modifiers in mitigating the rutting problem. Given this, also, the usage of waste cooking oil as a binder rejuvenator in asphalt block is found to be promising [193]. Polyethylene Terephthalate (PET) is also a reliable bio-polymer for retarding the effect of rutting in concrete asphalt when subjected to static and dynamic loadings [194]. The threat of land degradation, which may be caused by uncontrolled dumping of such may be minimized when utilized as an additive to the pavement mix [195]. Intensified quality control should be implemented as part of the considerations while using additive modifiers and other polymeric materials in asphalt, plastic size, shear rate, and mixing temperature [196].
In regions with climate variabilities like Saudi Arabia, several field-based studies have demonstrated the overall performance of rutting mitigation techniques. For instance, a task in Doha, Qatar, applied polymer-changed bitumen (PMB) on arterial roads, resulting in up to 32 % reduction in rut depth over summer cycles, in comparison to standard bitumen [135]. Similarly, in Abu Dhabi, UAE, hydrated lime changed into delivered at 2 % by using combination weight in a dense-graded asphalt mixture, showing enhanced rutting resistance and a 25 % decrease in maintenance frequency in the first 5 years [197]. In Muscat, Oman, discipline trials regarding geo-grid reinforcement within the base layer progressed pavement balance beneath high-temperature truck visitors’ corridors, lowering floor rutting by up to 40 % in comparison to non-strengthened sections [198]. These local case studies confirm the effectiveness of the mentioned admixtures and modifiers under harsh thermal conditions, validating their applicability within Saudi Arabia’s infrastructure system.
Reinforcement of asphalt concrete is intended to prevent reflection cracking by the use of geo-synthetic materials as a reinforcing mechanism in pavement structures in road bases and embankments [199], 200]. Following material characteristics are associated with rutting susceptibility: high percentages of natural sand [201], high amounts of fine-grained aggregate [94], rounded aggregate particles [202], excessive amounts of moisture permitted in the mix or granular materials and soils, and cold weather paving that results in ineffective compaction [203]. The selection of the above-mentioned materials and their systematic usage signal Saudi Arabia’s intention to create a durable, long-lasting, and sustainable infrastructure that can withstand the arid and hot climatic conditions in the country. Table 9 gives a summary of some studies that were carried out, comprising the material used, testing method, and remarks.
Overview of some literature on rutting control.
| S/N | Ref. | Material used | Test employed | Remark |
|---|---|---|---|---|
| 1 | [67] | Ministry of Transport (MOT) granular base class A and B, subbase material class B, reclaimed asphalt pavement (RAP) material, and Portland Cement (PC) |
CBR, Split tensile strength (STS), and Resilient modulus test (RSMT) | The study reveals that base class A has the least rutting in dry conditions at 50 °C, followed by base class B, foamed SB, and foamed RAP in soaked conditions. |
| 2 | [204] | Waste crumb rubber (WCR) and Sulphur | Rheological tests (RT) | Utilizing sulphur and waste crumb rubber in asphalt modification extends pavement life, meets increased demand, lowers pavement costs, and addresses waste disposal issues. |
| 3 | [22] | Dolomite sand, sand material, blast oxygen furnace steel slag | Resistance to permanent deformations and fatigue resistance | Laboratory tests showed strong plastic deformation resistance and good fatigue failure resistance in asphalt concrete mixtures containing steel slag, limestone, and dolomite sand waste. |
| 4 | [67], 205] | Oil fly ash (OFA), concentrated sulfuric acid (H2SO4, 98 %), nitric acid (HNO3, 68 %), and asphalt cement of 60/70 penetration grade | RT | The modified OFA binder, when increased in COOH content, decreased activation energy, making it more resistant to low temperatures, demonstrating improved asphalt mixture characteristics. |
| 5 | [161] | Cement dust waste, Ordinary Portland Cement (OPC) | Marshall test (MT) | Experimental results show that replacing conventional mineral filler with cement dust or OPC results in a new hot mix asphalt with lower flow, increased stability, bulk density, and VFA-filled voids. |
| 6 | [134] | Low-density polyethylene, high-density polyethylene, and crumb rubber | RT | The modified binder made of low-density polyethylene (LDPE), high-density polyethylene (HDPE), and crumb rubber (CR) shown a noteworthy enhancement in the binder’s rheological characteristics. |
| 7 | [206] | Polyethylene modified, aggregates, recycled plastic wastes, and PC | Compressive strength test (CST), flexural strength test (FST), moisture resistance test (MRT), rutting resistance test (RPP test), crack healing efficiency test, and thermal sensitivity test | Further research on RPBCs’ volumetric properties, ideal grade, fatigue, and rutting performance, damping, and radiation absorption qualities is recommended for pavement application objectives. |
| 8 | [207] | Silica fume (SF) | Marshall, direct compression (DC), indirect tensile strength (ITS), and wheel tracking (WT) | Rutting depth is decreased by roughly 35.82 % when SF is included. While the ITS value improves by roughly 3.83 %, the DC value increases by roughly 25 %. Lastly, SF addition to asphalt cement improves the qualities of hot mix asphalt. |
| 9 | [208] | Aggregate & reclaimed Asphalt pavement (RAP), commercial rejuvenator (CR), waste engine oil, asphalt, and aggregate blending |
ITS, durability, and resilient modulus (RM) | The research suggests that waste engine oil can be a sustainable alternative to commercial rejuvenators in asphalt mixtures with high RAP content. Mixes with 30–40 % RAP and 7–13 % waste engine oil have similar properties, promoting sustainability in road construction. |
| 10 | [209] | Rubber, polyethylene, lime, nano silica (NS), and silica fume (SF) | Marshall, ITS, DC, and WT | According to the findings, NS is regarded as the best modifier since it produced the highest levels of stability, lowest flow, tensile strength, direct compression strength, and rutting depth. |
| 11 | [210] | Desert and river sands | ITS, uniaxial repeated loading and repeated flexural beam tests | The study found that high natural sand content in asphalt concrete mixes has lower resilience modulus, increased fatigue resistance, and rutting sensitivity. A revision of local specifications is needed. |
| 12 | [211] | Aggregate and asphalt binder “A 64–12 performance grade (PG)”, chicken feather (CF) | Rutting test (RT), moisture sensitivity test (MST), and ITS | The asphalt concrete’s resistance to rutting, stability, and moisture sensitivity can all be enhanced by the CF, according to the results. The findings of the extended moisture test demonstrated that the asphalt can prevent the CF from biodegrading. |
| 13 | [212] | Asphalt cement, coarse and fine aggregates, steel slag (SS), and construction waste (CW) | Marshall test (MT) | |
| 14 | [213] | Aggregate, bitumen, bentonite, | MT, ultrasonic pulse velocity (UPV) measurement, and freeze and thaw (FT) | The outcomes demonstrated the practicality of adding natural bentonite clay (NBC) to asphalt mixtures to enhance the mixtures’ characteristics, especially in conditions where asphalt pavement is subjected to alternating FT cycles that alternate. |
| 15 | [214] | Bituminous surface treatment (MAST) and double bituminous surface treatment (DBST) | Visual inspection and light-falling weight deflectometer | A pavement produced with a combination of MAST as the surface layer and RCC as the base layer presents a promising result compared to the conventional asphalt concrete roads, especially in roads that induce relatively high traffic loads. |
| 16 | [215] | Macro-synthetic (MS) fibre | Weight change, ultrasonic pulse velocity, dynamic modulus of elasticity, skid resistance, flexural and compressive strength tests | The comparative outcome of the results indicates the superiority of concrete roller compacted concrete produced with MS fibre utilization in RCC production over the conventional roller compacted concrete |
| 17 | [216] | Epoxy asphalt concrete (EAC), modified with glass fibre (FEAC) | Viscosity test and direct tensile test | Optimum content of glass fibre leads to improved viscosity of the mix, coupled with incremental tensile strength. Additionally, there is a noticeable enhancement in reducing the resistance and moisture susceptibility of FEAC. However, permeability, friction, and high-temperature stability due to the addition of the glass are not promising |
| 18 | [217] | Synthetic polymers | Mechanical and durability properties tests | Concrete produced by incorporating polymers, named as polymer concrete (PC), was found to be an excellent candidate with desired properties including enhanced strength-to-weight ratios, durability, and chemical resistance, concrete. |
| 19 | [218] | Artificial aggregates | 3D printing technology | Favoring the standard mix of pavement, coarse aggregate synthesized from 3D printing via the grouting molding process presents a desirable result in terms of physical and mechanical performance. However, inflated production costs cannot be ignored as they may hinder its full utilization against conventional coarse aggregate. |
7.1 Interdisciplinary relevance and potential Impact
This section explores various pavement rutting mitigation techniques, including the use of high-performance asphalt combinations and modifiers like polymers, fibers, and recycled materials. Superior compaction techniques ensure a denser, extra uniform pavement shape and decrease susceptibility to deformation. Geo-synthetics, consisting of geogrids and geotextiles, are used to enhance the pavement layers and distribute loads more efficiently. Additionally, present-day technology, like mechanistic-empirical pavement design methods, allows for more particular prediction and mitigation of rutting by focusing on traffic patterns and environmental conditions. The usage of advanced monitoring structures, which include floor-penetrating radar and laser-based floor profilers, enables non-stop assessment of pavement conditions, facilitating well-timed renovation and rehabilitation. Combining those strategies and technologies creates a complete approach to significantly lessen the prevalence and severity of rutting in pavements, improving their sturdiness and overall performance.
Moreover, other ingredients used in asphalt concrete mixture, such as recycled asphalt materials (RAMs), also need to follow certain measures to counter crack development, although the use of softer binders and recycling agents can mitigate recycled binders [219], 220]. In addition, there are the anti-rut agents: polyolefin and polyphenylene sulfide, of which an experimental investigation has established evidence in their anti-rut performance in asphalt mixtures through the formulation of a network structure within the asphalt [221].
The application of innovative materials is critical in preventing rutting. The improvement of the stability and anti-deformation characteristics of asphalt mixtures with a pellet-type anti-stripping additive has been proven to enhance resistance to fatigue, moisture, and rutting. Thus, improving the life expectancy of pavements and minimizing maintenance costs [222]. Also, incorporating Nano-silica in asphalt binders affects the complex shear modulus, increased stiffness characteristics, and intensity of rutting at optimal sizes of the Nano-silica and composition level is increased [223]. Through the establishment of better-performing materials, specifically, anti-stripping warm mix asphalt and Nano-silica modified bitumen, the road construction industry can get rid of rutting [224]. Moreover, the usage of bitumen-stabilized materials (BSM) with bitumen dispersed in the aggregates for base layers presents flexibility, durability, and resistance to moisture, addressing the shortcomings of traditional bases [225]. Incorporating polypropylene fibers in hot mix asphalt enhances rutting resistance and increases moisture harm resistance, contributing to improved overall street performance [226]. Likewise, implementing progressive patching materials, making use of induction heating technology and composite fiber-glass materials, has proven durability and sustainability, lowering charges and environmental impacts [227].
In evaluating the efficiencies of varied strategies for combating rutting in light of the conditions of Saudi Arabia, there are relatively recent works that offer helpful information. Among these is the study conducted to assess the performance of polymer-modified asphalt mixes, which are used frequently in that region due to the high temperature prevalence. The study also looked at different polymers such as Lucolast 7010, Anglomak 2144, paviflex140, SBS KTR 401, and EE-2, revealing that Anglomak 2144 proved to be the most effective in enhancing the mechanical properties of the binder as well as reducing rutting deformation [228]. Additionally, application of fly ash, which is a by-product waste from electric power generation plants to the asphalt mixtures improves the mix’s rutting resistance value and reduces the environmental harm [154]. Moreover, Saudi Arabia, like other Middle Eastern states, has photovoltaic module desert soiling that could be minimized through the application of anti-soiling coatings (ASC) and tracking algorithms that reduce soiling losses by up to 85 % if both interventions are implemented [229].
