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Utilization of intelligent vehicle units for train set dispatching

  • Oldřich Kodym EMAIL logo
Published/Copyright: December 31, 2021
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Abstract

This study focuses on the synthesis of particular solutions with the aim of improving accuracy and safety in rail transport systems. It is based on logistic/transport units equipped with a smart unit for information acquisition, processing, and communication (intelligent vehicle unit [IVU]). These IVUs can communicate with their neighbors and process their data to automatically create a superior/parent unit – the train. The train unit (the engine) has the ability to communicate with connected information systems. In this way, information stored in information systems can be verified, in real time updated, and supplied to all parties acting in the logistic chain. Algorithms used in each IVU are a crucial part of this kind of system. Designed system is modeled, and some simulations are used for verification.

1 Introduction

Nowadays, the Internet of “anything” (including Transportation 4.0) is the buzzword.

Nowadays, we are more frequently encountering the need for regular measurements of various physical values. This includes the collection of climatic data, acoustic and chemical parameters, or the electrical properties of a given object. As they are typically a whole network of different sensors, the main problem arises when transferring their values to a central unit. The classical solution, which uses a direct cable connection, is not very suitable. The installation of such a network always includes high costs and usually a complex approach as well because we have a fixed location of the sensors. For this reason, wireless sensor networks are preferable for transmitting data from more distant sensors. These not only eliminate the high cost of cable connections and installation but also provide a highly flexible solution.

A wireless sensor network (WSN) or wireless sensor and actuator network, is composed of autonomous sensors (and actuators) spread over a space, and it usually consists of many low-cost and low-energy sensors spread over a large area (Figure 1). Measured quantities are transmitted over the network to the main storage. Newer sensor networks allow bidirectional communication, so they can be controlled as well as monitored. Originally, sensor networks were used in military projects, and they have gradually expanded into many other industries. Wireless sensor networks combine high connectivity, low-power consumption, and interoperability with electronic devices and various data systems.

Figure 1 
               WSN network scheme [1].
Figure 1

WSN network scheme [1].

Intelligent Transport Systéme, sometimes referred to as transport telematics, links information and telecommunication technologies with transport engineering and the support of other related disciplines (economics, transport theory, systems engineering, etc.) to provide transport and transport process management systems for existing infrastructure (increased transport performance and efficiency, increased transport safety, increased transport comfort, etc.) [2].

The train marshaling problem consists of rearranging an incoming train in a marshaling yard in such a way that cars with the same destinations appear consecutively in the final train, and the number of needed sorting tracks is minimized. Besides an initial roll-in operation, just one pull-out operation is allowed. This problem can be solved using a new lower bound on the optimal objective value by partitioning an appropriate interval graph. Furthermore, upper and lower bounds can be provided and a corresponding optimization can be solved. An experimental evaluation of lower bound and algorithm shows the practical tightness of the results [3].

The future of rail transport will depend on smart transport systems. New services such as integrated safety, asset management, and predictive maintenance should enable timely decision making on safety, planning, and system capacity. Smart railways are a combination of interconnected technology solutions and components and modern transport infrastructure. These systems require seamless wireless connectivity with high data rates and integrated software solutions to meet the ever-increasing demand for energy-efficient and safer services. The rail industry has undergone a major revolution since 2005 with the advent of the Internet of things (IoT) and smart city projects, which have led to the development of solutions such as smart ticketing, passenger informatics, rail analytics, and dynamic route planning. IoT-based industry solutions have brought new business models that are impacting the global rail industry.

The rail industry has started to exploit the opportunities defined by the industrial IoT and has enabled the application of the same communication technologies within the Internet of trains model. The IoT aims to increase the safety and efficiency of railway. Economic savings can also be achieved through simplification of processes and better decision making by analyzing data from sensors on board trains. In addition, data analysis can reduce the maintenance time itself. By monitoring the railway infrastructure, the risk of train collisions, derailments, terrorism, and wagon failures is reduced. Another example of IoT enhancing safety on railways is the on-board train location system, essential for determining the location of other trains, which can be used to avoid collisions, make operations safer near tracks, or optimize track utilization.

