Optimization-based motion primitive automata for autonomous driving
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Matheus V. A. Pedrosa
Matheus V. A. Pedrosa received the bachelor's degree in computer engineering from the Federal University of Rio Grande do Norte, Natal, Brazil, in 2016, and the master's degree in automation and systems engineering from the Federal University of Santa Catarina, Florianópolis, Brazil, in 2018. He is currently pursuing the Ph.D. degree with the Chair of Systems Modeling and Simulation, Department of Systems Engineering, Saarland University, Saarbrücken, Germany, under the supervision of Prof. Dr. Kathrin Flaßkamp.
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Patrick Scheffe
Patrick Scheffe received the B.Sc. degree in mechanical engineering and the M.Sc. degree in automation engineering from RWTH Aachen University, Aachen, Germany, in 2016 and 2019, respectively, where he is currently pursuing the Ph.D. degree in computer science with the Chair of Embedded Software. His research interests include distributed decision-making for networked control systems and its application to connected and autonomous vehicles.
Bassam Alrifaee received the Ph.D. degree from the Institute of Automatic Control, RWTH Aachen University, Aachen, Germany, in 2017. From 2011 to 2017, he was a Research Associate with the Institute of Automatic Control, RWTH Aachen University. He is currently a Senior Researcher and a Lecturer with the Chair of Embedded Software, RWTH Aachen University. He is the Founder of the Cyber-Physical Mobility Group and Lab, Aachen, Germany. His research interests include: 1) networked control systems; 2) service-oriented software architectures for control systems; and 3) applications of 1) and 2) to connected and autonomous vehicles. He is a principal investigator of several projects.
Kathrin Flaßkamp received the Diploma degree in technomathematik (applied mathematics with engineering) and the Ph.D. (Dr.rer.nat.) degree in mathematics from Paderborn University, Paderborn, Germany, in 2008 and 2013, respectively. She is currently a Full Professor of Systems Modeling and Simulation with Saarland University, Saarbrücken, Germany. Her research is within the field of modeling, simulation, optimization, and control, focusing on the development of numerical methods and on applications.
Abstract
Trajectory planning for autonomous cars can be addressed by primitive-based methods, which encode nonlinear dynamical system behavior into automata. In this paper, we focus on optimal trajectory planning. Since, typically, multiple criteria have to be taken into account, multiobjective optimization problems have to be solved. For the resulting Pareto-optimal motion primitives, we introduce a universal automaton, which can be reduced or reconfigured according to prioritized criteria during planning. We evaluate a corresponding multi-vehicle planning scenario with both simulations and laboratory experiments.
Zusammenfassung
Die Trajektorienplanung autonomer Fahrzeuge kann basierend auf Bewegungsprimitiven erfolgen. Diese kodieren nichtlineares Systemverhalten in diskrete Automaten. In diesem Aufsatz betrachten wir die optimale Trajektorienplanung. Da typischerweise mehrere Optimierungskriterien zu berücksichtigen sind, müssen multikriterielle Optimierungsprobleme gelöst werden. Für die resultierenden Pareto-optimalen Bewegungsprimitiven stellen wir einen universellen Automaten vor. Dieser kann während der Planung, je nach priorisierten Kriterien, reduziert oder rekonfiguriert werden. Wir evaluieren den Ansatz für ein Planungsszenario mit mehreren Fahrzeugen sowohl in Simulationen als auch in Laborexperimenten.
Funding source: Deutsche Forschungsgemeinschaft
Award Identifier / Grant number: Unassigned
About the authors
Matheus V. A. Pedrosa received the bachelor's degree in computer engineering from the Federal University of Rio Grande do Norte, Natal, Brazil, in 2016, and the master's degree in automation and systems engineering from the Federal University of Santa Catarina, Florianópolis, Brazil, in 2018. He is currently pursuing the Ph.D. degree with the Chair of Systems Modeling and Simulation, Department of Systems Engineering, Saarland University, Saarbrücken, Germany, under the supervision of Prof. Dr. Kathrin Flaßkamp.
Patrick Scheffe received the B.Sc. degree in mechanical engineering and the M.Sc. degree in automation engineering from RWTH Aachen University, Aachen, Germany, in 2016 and 2019, respectively, where he is currently pursuing the Ph.D. degree in computer science with the Chair of Embedded Software. His research interests include distributed decision-making for networked control systems and its application to connected and autonomous vehicles.
Bassam Alrifaee received the Ph.D. degree from the Institute of Automatic Control, RWTH Aachen University, Aachen, Germany, in 2017. From 2011 to 2017, he was a Research Associate with the Institute of Automatic Control, RWTH Aachen University. He is currently a Senior Researcher and a Lecturer with the Chair of Embedded Software, RWTH Aachen University. He is the Founder of the Cyber-Physical Mobility Group and Lab, Aachen, Germany. His research interests include: 1) networked control systems; 2) service-oriented software architectures for control systems; and 3) applications of 1) and 2) to connected and autonomous vehicles. He is a principal investigator of several projects.
Kathrin Flaßkamp received the Diploma degree in technomathematik (applied mathematics with engineering) and the Ph.D. (Dr.rer.nat.) degree in mathematics from Paderborn University, Paderborn, Germany, in 2008 and 2013, respectively. She is currently a Full Professor of Systems Modeling and Simulation with Saarland University, Saarbrücken, Germany. Her research is within the field of modeling, simulation, optimization, and control, focusing on the development of numerical methods and on applications.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This research is supported by the Deutsche Forschungsgemeinschaft (German Research Foundation) within the Priority Program SPP 1835 “Cooperative Interacting Automobiles” (grant number: KO 1430/17-1).
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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Articles in the same Issue
- Frontmatter
- Editorial
- Cooperative interacting automobiles
- Methods
- Trajectory-based traffic observation of cooperation at a road narrowing
- Verhaltensentscheidungen für das automatische Fahren an innerstädtischen T-Kreuzungen mittels ereignisdiskreter Systeme
- Evaluation of the communication means of lateral driving dynamics at motorway slip roads
- Human system patterns for interaction and cooperation of automated vehicles and humans
- Applications
- Analyzing track management strategies for multi object tracking in cooperative autonomous driving scenarios
- Optimization-based motion primitive automata for autonomous driving
- Interaktive Trajektorienplanung mittels gemischt-ganzzahliger quadratischer Programmierung
- Optimizing the channel resource usage for sensor data sharing with V2X communications
- Tools
- Testing distributed trajectory planning in the cyber-physical mobility lab
Articles in the same Issue
- Frontmatter
- Editorial
- Cooperative interacting automobiles
- Methods
- Trajectory-based traffic observation of cooperation at a road narrowing
- Verhaltensentscheidungen für das automatische Fahren an innerstädtischen T-Kreuzungen mittels ereignisdiskreter Systeme
- Evaluation of the communication means of lateral driving dynamics at motorway slip roads
- Human system patterns for interaction and cooperation of automated vehicles and humans
- Applications
- Analyzing track management strategies for multi object tracking in cooperative autonomous driving scenarios
- Optimization-based motion primitive automata for autonomous driving
- Interaktive Trajektorienplanung mittels gemischt-ganzzahliger quadratischer Programmierung
- Optimizing the channel resource usage for sensor data sharing with V2X communications
- Tools
- Testing distributed trajectory planning in the cyber-physical mobility lab