Polymer-modified asphalt and recycled PET are promising options for addressing rutting issues in Saudi Arabia due to the region’s hot climate. These technologies show potential for improving infrastructure sustainability and reducing pavement rutting. Figure 11 presents materials that are most widely used for rutting mitigation, extensive. It was found that improved aggregate quality accounts for 56.21 %, followed by techniques to mitigate rutting in pavement – such as Modified Binders at 17.75 % and Maintenance Strategies (e.g., Overlay, Surface Treatments) at 15.38 %.
Proportion of research on mitigation strategies.
8 Research and development
Modern technology and effective modeling help in identifying rut formation in asphalt concrete pavements. Techniques include creating mathematical models, using imaging techniques, and conducting accelerated pavement tests to study traffic conditions, enabling effective prevention of pavement distress. Advancements in technology and knowledge are being made to improve asphalt pavement resistance to rutting [230]. This involves using superior cementitious materials and blend compositions. Emerging testing and modeling technologies are also playing a key role in utilizing rutting preventive actions in asphalt concrete [231]. Additives, such as crumb rubber, were evidently found to enhance the flow and stability of the asphaltic concrete when serving as a substitute for fine aggregate [232]. Additionally, increasing the Olive Husk Ash (OHA) up to 20 % in the asphalt-cement mix resulted in promising and enhanced properties [233].
Research in the area of rutting in asphalt concrete or intra-granular fracture is also ongoing, especially on the factors that may lead to this distress, the identification of the test guidelines, and techniques to address the issue. Out of those, attempts were made to underline that the minimization of permanent deformation could yield great benefits in terms of long-lasting pavements and safe highways [15]. Measures include, to this end: Implementing superior computational intelligence models such as finite element models and soft computing, implementing modifiers and better aggregate interlocks to reduce rutting [148]. Also, there is research on new and creative ideas, like high ash composite modified rock asphalt for the enhancement of the performance properties of pavement and rutting resistance. Thus, for instance, intelligent aggregates that are fitted with high-precision sensors could allow for direct assessments of rutting deformations in real time without compromising the integrity of the pavement structure [224]. These extensive research studies seek to present an inclusive study of rutting in asphalt concrete on the basis of grooming techniques that would boost the strength and safety of pavements.
Moreover, the ongoing research regarding rutting prevention includes different approaches to computing, minimizing, and identifying the principal pavement distress [225]. Lowering the oscillation in temperature with the help of other approaches, such as the microencapsulated phase change materials, has also been studied to help mitigate rutting [226]. This is in line with the recent developments in imagery processing and deep learning enabled the construction of a road rutting dataset and the use of object identification and semantic segmentation models for the precise identification and analysis of rutting [227].
Future research on rutting in Saudi Arabia’s asphalt concrete can enhance infrastructure by addressing extreme climate issues, researching accelerants and plasticizers, developing models for specific environmental and traffic systems, identifying environmentally friendly materials, recycling strategies, and implementing predictive maintenance technologies. The collaboration between international research organizations and local capacity building can foster innovation and improve road safety, strength, and sustainability [228]. High-performance asphalt mixtures, rational testing, and sustainable materials contribute to pavement performance and durability. However, most of the attempts were to replicate perpetual pavement, which is usually designed to sustain 50 years of traffic without major rehabilitations [234]. Due to limited accessible data from Saudi Arabia, information regarding resilient and high-performance asphalt mixtures remains scarce [235], 236].
In addition to the technology enhancement, the economic aspect of incorporating high-performance asphalt mixtures in Saudi Arabian road construction projects is also a factor that should be taken into consideration. The up-front expense for advanced binders, fibres, and nanomaterials can be higher than traditional materials, But the benefits over time, extended pavement life, reduced need for maintenance, and fewer delays from road closures for repairs can result in significant long-term cost savings over the life of the pavement. Considering the high temperature extremes and heavy traffic volume in Saudi Arabia, the investment in durable materials presents more economically intelligent decision. Cost-benefit model that considers the Saudi Arabian context might assist the decision-makers in using innovative rutting resistance mixtures more commonly in national highway projects.
9 Policy and standards
In the year 2024, the Minister of Transport and Logistics Services in Saudi Arabia launches the Saudi Highway Code, which is a technical documented guidelines meant to be the official reference for all entities in the kingdom. The Saudi Highway Code provides all related entities with specifications and information needed to plan, design, build, operate, and maintain the kingdom’s roads networks. The Code comprises 25 guidelines spanning all aspects of road infrastructure. While none are solely dedicated to rutting, at least three namely those on pavement design, substance specifications, and preservation practices, offer techniques and technical parameters that cope with rutting prevention and enhance basic pavement sturdiness. These include provisions for high-temperature binder grades, progressed mixture gradation, and performance-primarily based specs tailor-made to Saudi Arabia’s climatic and loading conditions. The Code includes revised guidelines that immediately target rutting resistance. These include superior testing techniques, which include MSCR and DSR to evaluate binder performance under excessive temperatures. Additionally, the code promotes mechanistic-empirical pavement design and stricter specifications for asphalt blend stiffness and rut intensity tolerances, ensuring better pavement durability below growing traffic masses.
10 International comparisons
Rutting problems in Saudi Arabia are influenced by harsh weather conditions, such as changing temperatures, high summer heat, and constant sandstorms. Countries like the UAE and Kuwait use high-performance asphalt mixtures and improved additives to address these issues. Countries like Canada and Sweden use thicker asphalt layers and anti-freeze additives to counter rutting. Countries like America and Europe handle rutting issues with measures considering both natural and traffic conditions. Saudi Arabia should adopt individual solutions, such as high-performance materials and design concepts, and incorporate international best practices adapted to local conditions for long-term solutions.
11 Conclusions
Drawn from this review that the assessment of identified parameters concerning the potential for rutting in the design of pavements is significant for the sustainability of road networks. Other considerations, like properties of asphalt binder, characteristics of aggregates, and the construction of the pavement section concerning its thickness, are some of the influential aspects in controlling rutting on a pavement. If all these parameters of design are well understood and implemented in guided manner, then engineers and planners involved could be able to design pavements that are strong, durable, and have the ability to endure the pressure exerted by traffic and weather factors. It is thus important to assess these factors continually and model them appropriately to offer the best pavement designs that can be sustainable and less expensive, with more rutting resistance.
An appropriate reinforcement and thickness of pavement is critical to be able to resist the repetitive stresses imposed by vehicles and uphold the structural soundness. Tackling those limitations mandates a holistic method that integrates long-lasting materials resilient to climatic conditions, state-of-the-art engineering methodologies, and continuous protection protocols. Through a clear comprehension and adjustment to the precise challenges encountered in Saudi Arabia, the concrete pavement may be formulated and set up to comply with stringent overall performance criteria, thereby ensuring the safety and sustainability of transportation infrastructure.
Deformations in asphalt concrete are still a major concern in the Saudi Arabian pavement network, mainly due to the challenging regional climate, together with growing traffic loads. This review has brought to light the complexity of the phenomenon of rutting, in which material properties and mix design, environmental conditions, as well as the applied load, all play an important role. The status of pavement design systems and standards being used in Saudi Arabia is relatively sound. Nonetheless, the existing systems need to be periodically updated to include new findings and technologies. It also highlighted the need for an approach emphasizing the comparison with other countries to come up with solutions that would effectively address the Saudi Arabian circumstances.
Hence, one of the most efficient ways to manage rutting appropriately is to study new materials and improved additives that will enhance the overall capabilities of the asphalt system in high-temperature and abrasive areas. Employing leading-edge strategies in monitoring and maintenance can be a preventative means to recognize and curb early signs of rutting. Besides, top-down and bottom-up approaches will play a significant role in the formulation of resilient, sustainable pavement solutions that will be achieved through research collaborations both locally and abroad.
Future research has to examine modelling approaches and their translation to new contexts, the effectiveness of different modifiers, and the use of environmentally friendly and biodegradable materials.
These key points show that Saudi Arabia can enhance the performance throughout the service life of its asphalt pavements in these areas to boost the nation’s infrastructure toughness and support Vision 2030. All these will work well in terms of having pavements that not just meet the current traffic load, but also that will meet the future needs.
12 Recommendations
Having presented a wider range of findings from research, Laboratory experiments, and models, the extended research on permanent deformation is still far from complete concerning the generalized understanding of the phenomenon, factors, remedies, and the process of its minimization. Therefore, based on the findings of this review, the following recommendations are proposed to address rutting in asphalt concrete in Saudi Arabia.
Advanced Material Research and Enhancement: Investigate the effectiveness of production and incorporation of superior asphalt mixtures and chemical additives, including polymers and fiber for enhanced rutting resistance. Emphasis should be placed on the materials that are suitable and durable for Saudi Arabia regions, specifically those that are heat and abrasion-resistant. At the material-based stage, modification is necessary, especially related to upgrading the binder material from softer to relatively harder grades in hotter regions. This is with emphasis on alternatively modifying the content with polymers.
Predictive Modeling: Use field and laboratory data to build and test models that allow for the numerical simulation of the rutting of asphalt pavements in the regional climate. These models should incorporate features like high temperature, traffic loads, and sandstorms to ensure that they give reliable predictions and guide designs.
Sustainable Practices: Discover effective ways and means involved in using sustainable materials and recycling methodologies in the construction of asphalt pavements. This is by the vision of Saudi Arabia Vision 2030, which encourages environmental sustainability and its application in the construction sector.
Monitoring and Maintenance Technologies and Intelligent Approach Adoption: Use of sophisticated technologies for early signs of rutting detection, including the Ground Penetrating Radar (GPR), and SPD Surface Deflection Tests (SPD) with respective accuracies of 95.1 % and 85–95 %, will facilitate early detection of the rutting [228], 229], 237]. Also, implementing the application of advanced analytical techniques and smart technologies, such as the use of smart sensors for early identification of pavement problems before they become severe. The temperature variations are usually uncontrollable, which aids in causing the pavement to undergo permanent deformation. To overcome this effect, an emerging technology such as intelligent compaction (IC) and continuous compaction monitoring should be employed for regulating the temperature variation, especially in gulf regions.
Collaborative Research: Strengthen partnerships among research institutions. This partnership may kick-start the process of promoting the sharing of information and ideas between the academic and industrial sectors to enhance the performance of pavements.
Training and Capacity Building: Emphasis on ensuring enhanced training and capacity building programs for the engineers and technicians, particularly those who work on pavement design, construction, and maintenance. Educating these specialists with the latest knowledge and techniques to solve rutting issues and other related pavement problems.
Microstructural Analysis: Most of these processes involved in rutting are to be fully understood through internal processes between aggregate, binder materials, and asphalt. It is essential to give more emphasis to the study of the rutting effect and other distress phenomena related to asphaltic pavement at the microstructural level. This is due to the complexities associated with the mechanics of the rutting phenomenon, which usually results from internal disruption caused by external activities. Therefore, the most promising approach to understanding the phenomenon of rutting in asphaltic pavement is to generalize and study it from the microstructural level. Advanced numerical modeling approaches should be implemented to study the effect of rutting at the microstructural level. Also, a semi-quantitative approach should be implemented for checking and validation.
Operational Modification: The general approach of design, construction, and maintenance is another contributing factor to the rutting effect; employing generalized methods may not give satisfactory results for some regions. Therefore development of regionally based design, construction, maintenance, and rehabilitation is worthy of consideration for all stakeholders. This is related to the variation of environmental prevailing conditions, cultural setup, and usage of the roads by aggregated regions. Carrying out previews and feasibility assessments for new material, design, and tech in actual-use settings to fine-tune them. They will also serve as pilot projects that can give useful information and experiences on the eventual scale-up of larger projects. In addition, a localized benchmark with peculiarities in consideration of a specific region is notably effective in minimizing the general deterioration of the pavement structure. Therefore, for the agencies with responsibility for the maintenance and rehabilitation of roads, it is paramount to develop a regionally based pavement management system with specialized features focusing on identifying permanent deformation at an earlier stage for proper attainment.