2 Methods

With the IoT connecting millions of shipments being transported, tracked, and stored in real time every day, it will be possible to achieve higher levels of operational efficiency in logistics itself over the next decade. Linking pallets and stored items will ensure smarter inventory management. In freight transport, tracking of transported goods will be even faster, more accurate, predictable and safer. A connected fleet will prevent unexpected technical breakdowns and minimize downtime by optimizing the timing of regular service inspections and continuously monitoring and evaluating the technical condition of vehicles. By linking delivery drivers to surrounding vehicles and people, it will be possible to optimize the use of transport capacity even on return journeys, leading to even greater efficiency in the final stage of distributing goods into the hands of consumers. Toward customers, this will mean faster, more reliable, and cost-effective services [4].

2.1 The information system for transport infrastructure

The information system of the infrastructure manager records the composition of all trains on its network. It shall make this data available to authorized users. It fulfils two basic functions:

  • for an infrastructure manager to obtain data on trains on its network and

  • for an operator without its own information system, it is used to obtain information on train composition, train ready for departure, and driver performance on the train and to transfer it to the information system that records the composition of all trains operated on its network (ISC).

    Within the development of the information system, it is planned to extend its functions in the areas of recording the composition of all trains and selected events on wagon movements on the network of the infrastructure manager and other smaller operators. It will provide this data to authorized users.

    The information system will perform the following functions:

  • the infrastructure manager will be able to access train and wagon data recorded in the information system (IS) and

  • the operator will capture information on train composition, train ready for departure, and driver performance on the train and selected wagon events in the IS and transfer them to the IS. The wagon operational database of wagon and intermodal unit movements module – operational database of wagon and intermodal unit movements – will be extended.

2.2 Electronic check of transport unit status

The system for automatic identification of the operating condition of transport and/or transport means enabling continuous acquisition of up-to-date information on the technical condition of transport and/or transport means for predicting repairs or removal of these means from transport operation to prolong their service life, eliminate the occurrence of accident situations on transport routes, etc.

The aforementioned drawbacks are eliminated by the circuitry for automatic identification of the operating condition of the transport and/or conveyance means. It requires at least one data exchange 11 provided with a software component for collecting, analyzing, and evaluating data information. The data exchange is connected, via a bidirectional data link, to at least one memory module for storing static and dynamic data, and also the data exchange is connected, via a bidirectional data link, to at least one sensor for sensing the current operational state of the transport and/or transportation means.

It is preferable that the data center is connected to at least one user module via a bi-directional data link. It is further preferable that the data center is connected via a bi-directional data link to at least one communication module.

The system for automatic identification of the operational status of transport and/or transportation means, whose essence is that it comprises at least one circuit representing a separate unit and a computing technique provided with a service information system, wherein the computing technique is provided with a compatible data/information transfer interface.

Advantageously, the communication module of at least one circuitry is arranged to communicate via a compatible data/information transfer interface with the computer technology.

The railway car with an electronic check of the technical condition (see Figure 2) has a data control panel, which is connected to the revolution/speed sensor by a wireless connection, wirelessly connected to a temperature sensor, a pressure sensor, a brake condition sensor, and a brake cylinder position sensor. The data control panel is wirelessly connected to the load weight sensor, the service block, and the operating block.

Figure 2 
                  Railway car with electronic check of technical condition [5]: (1) data control panel, (2) revolution/speed sensor, (3) temperature sensor, (4) pressure sensor, (5) brake condition sensor, (6) service/maintenance block, (7) operating/communication block, (8) brake cylinder position sensor, (9) cargo weight sensor, and (10–17) data (wireless) connections.
Figure 2

Railway car with electronic check of technical condition [5]: (1) data control panel, (2) revolution/speed sensor, (3) temperature sensor, (4) pressure sensor, (5) brake condition sensor, (6) service/maintenance block, (7) operating/communication block, (8) brake cylinder position sensor, (9) cargo weight sensor, and (10–17) data (wireless) connections.