Open-Source Data Platform: Researchers encounter difficulties when assessing pavement-related data. Having an open-source database available for researchers is important to enhance the research quantitatively and qualitatively, which can contribute to solving issues. For instance, the Long-Term Pavement Performance (LTPP) has a tremendous amount of pavement data, including pavement performance and parameters for many road sections across the United States and Canada. Such a program assists researchers in getting data, considering that many agencies in Saudi Arabia have valuable and sophisticated pavement-related data.
By adopting these suggestions, Saudi Arabia can enhance the durability and performance of its asphalt pavements, ensuring they meet present-day and future needs. This comprehensive approach will contribute to the country’s infrastructure resilience and aid mission for sustainable development and economic growth.
-
Funding information: The author extends their appreciation to the Deanship of Postgraduate Studies and Scientific Research at Majmaah University for funding this research work through the project number (R-2025-2059).
-
Author contribution: Conceptualization, Mohammed Ibrahim Albuaymi and Auwal Alhassan Musa; Methodology, Mohammed Ibrahim Albuaymi; Data curation, Mohammed Ibrahim Albuaymi.; Writing – original draft, Auwal Alhassan Musa.; Writing – review and editing, Mohammed Ibrahim Albuaymi and Auwal Alhassan Musa; Project administration, Mohammed Ibrahim Albuaymi. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Conflict of interest: The authors state no conflict of interest.
-
Data availability statement: Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
References
1. Xie, N, Wang, H, Feng, D. Coating materials to increase pavement surface reflectance, Eco-efficient materials for mitigating building cooling needs. 2015:13–35. https://doi.org/10.1016/B978-1-78242-380-5.00002-9.Search in Google Scholar
2. Alnaqbi, AJ, Zeiada, W, Al-Khateeb, GG, Hamad, K, Barakat, S. Creating rutting prediction models through machine learning techniques utilizing the long-term pavement performance database. Sustainability 2023;15:13653. https://doi.org/10.3390/su151813653.Search in Google Scholar
3. Al-mosawe, H, Nick, T. Prediction of permanent deformation in asphalt mixtures [PhD diss.]. Nottingham: University of Nottingham; 2016.Search in Google Scholar
4. Yasir, A, Muhammad, I, Sarfraz, A, Shafeeq, A. Empirical correlation of permanent deformation tests for evaluating the rutting response of conventional asphaltic concrete mixtures. J Mater Civ Eng 2012;29:1–9. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001888.Search in Google Scholar
5. Haas, R, Meyer, F. Bituminous mixtures, aggregates, and pavements. Washington, D.C.: National Research Council (U.S.). Transportation Research Board; 1975:1–63 pp.Search in Google Scholar
6. Hamdar, YS, Bakchan, A, Chehab, GR, Al-qadi, I, Little, D. Benchmarking pavement practices in data-scarce regions – case of Saudi Arabia. Int J Pavement Eng 2019;22:1–13. https://doi.org/10.1080/10298436.2019.1606914.Search in Google Scholar
7. Pasandín, AR, Pérez, I. Fatigue performance of bituminous mixtures made with recycled concrete aggregates and waste tire rubber. Constr Build Mater 2017;157:26–33. https://doi.org/10.1016/j.conbuildmat.2017.09.090.Search in Google Scholar
8. Sirin, O, Paul, DK, Kassem, E, Ohiduzzaman, M. Effect of ageing on asphalt binders in the State of Qatar: a case study. Road Mater Pavement Des 2017;18(4 suppl):165–84. https://doi.org/10.1080/14680629.2017.1389094 Search in Google Scholar
9. Sulyman, M, Sienkiewicz, M, Haponiuk, J. Asphalt pavement material improvement: a review. Int J Environ Sci Dev 2014;5:444–54. https://doi.org/10.7763/IJESD.2014.V5.525.Search in Google Scholar
10. Mahboub, K. Asphalt concrete creep as related to rutting. J Mater Civ Eng 1991;2:147–63. https://doi.org/10.1061/(asce)0899-1561(1990)2:3(147).10.1061/(ASCE)0899-1561(1990)2:3(147)Search in Google Scholar
11. Vallejo, J, Kennedy, TW, Haas, R. Permanent deformation characteristics of asphalt mixtures by repeated-load indirect tensile test. Transp Res Rec 1976;1–85.Search in Google Scholar
12. Bissada, AF. Compatibility of asphalt paving mixtures and relation to permanent deformation. Transp Res Rec 1983;911:1–10.Search in Google Scholar
13. Almazroui, M, Islam, MN, Dambul, R, Jones, PD. Trends of temperature extremes in Saudi Arabia. Int J Climatol 2014;34:808–26. https://doi.org/10.1002/joc.3722.Search in Google Scholar
14. Al-Mosaind, M. Traffic conditions in emerging university campuses: King Saud University, Riyadh, Saudi Arabia. J Sustain Dev 2014;7:204–13. https://doi.org/10.5539/jsd.v7n6p204.Search in Google Scholar
15. Joumblat, R, Al, Z, Al, B, Khateeb, GA, Elkordi, A, Rahman, A, et al.. State-of-the-Art review on permanent deformation characterization of asphalt concrete pavements. Sustainability 2023;15:1–34. https://doi.org/10.3390/su15021166.Search in Google Scholar
16. Majidzadeh, K, Bayomy, F, Khedr, S. Rutting evaluation of subgrade soils in Ohio. Transp Res Rec 1976;671:75–84.Search in Google Scholar
17. Albayati, Amjad H, Hassan, A-M. Influence of different factors on permanent deformation of hot asphalt concrete mixtures. Civ Environ Eng 2023;19:555–67. https://doi.org/10.2478/cee-2023-0050.Search in Google Scholar
18. Ali, S, Cui, HZ, Zhang, H, Xing, F. Utilization of macro-encapsulated phase change materials for the development of thermal energy storage and structural lightweight aggregate concrete. Appl Energy 2015;139:43–55. https://doi.org/10.1016/j.apenergy.2014.11.022.Search in Google Scholar
19. Laukkanen, OV, Soenen, H, Pellinen, T, Heyrman, S, Lemoine, G. Creep-recovery behavior of bituminous binders and its relation to asphalt mixture rutting. Mater Struct 2015;48:4039–53. https://doi.org/10.1617/s11527-014-0464-7.Search in Google Scholar
20. Faruk, ANM, Lee, SI, Zhang, J, Naik, B, Walubita, LF. Measurement of HMA shear resistance potential in the lab: the simple punching shear test. Constr Build Mater 2015;99:62–72. https://doi.org/10.1016/j.conbuildmat.2015.09.006.Search in Google Scholar
21. Hadi, DA. MS-2 asphalt mix design methods. Baghdad: Asphalt Institute Mustansiriyh University; 2014, vol 1:1–197 pp.Search in Google Scholar
22. Haritonovs, V, Tihonovs, J. Use of unconventional aggregates in hot mix asphalt concrete. Baltic J Road Bridge Eng 2014;9:276–82. https://doi.org/10.3846/bjrbe.2014.34.Search in Google Scholar
23. Liu, ZB. Asphalt pavement preventive maintenance technology overview. Appl Mech Mat 2014;638–640:1135–8. https://doi.org/10.4028/www.scientific.net/amm.638-640.1135.Search in Google Scholar
24. Hirato, T, Murayama, M, Sasaki, H. Development of high stability hot mix asphalt concrete with hybrid binder. J Traffic Transport Eng 2014;1:424–31. https://doi.org/10.1016/S2095-7564(15)30292-0.Search in Google Scholar
25. Li, Q, Ni, F, Gao, L, Yuan, Q, Xiao, Y. Evaluating the rutting resistance of asphalt mixtures using an advanced repeated load permanent deformation test under field conditions. Constr Build Mater 2014;61:241–51. https://doi.org/10.1016/j.conbuildmat.2014.02.052.Search in Google Scholar
26. Monismith, C, Inkabi, K, Freeme, C, McLean, D, editors. A subsystem to predict rutting in asphalt concrete pavement structures. In: Volume I of Proceedings of 4th international conference on structural design of asphalt pavements, Ann Arbor, Michigan, August 22–26; 1977.Search in Google Scholar
27. Suh, YC, Cho, NH. Development of a rutting performance model for asphalt concrete pavement based on test road and accelerated pavement test data. KSCE J Civ Eng 2014;18:165–71. https://doi.org/10.1007/s12205-014-0394-5.Search in Google Scholar
28. Dai, Q, You, Z. Prediction of creep stiffness of asphalt mixture with micromechanical finite-element and discrete-element models. J Eng Mech 2007;133:163–73. https://doi.org/10.1061/(asce)0733-9399(2007)133:.Search in Google Scholar
29. Mahboub, K, Little, D. Improved asphalt concrete design procedure. Washington, D.C: U.S. Department of Transportation Federal Highway Administration; 1988, vol 474-1F:1–266 pp.Search in Google Scholar
30. Vallerga, BA, Tayebali, AA. Early rutting of asphalt concrete pavement under heavy axle loads in hot desert environment: case history. Transp Res Rec 1995;(1473):25–34.Search in Google Scholar
31. Ahlrich, RC. Influence of aggregate gradation and particle shape/texture on permanent deformation of hot mix asphalt pavements. USA: Auburn University; 1995:1–251 pp.Search in Google Scholar
32. Officials, T. Mechanistic-empirical pavement design guide: a manual of practice. Washington, DC, USA: AASHTO; 2008.Search in Google Scholar
33. AASHTO. Report of the AASHTO joint task force on rutting. American Association of State Highway and Transportation Officials; 1989.Search in Google Scholar
34. Sadek, H, Masad, E, Sirin, O. Performance evaluation of full-scale sections of asphalt pavements in the State of Qatar. J Perform Constr Facil 2015;29:1–14. https://doi.org/10.1061/(ASCE)CF.1943-5509.Search in Google Scholar
35. Krugler, P, Mounce, J, Bentenson, W. Asphalt pavement rutting in the Western states. Two Texas Lectures and the WASHTO Report. Special Study 26.0. Texas State; 1985.Search in Google Scholar
36. Rauhut, JB, Mopac, N, Darter, MI, Ahmad, R. Evaluation of the AASHTO design equations and recommended improvements. Washington, DC: Strategic Highway Research Program National Research Council; 1994:1–219 pp.Search in Google Scholar
37. Griffiths, G, Thom, N. Concrete pavement design guidance notes. Boca Raton, FL: CRC Press; 2019.Search in Google Scholar
38. Saleh, M, Ghorban Ebrahimi, M. Finite element modeling of permanent deformation in the loaded wheel tracker test. Transp Res Rec 2017;2641:94–102. https://doi.org/10.3141/2641-12.Search in Google Scholar
39. Pereira, PA, Pais, JC, Sousa, JB. Modeling the effect of truck speed on permanent deformation of asphalt concrete mixes. USA: TRB 78th Annual Meeting; 1999.Search in Google Scholar
40. Alshabibi, NM, Abdelhamid, HT. Impact assessment of long-term work zones in arterial roads on commercial activities in Dammam metropolitan area, Saudi Arabia. Eng Sci 2018;29:19–36. https://doi.org/10.4197/Eng.Search in Google Scholar
41. Liu, Y, Cao, X, Xu, J, Li, T. Influence of traffic accessibility on land use based on Landsat imagery and internet map: A case study of the Pearl River Delta urban agglomeration. PLoS ONE 2019;14:e0224136. https://doi.org/10.1371/journal.pone.0224136.Search in Google Scholar PubMed PubMed Central
42. Liu, Y, Cao, X, Li, T. Influence of accessibility on land use and landscape pattern based on mapping knowledge domains: review and implications. J Adv Transp 2020;7985715:1–12. https://doi.org/10.1155/2020/7985719.Search in Google Scholar
43. Outay, F, Mengash, HA, Adnan, M. Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: recent advances and challenges. Transp Res Part A 2020;141:116–29. https://doi.org/10.1016/j.tra.2020.09.018.Search in Google Scholar PubMed PubMed Central
44. Ali, H, Al, HI, Wahhab, A, Dalhat, MA, Al-juhani, AA, Al-osta, MA. Case studies in construction materials recycled polyethylene waste as binder stabilizer for SMA Mix in Gulf environment. Case Stud Constr Mater 2023;18:e02177. https://doi.org/10.1016/j.cscm.2023.e02177.Search in Google Scholar
45. Fuhaid, A. Application of mechanistic empirical pavement design guide software in Saudi Arabia. Appl Sci 2022;12. https://doi.org/10.3390/app12168165.Search in Google Scholar
46. Mubaraki, M. Highway subsurface assessment using pavement surface distress and roughness data. Int J Pavement Res Technol 2016;9:393–402. https://doi.org/10.1016/j.ijprt.2016.10.001.Search in Google Scholar
47. Turki, S. Traffic medicine in Saudi Arabia, from prevention to rehabilitation. J Local Global Health Sc 2015;2015:4–6. https://doi.org/10.5888/pcd11.140176.4.Search in Google Scholar
48. Mubaraki, M, Ba, D. An analytical study of the characteristics of the traffic flow in Jazan region, Saudi Arabia. Proc Inst Civ Eng Transp 2018;173:184–94. https://doi.org/10.1680/jtran.18.00009.Search in Google Scholar
49. Mubaraki, M. Study the relationship between pavement surface distress and roughness data. MATEC Web Conf 2016;81:4–8. https://doi.org/10.1051/matecconf/20168102012.Search in Google Scholar
50. Alhusain, F, Alghafees, M, Rezk, A, Alwatban, S, Almoaiqel, F, Alsalamah, M. Exploring the spatio-temporal patterns of road traffic accidents in Saudi Arabia. Saud J Emerg Med 2023;4:12–30. https://doi.org/10.24911/sjemed/72-1669286526.Search in Google Scholar
51. Jiang, X, Li, P, Ding, Z, Yang, L, Zhao, J. Investigations on viscosity and flow behavior of polyphosphoric acid (PPA) modified asphalt at high temperatures. Constr Build Mater 2019;228:116610. https://doi.org/10.1016/j.conbuildmat.2019.07.336.Search in Google Scholar
52. Adwan, I, Milad, A, Memon, ZA, Widyatmoko, I, Zanuri, NA, Memon, NA, et al.. Asphalt pavement temperature prediction models: a review. Appl Sci 2021;11:1–19. https://doi.org/10.3390/app11093794.Search in Google Scholar
53. Lasmar, G, Anoop, B, Mahesh, S, Mustapha, N, Alhassan, AM. Sugarcane bagasse as an alternative material for the reuse of scarified pavement material. Environ Res Technol 2025;8:616–29. https://doi.org/10.35208/ert.1527743.Search in Google Scholar
54. Romain, JE. Rut Depth Prediction Routieres, Brassekss, Research Report No. 150. Belgium: Centre de Recherches Routieres, Brasseks; 1969.Search in Google Scholar
55. Abdullah, GMS. 3D finite element modeling to predict the foamed sulfur asphalt marl soil mixes rutting behavior. Ain Shams Eng J 2019;10:661–8. https://doi.org/10.1016/j.asej.2019.03.005.Search in Google Scholar
56. Dave, EV, Hoplin, C. Flexible pavement thermal cracking performance sensitivity to fracture energy variation of asphalt mixtures. Road Mater Pavement Des 2015;16:423–41. https://doi.org/10.1080/14680629.2015.1029697 Search in Google Scholar
57. Monismith, CL, Epps, JA, Finn, FN. Improved asphalt mix design (with discussion). Suite I St Paul, MN: Association of Asphalt Paving Technologists Proc; 1985, 54:340–406 pp.Search in Google Scholar
58. Collop, AC, Scarpas, AT, Kasbergen, C, Bondt, AD. Development and finite element implementation of stress-dependent elastoviscoplastic constitutive model with damage for asphalt. Transp Res Rec 1832;96–104. https://doi.org/10.3141/1832-12.Search in Google Scholar
59. Collop Decker, DS, Goodrich, JL. Asphalt cement properties related to pavement performance. Suite I St Paul, MN: Association of Asphalt Paving Technologists Proc; 1989, 58:503–18 pp.Search in Google Scholar
60. Yin, F, Arámbula-Mercado, E, Epps Martin, A, Newcomb, D, Tran, N. Long-term ageing of asphalt mixtures. Road Mater Pavement Des 2017;18(1 Suppl):2–27. https://doi.org/10.1080/14680629.2016.1266739 Search in Google Scholar
61. Wang, D. Analytical solutions for temperature profile prediction in multi-layered pavement systems. [Ph.D. thesis]. Champaign, IL: University of Illinois at Urbana-Champaign; 2011.Search in Google Scholar
62. Finn, FN, Margot, YT, TaskJohnJohn, SSC, FinnAmer, FNZD. Asphalt properties and relationship to pavement performance by relationship to pavement performance. Richmond, CA: University of California-Berkeley Institute of Transportation Studies Asphalt Research Program Richmond Field Station; 1990:1–404 pp.Search in Google Scholar
63. Keyser, JH, Ruth, BE. Analysis of asphalt concrete test road sections in the province of Quebec, Canada. Transp Res Rec 1984;968.Search in Google Scholar
64. Solaimanian, M, Kennedy, TW. Predicting maximum pavement surface temperature using maximum air temperature and hourly solar radiation. Transp Res Rec J Transp Res Board 1993;1417.Search in Google Scholar
65. Athar, H. Trends in observed extreme climate indices in Saudi Arabia during 1979–2008. Int J Climatol 2014;34:1561–74. https://doi.org/10.1002/joc.3783.Search in Google Scholar
66. Almazroui, M. Simulation of present and future climate of Saudi Arabia using a regional climate model (PRECIS). Int J Climatol 2013;33:2247–59. https://doi.org/10.1002/joc.3721.Search in Google Scholar
67. Al-Abdul Wahhab, HI, Baig, MG, Mahmoud, IA, Kattan, HM. Study of road bases construction in Saudi Arabia using foam asphalt. Constr Build Mater 2012;26:113–21. https://doi.org/10.1016/j.conbuildmat.2011.05.010.Search in Google Scholar
68. Alshammary, NF, Salama, KF, Zafar, M. Heat stress among steel workers in Al Jubail, Saudi Arabia. J Ecophysiol Occup Health 2020;20:34–40. https://doi.org/10.18311/jeoh/2020/24661.Search in Google Scholar
69. Ajbar, AH, Ali, EM. Prediction of municipal water production in touristic Mecca City in Saudi Arabia using neural networks. J King Saud Univ Eng Sci 2015;27:83–91. https://doi.org/10.1016/j.jksues.2013.01.001.Search in Google Scholar
70. AlQdah, KS. Effect of using natural and local environment contents on the thermal conductivity of building materials; case in Medina, Saudi Arabia. Case Stud Therm Eng 2021;28:101597. https://doi.org/10.1016/j.csite.2021.101597.Search in Google Scholar
71. Alshammari, TO, Guadagnini, M, Pilakoutas, K. The effect of harsh environmental conditions on concrete plastic shrinkage cracks: case study Saudi Arabia. Materials 2022;15:8622. https://doi.org/10.3390/ma15238622.Search in Google Scholar PubMed PubMed Central
72. Krishna, V. Long term temperature trends in four different climatic zones of Saudi Arabia. Int J Appl Sci Technol 2014;4:233–42.Search in Google Scholar
73. Raggad, B. Statistical assessment of changes in extreme maximum temperatures over Saudi Arabia, 1985–2014. Theor Appl Climatol 2018;132:1217–35. https://doi.org/10.1007/s00704-017-2155-0.Search in Google Scholar
74. Al-Ghamdi, SS. Seasonal and location dependence of indoor and soil radon concentrations in two villages, Najran region, Saudi Arabia. Radiat Meas 2014;69:12–17. https://doi.org/10.1016/j.radmeas.2014.07.020.Search in Google Scholar
75. Boretti, A, Castelletto, S, Al-Kouz, W, Nayfeh, J. Enclosed trough solar thermal power plant with thermal energy storage and saltwater condenser in Al Khobar, Kingdom of Saudi Arabia. Renew Energy Focus 2020;35:132–47. https://doi.org/10.1016/j.ref.2020.09.005.Search in Google Scholar
76. Khalil, MAK, Butenhoff, CL, Porter, WC, Almazroui, M, Alkhalaf, A, Al-Sahafi, MS. Air quality in Yanbu, Saudi Arabia. J Air Waste Manag Assoc 2016;66:341–55. https://doi.org/10.1080/10962247.2015.1129999.Search in Google Scholar PubMed
77. Alotaibi, K, Ghumman, AR, Haider, H, Ghazaw, YM, Shafiquzzaman, M. Future predictions of rainfall and temperature using GCM and ANN for arid regions: a case study for the Qassim region, Saudi Arabia. Water 2018;10:1260. https://doi.org/10.3390/w10091260.Search in Google Scholar
78. Mashwani, ZUR. Environment, climate change and biodiversity. In: Environment, climate, plant and vegetation growth. Cham: Springer; 2020:473–501 pp.10.1007/978-3-030-49732-3_19Search in Google Scholar
79. Zaidan, AE, Rainis, R, Abdurrahman, AB, Abdulkadir, M. Flash flood causes in Ha’il city Kingdom of Saudi Arabia using remote sensing data and gis. J Crit Rev 2020;7:144–53. https://doi.org/10.22159/jcr.07.01.26.Search in Google Scholar
80. Naeem, M, Alahmed, AM, Kheir, SM, Sallam, MF. Spatial distribution modeling of Stegomyia aegypti and Culex tritaeniorhynchus (Diptera: Culicidae) in Al-Bahah Province, Kingdom of Saudi Arabia. Trop Biomed 2016;33:295–310.Search in Google Scholar
81. Haq, MA, Ahmed, A. On interesting correlation between meteorological parameters and COVID-19 pandemic in Saudi Arabia. Int J Comput Sci Netw Secur 2022;22:159–68.Search in Google Scholar
82. William, H, Andrews, J. Improving the visibility of railroad-highway grade crossing signals. Washington, DC: Federal Highway Administration; 1987.Search in Google Scholar
83. Narayanan, S, Kathuria, A, Singh, B. Utilization of inferior quality aggregates in asphalt mixes: a systematic review. J Traffic Transport Eng 2022;9:864–79. https://doi.org/10.1016/j.jtte.2022.03.001.Search in Google Scholar
84. Hussan, S, Kamal, MA, Khan, MB, Irfan, M, Hafeez, I. Determining the contribution of different structural layers of asphalt pavement system to rutting using transverse profile analysis. 2013;1:174–80. https://doi.org/10.12691/ajcea-1-6-7.Search in Google Scholar
85. Tarrer, Arthur, R, Vinay, W. Factors influencing mix setting characteristics and tests to predict mix setting characteristics. Transp Res Rec USA 1994;(Strategic Highway Research Program National Research Council Washington, DC 1994):1–17.Search in Google Scholar
86. Hofko, B. Paths to successful asphalt road structures: performance-based specifications for hot mix asphalt. In: Advances in road infrastructure and mobility. Dubai: 18th International Road Federation World Meeting & Exhibition Springer International Publishing; 2022:35–45 pp.10.1007/978-3-030-79801-7_3Search in Google Scholar
87. Moreland Herrix, WHG. Effect of aggregate shape on stability of bituminous mixes. Transp Res Rec USA 1954;293–308.Search in Google Scholar
88. Perdomo, D, Button, J. Identifying and correcting rut-susceptible asphalt mixtures. Final Report. Washington, DC: Department of Transportation. Division of Transportation Planning; United States. Department of Transportation. Federal Highway Administration; 1991.Search in Google Scholar
89. Brown, ER, Crawley, A, McRae, J. Effect of aggregates on performance of bituminous concrete. USA: ASTM International; 1989.10.1520/STP24555SSearch in Google Scholar
90. Stevens, R. Sustainable use of cool pavement and reclaimed asphalt in the City of Phoenix. Springer International Publishing; 2022. Hal Kandhal PS. Design of large stone asphalt mixes to minimize Rutting. NCAT Report No. 90-1, USA; 1990 https://doi.org/10.1007/978-3-030-79801-7.Search in Google Scholar