In view of the fact that the operability of the rolling stock is not sufficiently attended to for various reasons, frequent collisions or accidents occur in the course of railway transport operation. This can be prevented by systematic monitoring and recording of the technical condition of railway wagons. The solution is applicable in all companies and firms operating rail transport. There are many more possible applications, and one important area is the integration into operating information systems, where the possibility of human failure can be significantly eliminated.

3 Results – design of an algorithm to compose a train

The IVU is a railway carriage (wagon), in this proposal a freight car, which has modern technologies of identification, geolocation, measurement, and communication.

3.1 Use of a utility model

Figure 3 shows a schematic of the IVU, which is equipped with bumper impact measurement technology, a speed sensor, bearing and wheelset temperature sensors, communication technology (at both ends of the car), a global positioning system unit, a power supply, and a central unit that stores data in memory [5]. In addition, this type of vehicle assumes communication with the load (ISO container), which is also equipped with wireless communication and its own sensors (e.g., temperature, humidity, and impact measurement). The interconnection of the individual components within the vehicle is assumed to be via cable harnesses. In addition, the IVU should be equipped with an interface for connecting a computer personal digital assistant to set or update the values in memory (e.g., secure digital memory card) with, for example, the following data:

  • unique car identification (European vehicle number, EVN, specified by Union Internationale des Chemins de fer, International Union of Railways, UIC),

  • date of entry into operation,

  • number of chassis and axles,

  • date of last inspection or repair,

  • speed limits of the car, and

  • weights (per axle, per wheel, load weight, and a maximum load weight).

Figure 3 
                  Smart transport unit (wagon + container) [6].
Figure 3

Smart transport unit (wagon + container) [6].

The intention is to design a solution for

  • automated checking of the correct ordering of the IVU in the train set,

  • elimination of human errors,

  • linking to a higher level information system,

  • reducing the risk of train accidents,

  • prolonging the service life of the mechanical parts of the wagons,

  • prediction of necessary maintenance, and

  • monitoring the transport conditions of the goods being transported.

3.2 IVU data processing

The proposed algorithm starts with the moment of the IVU hitting the IVU in front of it in the normal car shifting (shifting, over a binding hump, etc.). Design of data processing was developed by Mr. Urbanec in his diploma thesis [6] under the supervision of author of this article. This moment is preceded by the steps described in the previous section:

Selection of available IVUs is according to the parameters of the planned train journey,

  • that is, type of load,

  • operability of the IVU,

  • speed limits on the planned route,

  • braking percentages, and

  • maximum length of the train set.

The result of this step is a list of cars (with the EVN) as they should be ordered in sequence. This list is later made available, among others, to the driver and the train manager.

This is followed by the sequential physical movement of the IVUs (shunters, remote control) into the final assembly. During the shift, the cars are sequenced, with each car always hitting the previous set and stopping. The first car is not hit but is braked by other means (hand brake, magnetic brake, or stop). In normal practice, at this point, the driver steps in and should walk around the entire set (from both sides of the set) and check to see whether any cars have been swapped during the shift or whether any cars are missing. At the same time, the train crew (trainmaster, conductor) goes around the train and enters the identification data of each car into the portable personal cash register (PPCR). The PPCR sends the data, for example, via Global System for Mobile Communications – Railway (GSM-R) or other communication channels to the IS.

At this point, the proposed algorithm comes into play, so that the final phase is no longer necessary.

As there is a difference between the wagon and the locomotive in terms of functionality, two different algorithms need to be built. The first algorithm will be designed for the intelligent car and the second algorithm for the intelligent locomotive. Both algorithms will be involved in the communication among the cars themselves and between the car and the locomotive. Each car will behave autonomously. If a locomotive is included in the consist that is not traction and is passive, it will become a car in terms of communication and subordination. The (traction) locomotive will, therefore, be superior to the wagons in terms of authority. However, since the locomotive’s inclusion will only occur at the end, the wagons will have to act “for themselves” until that point.