91. Sawangsuriya, A. Field monitoring of road pavement responses and their performance in Thailand. In: Advances in road infrastructure and mobility. Dubai: 18th International Road Federation World Meeting & Exhibition, Springer International Publishing; 2022:441–9 pp.10.1007/978-3-030-79801-7_32Search in Google Scholar
92. Brown, E, Bassett, CE. Effects of maximum aggregate size on rutting potential and other properties of asphalt-aggregate mixtures. Transp Res Rec 1990;1259:107–19.Search in Google Scholar
93. Al-Qaili, AH, Al-Solieman, H. Enhancing MEPDG distress models prediction for Saudi Arabia by local calibration. Road Mater Pavement Des 2021;23:1681–93. https://doi.org/10.1080/14680629.2021.1910546.Search in Google Scholar
94. Anwar Parvez, M, Al-Abdul Wahhab, HI, Shawabkeh, RA, Hussein, IA. Asphalt modification using acid-treated waste oil fly ash. Constr Build Mater 2014;70:201–9. https://doi.org/10.1016/j.conbuildmat.2014.07.045.Search in Google Scholar
95. Chesner, WH, Collins, RJ, MacKay, MH. User guidelines for waste and by-product materials in pavement construction. Washington, D.C.: Federal Highway Administration; 1998:683 p.Search in Google Scholar
96. Sivagnanasuntharam, S, Sounthararajah, A, Ghorbani, J, Bodin, D, Kodikara, J. A state-of-the-art review of compaction control test methods and intelligent compaction technology for asphalt pavements. Road Mater Pavement Des 2021;24:1–30. https://doi.org/10.1080/14680629.2021.2015423.Search in Google Scholar
97. Wang, S, Jiang, H, Wang, Z, Wang, Y, Li, Y, Geng, X, et al.. Evaluation of heavy roller compaction on a large-thickness layer of subgrade with full-scale field experiments. J Zhejiang Univ A 2022;23:933–44. https://doi.org/10.1631/jzus.A2200201.Search in Google Scholar
98. Abdullah, GMS. Performance of enhanced problematic soils in roads pavement structure : numerical simulation and laboratory study. Sustainability 2023;15:2595. https://doi.org/10.3390/su15032595.Search in Google Scholar
99. Santos, A, Freitas, E, Faria, S, Oliveira, J, Rocha, AMAC. Degradation of friction performance indicator over time in highways using linear mixed models. In: Advances in road infrastructure and mobility. Dubai: 18th International Road Federation World Meeting & Exhibition, Springer International Publishing; 2022:474–89 pp.10.1007/978-3-030-79801-7_35Search in Google Scholar
100. Sousa, JB, Craus, J, Monismith, CL. Summary report on permanent deformation in asphalt concrete. Washington, D.C.: Strategic Highway Research Program, National Academy of Sciences; 1991:91–104 pp.Search in Google Scholar
101. Hand, AJ, Epps, AL. Impact of gradation relative to superpave restricted zone on hot-mix asphalt performance. Transp Res Rec 1987;1767:158–66. https://doi.org/10.3141/1767-20.Search in Google Scholar
102. Yang, Q, Lin, J, Wang, X, Wang, D, Xie, N, Shi, X. A review of polymer-modified asphalt binder: modification mechanisms and mechanical properties. Cleaner Mater 2024;12:100255. https://doi.org/10.1016/j.clema.2024.100255.Search in Google Scholar
103. Du, Y, Chen, J, Han, Z, Liu, W. A review on solutions for improving rutting resistance of asphalt pavement and test methods. Constr Build Mater 2018;168:893–905. https://doi.org/10.1016/j.conbuildmat.2018.02.151.Search in Google Scholar
104. Kallas, B, Puzinauskas, V, Krieger, H. Mineral fillers in asphalt paving mixtures. Highw Res Board Bull 1962;329.Search in Google Scholar
105. Anderson, DA, Goetz, WH. Mechanical behavior and reinforcement of mineral filler-asphalt mixtures. Jt Highw Res Projec 1973.Search in Google Scholar
106. Douries, WJ. Factors influencing asphalt compatibility and its. 2004.Search in Google Scholar
107. Serrano Anderson, DA, Goetz, WH. Mechanical behavior and reinforcement of mineral filler-asphalt mixtures. USA: Joint Highway Research Project, Prude University; 1973.10.5703/1288284313845Search in Google Scholar
108. Anani, BA, Balghunaim, FA. Laboratory and field study of pavement rutting in Saudi Arabia. Transp Res Rec 1990;79:79–90.Search in Google Scholar
109. Ali, Y, Irfan, M, Ahmed, S, Ahmed, S. Empirical correlation of permanent deformation tests for evaluating the rutting response of conventional asphaltic concrete mixtures. J Mater Civ Eng 2017;29:04017059. https://doi.org/10.1061/(asce)mt.1943-5533.0001888.Search in Google Scholar
110. Albayati, AH, Abdulsattar, H. Results in engineering performance evaluation of asphalt concrete mixes under varying replacement percentages of natural sand. Results Eng 2020;7:100131. https://doi.org/10.1016/j.rineng.2020.100131.Search in Google Scholar
111. Asmael, NM. Effect of mineral filler type and content on properties of asphalt concrete mixes. J Eng 2010;16:5352–62.10.31026/j.eng.2010.03.05Search in Google Scholar
112. Arabani, M, Azarhoosh, AR. The effect of recycled concrete aggregate and steel slag on the dynamic properties of asphalt mixtures. Constr Build Mater 2012;35:1–7. https://doi.org/10.1016/j.conbuildmat.2012.02.036.Search in Google Scholar
113. Seif, ESA. Geomechanical evaluation of Pliocene natural aggregates as pavement materials. Arab J Geosci 2013;7:1567–76. https://doi.org/10.1007/s12517-013-0890-9.Search in Google Scholar
114. Seif, ESA, Sonbul, AR, Abdo, B, Hakami, H. Experimental study on the utilization of dune sands as a construction material in the area between Jeddah and Mecca, Western Saudi Arabia. Bull Eng Geol Environ 2016;75:1007–22. https://doi.org/10.1007/s10064-016-0855-9.Search in Google Scholar
115. Khattab, AM, El-badawy, SM, Abbas, A, Hazmi, A, Elmwafi, M. Evaluation of Witczak E Ã predictive models for the implementation of AASHTOWare-pavement ME design in the Kingdom of Saudi Arabia. Constr Build Mater 2014;64:360–9. https://doi.org/10.1016/j.conbuildmat.2014.04.066.Search in Google Scholar
116. Ziauddin, AK, Hamad, IA-AW, Ibrahim A, Rezqallah R. Comparative study of asphalt concrete laboratory compaction methods to simulate field compaction. Constr Build Mater 1998;12:373–84. https://doi.org/10.1016/s0950-0618(98)00015-4.Search in Google Scholar
117. Abttan, AA, Zeiada, W, Merabtene, T, Gamal, A, Mirou, S. Implications of future temperature changes on asphalt binder selection and simulated pavement performance in Sharjah. Innov Infrastruct Solut 2024;9:88. https://doi.org/10.1007/s41062-024-01408-6.Search in Google Scholar
118. Asi, IM, Alis, MF. Performance-based Arab asphalt characterization of 33. 1998.10.1016/S0360-1323(97)00052-8Search in Google Scholar
119. Ramadhan, RH, AI-Abdul Wahhab, HI, Asi, IM, Ai-Dubabe, IA. Evaluation of Arabian asphalt binder for low-temperature cracking. J Mater Civ Eng 1998;10:26–33. https://doi.org/10.1061/(asce)0899-1561(1998)10:.Search in Google Scholar
120. Mohammed, G, Hussain, A, Ahmed, M, Abdulaziz, G, Nan, Z, Al-hammadi, M. Climate zones of the asphalt binder performance for the highway pavement design. Civ Eng J 2020;6:2220–30. https://doi.org/10.28991/cej-2020-03091613.Search in Google Scholar
121. Ibrahim, H, Wahhab, AA, Hasnain, J. Laboratory study of asphalt concrete durability in Jeddah. Build Environ 1998;33:219–30. https://doi.org/10.1016/s0360-1323(97)00031-0.Search in Google Scholar
122. Zaumanis, M, Mallick, RB, Poulikakos, L, Frank, R. Influence of six rejuvenators on the performance properties of Reclaimed Asphalt Pavement (RAP) binder and 100% recycled asphalt mixtures. Constr Build Mater 2013;71:538–50. https://doi.org/10.1016/j.conbuildmat.2014.08.073.Search in Google Scholar
123. Alharbi, F, Almoshaigeh, A, Almoshaogeh, M, Elragi, A, Elkholy, S. Effect of geo-grid depth in roads cross-section on reducing pavement rutting. Eng 2022;3:1–8. https://doi.org/10.3390/eng3010001.Search in Google Scholar
124. Almatar, KM. Perception of drivers toward road safety and factors that cause road accidents in Riyadh city of Saudi Arabia. Front Built Environ 2024;10:1–11. https://doi.org/10.3389/fbuil.2024.1367553.Search in Google Scholar
125. Rasul, JM, Michael, PN, Burrow, GSG. Consideration of the deterioration of stabilised subgrade soils in analytical pavement design. 2020. https://doi.org/10.1016/j.trgeo.2016.08.002.Search in Google Scholar
126. Radhakrishnan, V, Ramya Sri, M, Sudhakar Reddy, K. Evaluation of asphalt binder rutting parameters. Constr Build Mater 2018;173:298–307. https://doi.org/10.1016/j.conbuildmat.2018.04.058.Search in Google Scholar
127. Zou, G, Xu, J, Wu, C. Evaluation of factors that affect rutting resistance of asphalt mixes by orthogonal experiment design. Int J Pavement Res Technol 2017;10:282–8. https://doi.org/10.1016/j.ijprt.2017.03.008.Search in Google Scholar
128. Salim, R, Gundla, A, Zalghout, A, Underwood, BS, Kaloush, KE. Relationship between asphalt binder parameters and asphalt mixture rutting. Transp Res Rec 2019;2673:431–46. https://doi.org/10.1177/0361198119842129.Search in Google Scholar
129. Lira, B, Ekblad, J, Lundström, R. Evaluation of asphalt rutting based on mixture aggregate gradation. Road Mater Pavement Des 2021;22:1160–77. https://doi.org/10.1080/14680629.2019.1683061.Search in Google Scholar
130. Norouzi, A, Kim, D, Kim, YR. Numerical evaluation of pavement design parameters for the fatigue cracking and rutting performance of asphalt pavements numerical evaluation of pavement design parameters for the fatigue cracking and rutting performance of asphalt pavements. Mater Struct 2015. https://doi.org/10.1617/s11527-015-0744-x.Search in Google Scholar
131. Li, Q, Xiao, DX, Wang, KCP, Hall, KD, Qiu, Y. Mechanistic-empirical pavement design guide (MEPDG): a bird’s-eye view. J Mod Transp 2011;19:114–33. https://doi.org/10.1007/bf03325749.Search in Google Scholar
132. Abdullah, GMS. Pavement thickness design charts derived from Rut depth models developed for foamed and emulsified sulfur asphalt soil mixes. Geotech Geol Eng 2020;38:3053–65. https://doi.org/10.1007/s10706-020-01206-8.Search in Google Scholar
133. Al-Mehthel, M, Wahhab, HIA, Al-idi, SH, Baig, MG. Sulfur extended asphalt as a major outlet for sulfur that outperformed other asphalt mixes in the Gulf. Sulphur World Symp 2010:1–16.Search in Google Scholar
134. Khan, IM, Kabir, S, Alhussain, MA, Almansoor, FF. Asphalt design using recycled plastic and crumb-rubber waste for sustainable pavement construction. Procedia Eng 2016;145:1557–64. https://doi.org/10.1016/j.proeng.2016.04.196.Search in Google Scholar
135. Sirin, O, Paul, DK, Kassem, E, Ohiduzzaman, M. Effect of ageing on asphalt binders in the State of Qatar: a case study. Road Mater Pavement Des 2017;18:165–84. https://doi.org/10.1080/14680629.2017.1389094.Search in Google Scholar
136. Andrews, K, Dernayka, S, Amin Mir, M, Ali Khasawneh, M. Review of the utilization of plastic waste in asphalt pavements in hot climate conditions – KSA as a case study. Mater Today Proc 2023. https://doi.org/10.1016/j.matpr.2023.05.463.Search in Google Scholar
137. Debbarma, S, Ransinchung, GD, Singh, S, Sahdeo, SK. Utilization of industrial and agricultural wastes for productions of sustainable roller compacted concrete pavement mixes containing reclaimed asphalt pavement aggregates. Resour Conserv Recycl 2020;152:104504. https://doi.org/10.1016/j.resconrec.2019.104504.Search in Google Scholar
138. Li, C, Li, L. Criteria for controlling rutting of asphalt concrete materials in sloped pavement. Constr Build Mater 2012;35:330–9. https://doi.org/10.1016/j.conbuildmat.2012.04.003.Search in Google Scholar
139. Miguel Baptista, A, Picado-Santos, LG, Capitão, SD. Design of hot-mix recycled asphalt concrete produced in plant without preheating the reclaimed material. Int J Pavement Eng 2013;14:95–102. https://doi.org/10.1080/10298436.2011.587009.Search in Google Scholar
140. Abdelaziz, A, Epps Martin, A, Masad, E, Arámbula Mercado, E, Kaseer, F. Effects of ageing and recycling agents on the multiscale properties of binders with high RAP contents. Int J Pavement Eng 2022;23:1248–70. https://doi.org/10.1080/10298436.2020.1797736.Search in Google Scholar
141. Asi, IM. Stabilization of sebkha soil using foamed asphalt. J Mater Civ Eng 2001;13:325–31. https://doi.org/10.1061/(asce)0899-1561(2001)13:5(325).10.1061/(ASCE)0899-1561(2001)13:5(325)Search in Google Scholar
142. Huang, B, Shu, X, Li, G. Laboratory investigation of Portland cement concrete containing recycled asphalt pavements. Cement Concr Res 2005;35:2008–13. https://doi.org/10.1016/j.cemconres.2005.05.002.Search in Google Scholar
143. Hariprasad, C, Umashankar, B, Garala, TKStalin, VK, Muttharam, M, editors. Lightweight deflectometer for compaction quality control BT – geotechnical characterisation and geoenvironmental engineering. Singapore: Springer Singapore; 2019:35–42 pp.10.1007/978-981-13-0899-4_5Search in Google Scholar
144. Wang, Q, Xu, Z, Wu, J, Chen, F, Zhou, Y, Zhang, H. Research on the pavement performance of high-ash composite modified rock asphalt mixture. STCE 2022;12460:1–6. https://doi.org/10.1117/12.2658690.Search in Google Scholar
145. Ding, L, Wang, X, Zhang, M, Meng, J, Hu, T. Construction quality control study of double-layer continuous paving for large-thickness cement-stabilized base. Adv Civ Eng 2020;8845642:1–13. https://doi.org/10.1155/2020/8845642.Search in Google Scholar
146. Beainy, F, Singh, D, Commuri, S, Zaman, M. Laboratory and field study on compaction quality of an asphalt pavement. Int J Pavement Res Technol 2014;7:317–23. https://doi.org/10.6135/ijprt.org.tw/2014.7(5).Search in Google Scholar
147. Umashankar, B, Hariprasad, C, Kumar, GT. Compaction quality control of pavement layers using LWD. J Mater Civil Eng 2012;6758:1–9. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001379.Search in Google Scholar
148. Savan, CM, Ng, KW, Ksaibati, K. Benefit-cost analysis and application of intelligent compaction for transportation. Transp Geotech 2016;9:57–68. https://doi.org/10.1016/j.trgeo.2016.07.001.Search in Google Scholar
149. Schmitt, RL. Layer thickness, compaction temperatures, and achieving density. J Assoc Asph Paving Technol 2012;81:9.Search in Google Scholar
150. Leyland, RLollino, G, Arattano, M, Giardino, M, Oliveira, R, Peppoloni, S, editors. A case study of intelligent compaction used in road upgrades BT – engineering geology for society and territory – Volume 7. Cham: Springer International Publishing; 2014:201–6 pp.10.1007/978-3-319-09303-1_39Search in Google Scholar
151. Hamdar, YS, Bakchan, A, Chehab, GR, Al-Qadi, I, Little, D. Benchmarking pavement practices in data-scarce regions – case of Saudi Arabia. Int J Pavement Eng 2021;22:294–306. https://doi.org/10.1080/10298436.2019.1606914.Search in Google Scholar
152. Fuhaid Al, AF, Arifuzzaman, M, Gul, MA. Application of mechanistic empirical pavement design guide software in Saudi Arabia. Appl Sci 2022;12:8165. https://doi.org/10.3390/app12168165.Search in Google Scholar
153. Chen, B, Yu, X, Dong, F, Zheng, C, Ding, G, Wu, W. Compaction quality evaluation of asphalt pavement based on intelligent compaction technology. J Construct Eng Manag 2021;147:04021099. https://doi.org/10.1061/(asce)co.1943-7862.0002115.Search in Google Scholar
154. Chabutkin, EK, Popov, YG, Tyuremnov, IS, Tarasova, NE. Ways to improve quality control devices when compacting asphalt concrete pavements. AIP Conf Proc 2022;2486:060007. https://doi.org/10.1063/5.0129898.Search in Google Scholar
155. Wang, W, Wang, L. Review on design, characterization, and prediction of performance for asphalt materials and asphalt pavement using multi-scale numerical simulation. Materials 2024;17:778. https://doi.org/10.3390/ma17040778.Search in Google Scholar PubMed PubMed Central
156. El-badawy, S, El-hakim, RA. Recent developments in pavement design, modeling and performance. Egypt: Proceedings of the 2nd GeoMEast International Congress and Exhibition on Sustainable Civil Infrastructures; 2018.10.1007/978-3-030-01908-2Search in Google Scholar
157. Agardh, S. Rut depth prediction on flexible pavements – calibration and validation of incremental-recursive models. Lund: Lund University; 2005, 227.Search in Google Scholar
158. Battiato, G, Verga, C, Ronca, G. Viscoelastic deformations in a two-layered paving system predicted from laboratory creep results. Transp Res Rec 1976;34–38.Search in Google Scholar
159. Kumar, A, Prasad, J. Rutting prediction models for flexible pavement structures: a review of historical and recent developments. J Traffic Transport Eng 2021;8:315–8. https://doi.org/10.1016/j.jtte.2021.04.003.Search in Google Scholar
160. Monismith, CL. Rutting prediction in asphalt concrete pavement. Transp Res Rec 1976;2–8.Search in Google Scholar
161. Abed, AH. Required criteria for implemention of the superpave system in local pavement designc [Ph.D. thesis]. Baghdad: University of Baghdad 2010.Search in Google Scholar
162. Abdel-Wahed, TA, Rashwan, NK. Application of cement dust and OPC as mineral filler in the binder hot mix asphalt. In: 15th annu. Int. Conf. Asph. Pavement eng. Infrastruct.; 2016, 15.Search in Google Scholar
163. Dawood, D, Pierce, L, Davis, A, Gisi, R, Lockett, L, Farnbach, B, et al.. Mechanistic – empirical pavement design guide a manual of practice. Washington, DC.: American Association of State Highway and Transportation Officials; 2008:218 p.Search in Google Scholar
164. Biligiri, KP, Kaloush, KE, Mamlouk, MS, Witczak, MW. Rational modeling of tertiary flow for asphalt mixtures. Transp Res Rec 2001;2001:63–72. https://doi.org/10.3141/2001-08.Search in Google Scholar
165. Sommer, P, Uzan, J, Lytton, RL. Structural design of flexible pavements: a simple predictive system. TRB 1982;1:56–63.Search in Google Scholar
166. Roja, KL, Yamani, H, Sadeq, M, Masad, E. Case studies in construction materials analysis of performance of asphalt pavements in Qatar using mechanistic-empirical approaches. Case Stud Constr Mater 2023;18:e01708. https://doi.org/10.1016/j.cscm.2022.e01708.Search in Google Scholar
167. Yang, H, Yuang. Pavement analysis and design. Upper Saddle River, NJ: Pearson/Prentice Hall; 2004, 2:1–21 pp.Search in Google Scholar
168. Milad, A, Adwan, I, Majeed, SA, Memon, ZA, Bilema, M, Omar, HALI, et al.. Development of a hybrid machine learning model for asphalt pavement temperature prediction. IEEE Access 2021;9:158041–56. https://doi.org/10.1109/ACCESS.2021.3129979.Search in Google Scholar
169. Marcelino, P, Antunes, MDL, Fortunato, E, Marcelino, P, Antunes, MDL, Fortunato, E, et al.. Machine learning approach for pavement performance prediction. Int J Pavement Eng 2019;22:1–14. https://doi.org/10.1080/10298436.2019.1609673.Search in Google Scholar
170. Hudson, RH, Ronald, W, Falls, LC. Pavement asset management. Hoboken, NJ: Wiley Sons Inc; 2015.Search in Google Scholar
171. Auwal, AM, Salim, IM, Wassef, O, Mohammed, A, Sadi, IH. Sustainable traffic management for smart cities using internet-of-things-oriented intelligent transportation systems (ITS): challenges and recommendations. Sustainability 2023;15. https://doi.org/10.3390/su15139859.Search in Google Scholar
172. Amin, S, Amador, L. Backpropagation Neural Network to estimate pavement performance: dealing with measurement errors. Road Mater Pavement Des 2016;18:1218–38. https://doi.org/10.1080/14680629.2016.1202129.Search in Google Scholar
173. Al-khateeb, GG, Khedaywi, TS, Obaidat, TIA, Najib, AM. Laboratory study for comparing rutting performance of limestone and basalt superpave asphalt mixtures. J Mater Civ Eng 2013;25:21–9. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000519.Search in Google Scholar
174. Cheng, C, Ye, C, Yang, H, Wang, L. Applied sciences predicting rutting development of pavement with flexible overlay using artificial neural network. Appl Sci 2023;13. https://doi.org/10.3390/app13127064.Search in Google Scholar
175. Khalifah, R, Souliman, MI, Bin, M, Bajusair, M. Development of prediction model for rutting depth using artificial neural network. Civil Eng 2023;4:174–84. https://doi.org/10.3390/civileng4010011.Search in Google Scholar
176. Makendran, C. Statistical modelling of rutting for low-volume roads in India. Građevinar 2023;75:379–87. https://doi.org/10.14256/JCE.3486.2022.Search in Google Scholar
177. Li, Z, Tao, M, Cao, J, Xinli Shi, T, Moa, WH. An augmented model of rutting data based on radial basis. Symmetry 2023;15:1–15. https://doi.org/10.3390/sym15010033.Search in Google Scholar
178. Shi, S, Tong, J, Chen, F, Hu, J, Ma, T. Towards an improved prediction of asphalt pavement rutting through thermal-mechanical coupled constitutive modelling. Int J Pavement Eng 2023;24:2192495. https://doi.org/10.1080/10298436.2023.2192495.Search in Google Scholar
179. Mirzapour Mounes, S, Karim, MR, Khodaii, A, Almasi, MH. Improving rutting resistance of pavement structures using geosynthetics: an overview. Sci World J 2014;2014:1–6. https://doi.org/10.1155/2014/764218.Search in Google Scholar PubMed PubMed Central
180. Rushing, JF, Little, DN, Garg, N. Selecting a rutting performance test for airport asphalt mixture design. Road Mater Pavement Des 2014;15:172–94. https://doi.org/10.1080/14680629.2014.926626.Search in Google Scholar
181. Yin, H, Zhang, Y, Sun, Y, Xu, W, Yu, D, Xie, H, et al.. Performance of hot mix epoxy asphalt binder and its concrete. Mater Struct 2014;48:3825–35. https://doi.org/10.1617/s11527-014-0442-0.Search in Google Scholar
182. Mirabdolazimi, SM, Shafabakhsh, G. Rutting depth prediction of hot mix asphalts modified with Forta fiber using artificial neural networks and genetic programming technique. Constr Build Mater 2017;148:666–74. https://doi.org/10.1016/j.conbuildmat.2017.05.088.Search in Google Scholar
183. Hamid, A, Baaj, H, El-Hakim, M. Rutting behaviour of geopolymer and styrene butadiene styrene-modified asphalt binder. Polymers 2022;14:1–20. https://doi.org/10.3390/polym14142780.Search in Google Scholar PubMed PubMed Central