Algorithm for intelligent car has two phases. In the first phase (Figure 4), the car is assigned to the train set, and in the second phase (Figure 5), it is already assigned, and its task is to mediate communication among the cars (or between the car and the locomotive) and also to transmit information about its current status.

Figure 4 
                  Algorithm for composition [6].
Figure 4

Algorithm for composition [6].

Figure 5 
                  Algorithm for wagon movement on the rail [6].
Figure 5

Algorithm for wagon movement on the rail [6].

Algorithm for the intelligent locomotive (Figure 6) is used for controlling communication between cars and locomotive, collecting information about the current status of individual cars, verifying the presence of all cars in the set and also remote communication with information systems, or data transfer to clouds and data warehouses (Table 1).

Figure 6 
                  Algorithm for smart engines [6].
Figure 6

Algorithm for smart engines [6].

Table 1

Combinations of stages [6]

Impact from the front Impact from the rear Communication on Impact confirmed by another IVU Situation
No No No No The car standing outside the classification yard
Yes No Yes No The car is heading toward the classification yard (engine impact)
No Yes Yes No The car is heading toward the classification yard (engine impact)
Yes No Yes Yes The car is placed into another car; it is the end car
No Yes Yes Yes The car is placed into another car; it is the end car
Yes Yes Yes No The car is heading toward the classification yard (engine is pushing more cars toward classification yard)
Yes Yes Yes Yes The car is part of the train set; it is not the end car

The car is already in the lineup (shift complete), knows its order, knows who its neighbors are (the car in front and the car behind it), and knows their ID. It maintains constant communication with both, because it can be the point (intermediary) through which data flows in both directions, and because it can itself, if necessary, send a warning or alarm signal to the locomotive (alarm). It is also ready to inform the locomotive of a possible “train break/disconnection” in the event of a communication failure with the car behind it.

At the same time, the car sends the current status from its sensors at set intervals or at the locomotive’s request (the “report” and “report back” instructions). Even if this prompt does not occur, the car performs cyclic measurements and sends a warning to the parent locomotive if the limit values are exceeded. Each message that is serially transmitted among cars and between cars and locomotive is always accompanied by the ID and the order of the car to which the message is related.

Once the journey is complete, the message is first relayed to the next car, and then the communication systems are switched off and put to sleep.

The algorithm for a smart engine provides the following:

  • monitoring of correct car composition according to the assignment given to the train driver and conductor (car number, required order) and

  • continuous checking of the train set compactness during the movement/journey as well as checking journey safety and cargo security.

    The smart engine is equipped, apart from common technologies, with the following:

  • communication with the car behind it (short distance communication),

  • communication toward the IS (long distance communication),

  • data center where data about car status are collected and which enables to transmit instructions to cars automatically or manually,

  • technology for impact measuring in buffers (strain gauge), and

  • GPS module (time synchronization).

    After the locomotive hits the (either) end of the assembly, the locomotive starts communicating with the IVU and comparing the impact time data (option A). Unlike cars, which often arrive at the lineup with considerable kinetic energy, the locomotive is assumed to make a sensitive assignment without much impact. A sensitive strain gauge in the buffer will detect the impact, but the physical displacement of the car may no longer occur. Therefore, the second technology (option B) is not applicable to the locomotive.

    The first car receives the information that it is first and starts to write a message about the order of the cars by writing down its ID and sending it to the next IVU (whose ID it already knows from the previous communication). The next car enters its ID in the message at the second position and this is how the cars use the communication gates to pass the message to the last car. The last car deduces from this information (as it has only experienced one impact) that it is the last car and, after inserting its ID in the last position of the message, returns it in the opposite direction in sequence to the locomotive. The resulting line-up is compared with the desired line-up, and, after reconciliation, the train is ready to depart (instruction “shift complete”).