184. Geng, H, Clopotel, CS, Bahia, HU. Effects of high modulus asphalt binders on performance of typical asphalt pavement structures. Constr Build Mater 2013;44:207–13. https://doi.org/10.1016/j.conbuildmat.2013.03.035.Search in Google Scholar
185. Al-tameemi, AF, Wang, Y, Albayati, A. Experimental study of the performance related properties of asphalt concrete modified with hydrated lime. 2015:1–11. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001474.Search in Google Scholar
186. Al-tameemi, AF, Wang, Y, Albayati, A. Influence of hydrated lime on the properties and permanent deformation of the asphalt concrete layers in pavement. 2015;4:1–19. https://doi.org/10.1515/rjti-2015-0027.Search in Google Scholar
187. Becker, Y, Méndez, MP. Polymer modified asphalt. Vision Tecnol 2001;9:39–50.Search in Google Scholar
188. Al-adham, K, Wahhab, HA. Effect of polymer type on improving rheological parameters related to rutting resistance of asphalt binders. In: Bituminous mixtures & pavements VI, Greece; 2015:89–95.10.1201/b18538-15Search in Google Scholar
189. Alharbi, F, Alshubrumi, F, Almoshaogeh, M, Haider, H, Elragi, A, Elkholy, S. Sustainability evaluation of cold In-place recycling and hot mix asphalt pavements: a case of Qassim, Saudi Arabia. Coatings 2022;12:50. https://doi.org/10.3390/coatings12010050.Search in Google Scholar
190. Roy, LB. Effect of geogrid reinforcement on shear strength characteristics of a rubber-sand mixture under undrained triaxial test. 2023;17:177–84. https://doi.org/10.14525/jjce.v17i2.01.Search in Google Scholar
191. Attahiru, YB, Mohamed, A, Ahmed, E, Burga, AA, Ibrahim, A, Nabade, AM. Effect of waste cooking oil on warm mix asphalt block pavement – a comprehensive review. Phys Chem Earth 2023;129:103310. https://doi.org/10.1016/j.pce.2022.103310.Search in Google Scholar
192. Andres, C, Hanandeh, E. Systematic literature review, meta- analysis and artificial neural network modelling of plastic waste addition on bitumen 0–40; 2020. https://doi.org/10.1016/j.jclepro.2020.124369.Search in Google Scholar
193. Moghaddam, TB, Soltani, M, Karim, MR. Experimental characterization of rutting performance of polyethylene terephthalate modified asphalt mixtures under static and dynamic loads. 2014;65:487–94. https://doi.org/10.1016/j.conbuildmat.2014.05.006.Search in Google Scholar
194. Greene, J, Nazef, A, Choubane, B, Horhota, D. Long-term evaluation of geosynthetic reinforcement of flexible pavements constructed over thick organic soil deposits. Transp Res Rec 2014;2462:89–97. https://doi.org/10.3141/2462-11.Search in Google Scholar
195. Chow, LC, Mishra, D, Tutumluer, E. Framework for development of an improved unbound aggregate base rutting model for mechanistic–empirical pavement design. Transp Res Rec TRB 2014;2401:11–21. https://doi.org/10.3141/2401-02.Search in Google Scholar
196. Jaya, RP, Hassan, NA, Mahmud, MZH, Aziz, MMA, Hamzah, MO, Wan, CNC. Effect of aggregate shape on the properties of asphaltic concrete AC14. J. Teknol. 2014;71:69–73. https://doi.org/10.11113/jt.v71.3762.Search in Google Scholar
197. Al-Nawasir, R, Al-Humeidawi, BH, Al-Humeidawi, BH. Qualitative evaluation for asphalt binder modified with SBS polymer. Tikrit J Eng Sci 2023;30:88–101. https://doi.org/10.25130/tjes.30.4.10.Search in Google Scholar
198. Lesueur, D, Denayer, C, Ritter, H-J, Kunesch, C, Gasiorowski, S, d’Alto, A. The use of hydrated lime in the formulation of asphalt mixtures: European case studies. In: 6th Eurasphalt & Eurobitume Congress | 1-3 June 2016; 2016. https://doi.org/10.25130/tjes.30.4.10.Search in Google Scholar
199. Sarsam, SI, Alwan, AH. Impact of moisture damage on rutting resistance, shear and tensile properties of asphalt pavement. Int J Sci Res Knowl 2014;2:453–62. https://doi.org/10.12983/ijsrk-2014-p0453-0462.Search in Google Scholar
200. Anwar Parvez, M, Al-Mehthel, M, Al-Abdul Wahhab, HI, Hussein, IA. Utilization of sulfur and crumb rubber in asphalt modification. J Appl Polym Sci 2014;131:1–11. https://doi.org/10.1002/app.40046.Search in Google Scholar
201. Dalhat, MA, Al-Abdul Wahhab, HI. Cement-less and asphalt-less concrete bounded by recycled plastic. Constr Build Mater 2016;119:206–14. https://doi.org/10.1016/j.conbuildmat.2016.05.010.Search in Google Scholar
202. Al-taher, MG, Hassanin, HD, Ibrahim, MF, Sawan, AM. Comparative study of performance of modified asphalt mixtures using different traditional and nano additives. Int J Sci Eng Res 2018;9:1243–50.Search in Google Scholar
203. Mamun, AA, Al-Abdul Wahhab, HI. Evaluation of waste engine oil-rejuvenated asphalt concrete mixtures with high RAP content. Adv Mater Sci Eng 2018;2018:7386256. https://doi.org/10.1155/2018/7386256.Search in Google Scholar
204. Al-Taher, MG, Hassanin, HD, Ibrahim, MF, Sawan, AM. Investigation of the effect of adding silica fume on asphalt concrete properties. Int J Eng Res 2018;7:48. https://doi.org/10.5958/2319-6890.2018.00095.8.Search in Google Scholar
205. Dalhat, MA, Osman, SA, Alhuraish, AAA, Almarshad, FK, Qarwan, SA, Adesina, AY. Chicken feather fiber modified hot mix asphalt concrete: rutting performance, durability, mechanical and volumetric properties. Constr Build Mater 2020;239:117849. https://doi.org/10.1016/j.conbuildmat.2019.117849.Search in Google Scholar
206. Eltariki, IM, Almhroog, AA. Evaluating the use of SS and CW in asphalt concrete. Int J Eng Inf Technol 2020;6:95–9. https://doi.org/10.13140/RG.2.2.14201.29287.Search in Google Scholar
207. Clay, B, Ibraheem, M, Baker, B, Abendeh, RM, Khasawneh, MA. Freeze and thaw effect on asphalt concrete mixtures modified with natural bentonite clay. Coatings 2022;12:1–14.10.3390/coatings12111664Search in Google Scholar
208. Licea, MR, Cervantes, I. An approach to mitigate the lateral skid for wheeled vehicles. IEEE Lat Am Trans 2018;16:1306–13. https://doi.org/10.1109/TLA.2018.8407101.Search in Google Scholar
209. Khorshidi, M, Goli, A, Oreškovi, M, Khayambashi, K, Ameri, M. Performance evaluation of asphalt mixtures containing different proportions of alternative materials. Sustainability 2023;15:13314. https://doi.org/10.3390/su151813314.Search in Google Scholar
210. Leavitt, A, Martin, AE, Arámbula-Mercado, E. Mitigation strategy selection for asphalt mixtures with high reclaimed asphalt pavement content. Transp Res Rec 2023;2677:602–14. https://doi.org/10.1177/03611981231166392.Search in Google Scholar
211. Kim, K, Ho, T, Le, M. Feasibility of pellet material incorporating anti-stripping emulsifier and slaked lime for pothole restoration. Buildings 2023;13:1305. https://doi.org/10.3390/buildings13051305.Search in Google Scholar
212. Marques, B, Tadeu, A, Almeida, J, Dias, S, Pedro, FMonteiro, J, João Silva, A, Mortal, A, Aníbal, J, Moreira da Silva, M, Oliveira, M, et al., editors. Mitigation of vibrations using composite materials produced from rice husk and recycled rubber BT – INCREaSE 2019. Cham: Springer International Publishing; 2020:981–8 pp.10.1007/978-3-030-30938-1_76Search in Google Scholar
213. Aljbouri, HJ, Albayati, AH. Effect of nanomaterials on the durability of hot mix asphalt. Transport Eng 2023;11:100165. https://doi.org/10.1016/j.treng.2023.100165.Search in Google Scholar
214. Elipse, C, Kim, JW, Ohm, BS. Performance evaluation on the application of MAST and RCC on a Cambodian rural road: a case study. Buildings 2023;13:2993. https://doi.org/10.3390/buildings13122993.Search in Google Scholar
215. Algin, Z, Gerginci, S. Freeze-thaw resistance and water permeability properties of roller compacted concrete produced with macro synthetic fibre. Constr Build Mater 2020;234:117382. https://doi.org/10.1016/j.conbuildmat.2019.117382.Search in Google Scholar
216. Wang, X, Wu, R, Zhang, L. Development and performance evaluation of epoxy asphalt concrete modified with glass fibre. Road Mater Pavement Des 2019;20:715–26. https://doi.org/10.1080/14680629.2017.1413006.Search in Google Scholar
217. Abiodun Salami, B, Bahraq, AA, Haq, MMU, Ojelade, OA, Taiwo, R, Wahab, S, et al.. Polymer-enhanced concrete: a comprehensive review of innovations and pathways for resilient and sustainable materials. Next Mater 2024;4:100225. https://doi.org/10.1016/j.nxmate.2024.100225.Search in Google Scholar
218. Li, W, Wang, D, Chen, B, Hua, K, Huang, Z, Xiong, C, et al.. Preparation of artificial pavement coarse aggregate using 3D printing technology. Materials 2022;15:1575. https://doi.org/10.3390/ma15041575.Search in Google Scholar PubMed PubMed Central
219. Jenkins, KJ. Durability of bitumen-stabilized materials. J Test Eval 2023;51:1966–86. https://doi.org/10.1520/JTE20220267.Search in Google Scholar
220. Naz, F, Kui, DH, Anwar, Zakir. Experimental study on rutting performance by using polypropylene fiber. Int J Sci Technol Eng 2022;10:753–66. https://doi.org/10.22214/ijraset.2022.41250.Search in Google Scholar
221. Kvitko, A, Shendrik, V, Mukharryamov, I, Kvitko, A, Shendrik, V, Mukharryamov, I. Traffic safety improvement through implementing innovative traffic safety improvement implementing innovative technologies and materials in through construction of roads and bridges technologies and materials in construction of roads and bridges. Transp Res Procedia 2018;36:404–10. https://doi.org/10.1016/j.trpro.2018.12.115.Search in Google Scholar
222. Alsolieman, HA, Babalghaith, AM, Memon, ZA, Al-Suhaibani, AS, Milad, A. Evaluation and comparison of mechanical properties of polymer-modified asphalt mixtures. Polymers 2021;13:2282. https://doi.org/10.3390/polym13142282.Search in Google Scholar PubMed PubMed Central
223. Basheer Ahmed, MI, Zaghdoud, R, Ahmed, MS, Sendi, R, Alsharif, S, Alabdulkarim, J, et al.. A real-time computer vision based approach to detection and classification of traffic incidents. Big Data Cogn Comput 2023;7:22. https://doi.org/10.3390/bdcc7010022.Search in Google Scholar
224. Laurinavičius, A, Oginskas, R. Experimental research on the development of rutting in asphalt concrete pavements reinforced with geosynthetic materials. J Civ Eng Manag 2006;12:311–17. https://doi.org/10.1080/13923730.2006.9636408.Search in Google Scholar
225. Deng, Y, Shi, X. Modeling the rutting performance of asphalt pavements: a review. J Infrastruct Preserv Resilience 2023;4:17. https://doi.org/10.1186/s43065-023-00082-9.Search in Google Scholar
226. Al Qadi, AN, Alhasanat, MB, Haddad, M. Effect of crumb rubber as coarse and fine aggregates on the properties of asphalt concrete. Am J Eng Appl Sci 2016;9:558–64. https://doi.org/10.3844/ajeassp.2016.558.564.Search in Google Scholar
227. Khedaywi, TS, Haddad, MA, Al Qadi, ANS, Al-Rababa’ah, OA. Investigating the effect of addition of olive husk ash on asphalt binder properties. Ann Chimie Sci Matériaux 2021;45:239–43. https://doi.org/10.18280/acsm.450307.Search in Google Scholar
228. Pomoni, M, Plati, C. Skid resistance performance of asphalt mixtures containing recycled pavement materials under simulated weather conditions. Recycling 2022;7:47. https://doi.org/10.3390/recycling7040047.Search in Google Scholar