    During the train journey, communication continues in both directions at preset periods or at any time according to the operator’s needs (the “announcement” call). By analyzing the resulting message, the system checks the safe running of the entire train set. Furthermore, the system checks the integrity of the train set during the journey (“train tear”) or other parameters such as the following:

  • bearings and wheelset firing

  • wheelset ovality,

  • blocked wheels, and

  • temperature and humidity of the cargo (perishables).

We are able to measure these variables using sensors and can communicate with the control units of individual IVUs over metallic or wireless communication networks. In the event of exceeding the limit values of the measured quantities, the locomotive will receive an “alarm” message. Depending on the control unit settings, either immediately or after approval by the operator (no stopping in the tunnel) the train is stopped, and the information is transmitted to the external IS.

At the end of the journey, the locomotive sends the “End of journey” message to the assembly.

3.3 Evaluation of modeling and simulation results

Modeling of transportation systems is often used with benefits of simulation results for decision making. The functionality of the designed algorithm for car composition was created in in-service training lab [7]. Several modeling and simulating environments are available here [8]. Presented model was verified and demonstrated using a simulation model in simulation software (see Figure 7).

Figure 7 
                  Design of simulation model with results of simulation [6].
Figure 7

Design of simulation model with results of simulation [6].

The model represents a real situation at the marshaling yard where the wagons arrive (e.g., by means of a tie-back or by pushing by a locomotive). In this case, there are a total of three tracks on which the designated wagons are brought. The track number for each car is given according to the timetable; the cars are marked with the EVN code. Once the setup is complete, the locomotive is brought in, and the algorithm described verifies that the order of the cars matches the request. If it does, the train departs outside the marshaling yard. If there is a shifting error, the consist is declared unfit, and the cars are handed over for sorting and reassembly.

After the end of the simulation time 1 shift, that is, 8 h, we can determine:

  • 446 cars were handled in total,

  • the total number of correctly composed trains is 39, and

  • the total number of incorrectly composed trains is 5.

4 Discussion

The presented system of utilization of intelligent vehicle units (IVUs) for train set dispatching can improve the quality and efficiency of important parts of supply chain. It can minimize errors and inconsistency of information in information systems and shorten delays between data gathering and presenting to parties in the supply chain. Designed system was modeled and results of simulations confirmed estimated functionalities.

Thera are many intelligent/information/organization systems as reasonable parts of logistic chain. One of the leading organizations is GS1. It is also active in processes of standardization [9]. Presented IVUs can be implemented in almost all traceability systems.

Single, particular solution can bring an effort or improvement of any process, but the best is to get all particular solutions to synergy.

5 Conclusion

The article deals with the design of an algorithm that could be the basis for the development of specific software for the IVU and for a locomotive that would be compatible with these cars.

We have got used to new technologies rushing at us from all sides faster than before, and this will continue to be the case. However, their applicability to mass-produced products varies according to their type. It is different, for example, for mobile phones than for railways. While in the case of the telephone, the novelty is already present in a new model, implementation in rail transport is limited by the huge number of wagons and locomotives of different equipment and various ages, many information systems, safety, and communication technologies. Due to the progressive standardization and interoperability within the EU and Europe, this will become increasingly easier. The problem of applying new technologies is not on the side of the car manufacturers, who can easily add new features to their products, but it is much harder to equip the whole infrastructure with the technology to make full use of such functionalities. This is primarily a question for the railway managers or owners. The problem is, therefore, mainly an economic one because the transition to this technology would have to be widespread, and this requires a large cost.

Acknowledgements

The utility model was designed in cooperation with Gaben company.

  1. Conflict of interest: Author states no conflict of interest.

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Received: 2021-07-09
Revised: 2021-10-19
Accepted: 2021-11-26
Published Online: 2021-12-31

© 2021 Oldřich Kodym, published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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