229. Abdulaziz, B. A quality of pavement construction in Saudi Arabia. Pract Period Struct Des Construct 2001;6:129–36. https://doi.org/10.1061/(ASCE)1084-0680(2001)6:3(129).10.1061/(ASCE)1084-0680(2001)6:3(129)Search in Google Scholar
230. Tan, Y, Liang, Z, Xu, H, Xing, C. Research on rutting deformation monitoring method based on intelligent aggregate. IEEE Trans Intell Transp Syst 2022;23:22116–26. https://doi.org/10.1109/TITS.2022.3175060.Search in Google Scholar
231. Shatnawi, N, Taleb Obaidat, M, Al-Sharideah, A. Modeling road pavement rutting using artificial neural network and conventional measurements. Transp Res Rec 2022;2677:973–84. https://doi.org/10.1177/03611981221110224.Search in Google Scholar
232. Mizwar, K, Madzlan, N, Hartadi, SM, Z, HN, Praveena, T, Yinghong, Q. Rutting prevention of bituminous mastic using microencapsulation phase change material. J Mater Civ Eng 2021;33:4021336. https://doi.org/10.1061/(ASCE)MT.1943-5533.0003965.Search in Google Scholar
233. Zhang, Y, Yuan, B, Chou, Y. Analyzing driving safety using vehicle-water-filled rutting dynamics model and simulation. Adv Mater Sci Eng 2022;2022:1–16. https://doi.org/10.1155/2022/9372336.Search in Google Scholar
234. Huang, W, Liang, S, Wei, Y. Surface deflection-based reliability analysis of asphalt pavement design. Sci China Technol Sci 2020;63:1824–36. https://doi.org/10.1007/s11431-019-1480-8.Search in Google Scholar
235. Jean-Pascal, B, Junyan, Y, Papa Masseck, T. Surface deflection analysis of flexible pavement with respect to frost penetration. J Cold Reg Eng 2019;33:04019013. https://doi.org/10.1061/(ASCE)CR.1943-5495.0000197.Search in Google Scholar
236. Newcomb, D. Perpetual pavements – a synthesis. Lanham, MD, USA: Asphalt Pavement Alliance; 2002.Search in Google Scholar
237. Lalague, A, Lebens, MA, Hoff, I. Accuracy of ground-penetrating radar in pavement thickness evaluation: impact of interpretation errors. In: Materials and infrastructures 1. Hoboken, NJ: Wiley & Sons, Inc; 2016.10.1002/9781119318583.ch17Search in Google Scholar
© 2026 the author(s), published by De Gruyter, Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.
Articles in the same Issue
- Research Articles
- A green and sustainable biocomposite materials: environmentally robust, high performance, low-cost materials for helicopter lighter structures
- Microstructural and UCS behavior of clay soils stabilized with hybrid nano-enhanced additives
- Optimization of microstructure and mechanical properties of microwave-sintered V/Ta/Re-doped tungsten heavy alloys
- Experimental and numerical study on the axial compression behavior of circular concrete columns confined by BFRP spirals and ties
- Effect of A-site calcium substitution on the energy storage and dielectric properties of ferroelectric barium titanate system
- Comparative analysis of aggregate gradation variation in porous asphalt mixtures under different compaction methods1
- Thermal and mechanical properties of bricks with integrated phase change and thermal insulation materials
- Nonlinear molecular weight dependency in polystyrene and its nanocomposites: deciphering anomalous gas permeation selectivity in water vapor-oxygen-hydrogen barrier systems
- ZnO nanophotocatalytic solution with antimicrobial potential toward drug-resistant microorganisms and effective decomposition of natural organic matter under UV light
- Predicting fracture energy and durability parameters of concrete through hybrid machine learning models
- α-hemihydrate gypsum crystal concerning the anionic surfactants with vary chain structure: syntheses, morphology controlling, formation mechanisms
- Advanced machine learning-driven prediction in construction materials: comparative analysis and software implementation for fiber-reinforced graphene nano-engineered concrete
- Innovative development of self-healing high-strength concrete using a polymeric air-entraining agent and Bacillus sphaericus: durability performance in aggressive saline environments
- Influence of welding speed on the microstructure and mechanical properties of CMT+P WAAM-based 205C aluminum alloy
- EcoMarble: macro-performance and carbon footprint optimization of concrete using cement-substituted Al-Kharj marble dust
- Predicting properties of lightweight strain-hardening ultra-high-performance concrete using smart hybrid AI-based framework
- Microstructural evolution and dry sliding wear behavior of composite shear flow casting M50 steel under different tempering conditions
- Long-term durability and microstructure of advanced high-performance concrete with cement kiln dust, boiler slag and PP fibers: flexural response and sustainability assessment
- Development of lightweight roof tiles using spent mushroom material: enhancing thermal insulation and sustainability
- Tailoring rheology and mechanical properties of 3D printed mortars with nanoclays and superplasticizer
- Fabrication of lightweight and thermal insulation roof tiles using industrial wastewater sludge
- Effect of axial compression ratio and beam end reinforcement ratio on the failure mode of RC frames
- Fatigue-based performance study of arch rib joints in CFST truss arch bridges
- Review Articles
- Granite powder in concrete: a review on durability and microstructural properties
- Properties and applications of warm mix asphalt in the road construction industry: a comprehensive review and insights toward facilitating large-scale adoption
- Artificial Intelligence in the synthesis and application of advanced dental biomaterials: a narrative review of probabilities and challenges
- Recycled tire rubber as a fine aggregate replacement in sustainable concrete: a comprehensive review
- Performance evaluation of blended cement mortar with supplementary cementitious materials: from pozzolans to industrial wastes
- A review on rutting in asphalt concrete in Saudi Arabia: mitigation strategies, innovations, and future directions
- 10.1515/rams-2025-0227
- Material properties, rheology, printability, and mechanical performance of waste glass powder in 3D concrete printing: a comprehensive review
- 10.1515/rams-2025-0228
- Rapid Communication
- Recent advances in resistive strain sensors: from materials and fabrication to applications in plant wearables
- Special Issue on AI-Driven Advances for Nano-Enhanced Sustainable Construction Materials - Part II
- Sustainable approach to control autogenous shrinkage in low water–cement ratio concretes
- Use of explainable symbolic regression approaches for predicting nanomaterial-enhanced concrete performance
Articles in the same Issue
- Research Articles
- A green and sustainable biocomposite materials: environmentally robust, high performance, low-cost materials for helicopter lighter structures
- Microstructural and UCS behavior of clay soils stabilized with hybrid nano-enhanced additives
- Optimization of microstructure and mechanical properties of microwave-sintered V/Ta/Re-doped tungsten heavy alloys
- Experimental and numerical study on the axial compression behavior of circular concrete columns confined by BFRP spirals and ties
- Effect of A-site calcium substitution on the energy storage and dielectric properties of ferroelectric barium titanate system
- Comparative analysis of aggregate gradation variation in porous asphalt mixtures under different compaction methods1
- Thermal and mechanical properties of bricks with integrated phase change and thermal insulation materials
- Nonlinear molecular weight dependency in polystyrene and its nanocomposites: deciphering anomalous gas permeation selectivity in water vapor-oxygen-hydrogen barrier systems
- ZnO nanophotocatalytic solution with antimicrobial potential toward drug-resistant microorganisms and effective decomposition of natural organic matter under UV light
- Predicting fracture energy and durability parameters of concrete through hybrid machine learning models
- α-hemihydrate gypsum crystal concerning the anionic surfactants with vary chain structure: syntheses, morphology controlling, formation mechanisms
- Advanced machine learning-driven prediction in construction materials: comparative analysis and software implementation for fiber-reinforced graphene nano-engineered concrete
- Innovative development of self-healing high-strength concrete using a polymeric air-entraining agent and Bacillus sphaericus: durability performance in aggressive saline environments
- Influence of welding speed on the microstructure and mechanical properties of CMT+P WAAM-based 205C aluminum alloy
- EcoMarble: macro-performance and carbon footprint optimization of concrete using cement-substituted Al-Kharj marble dust
- Predicting properties of lightweight strain-hardening ultra-high-performance concrete using smart hybrid AI-based framework
- Microstructural evolution and dry sliding wear behavior of composite shear flow casting M50 steel under different tempering conditions
- Long-term durability and microstructure of advanced high-performance concrete with cement kiln dust, boiler slag and PP fibers: flexural response and sustainability assessment
- Development of lightweight roof tiles using spent mushroom material: enhancing thermal insulation and sustainability
- Tailoring rheology and mechanical properties of 3D printed mortars with nanoclays and superplasticizer
- Fabrication of lightweight and thermal insulation roof tiles using industrial wastewater sludge
- Effect of axial compression ratio and beam end reinforcement ratio on the failure mode of RC frames
- Fatigue-based performance study of arch rib joints in CFST truss arch bridges
- Review Articles
- Granite powder in concrete: a review on durability and microstructural properties
- Properties and applications of warm mix asphalt in the road construction industry: a comprehensive review and insights toward facilitating large-scale adoption
- Artificial Intelligence in the synthesis and application of advanced dental biomaterials: a narrative review of probabilities and challenges
- Recycled tire rubber as a fine aggregate replacement in sustainable concrete: a comprehensive review
- Performance evaluation of blended cement mortar with supplementary cementitious materials: from pozzolans to industrial wastes
- A review on rutting in asphalt concrete in Saudi Arabia: mitigation strategies, innovations, and future directions
- 10.1515/rams-2025-0227
- Material properties, rheology, printability, and mechanical performance of waste glass powder in 3D concrete printing: a comprehensive review
- 10.1515/rams-2025-0228
- Rapid Communication
- Recent advances in resistive strain sensors: from materials and fabrication to applications in plant wearables
- Special Issue on AI-Driven Advances for Nano-Enhanced Sustainable Construction Materials - Part II
- Sustainable approach to control autogenous shrinkage in low water–cement ratio concretes
- Use of explainable symbolic regression approaches for predicting nanomaterial-enhanced concrete performance
