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Article

Design of a Low-complexity Graph-Based Motion-Planning Algorithm for Autonomous Vehicles

1
Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, Stoczek u. 2, H-1111 Budapest, Hungary
2
Systems and Control Laboratory, SZTAKI Institute for Computer Science and Control, Kende u. 13-17, H-1111 Budapest, Hungary
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(21), 7716; https://doi.org/10.3390/app10217716
Received: 1 September 2020 / Revised: 13 October 2020 / Accepted: 28 October 2020 / Published: 31 October 2020
(This article belongs to the Special Issue Connected Automated Vehicles)
In the development of autonomous vehicles, the design of real-time motion-planning is a crucial problem. The computation of the vehicle trajectory requires the consideration of safety, dynamic and comfort aspects. Moreover, the prediction of the vehicle motion in the surroundings and the real-time planning of the autonomous vehicle trajectory can be complex tasks. The goal of this paper is to present low-complexity motion-planning for overtaking scenarios in parallel traffic. The developed method is based on the generation of a graph, which contains feasible vehicle trajectories. The reduction of the complexity in the real-time computation is achieved through the reduction of the graph with clustering. In the motion-planning algorithm, the predicted motion of the surrounding vehicles is taken into consideration. The prediction algorithm is based on density functions of the surrounding vehicle motion, which are developed through real measurements. The resulted motion-planning algorithm is able to guarantee a safe and comfortable trajectory for the autonomous vehicle. The effectiveness of the method is illustrated through simulation examples using a high-fidelity vehicle dynamic simulator. View Full-Text
Keywords: autonomous vehicles; motion-planning; trajectory design autonomous vehicles; motion-planning; trajectory design
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MDPI and ACS Style

Hegedűs, T.; Németh, B.; Gáspár, P. Design of a Low-complexity Graph-Based Motion-Planning Algorithm for Autonomous Vehicles. Appl. Sci. 2020, 10, 7716. https://doi.org/10.3390/app10217716

AMA Style

Hegedűs T, Németh B, Gáspár P. Design of a Low-complexity Graph-Based Motion-Planning Algorithm for Autonomous Vehicles. Applied Sciences. 2020; 10(21):7716. https://doi.org/10.3390/app10217716

Chicago/Turabian Style

Hegedűs, Tamás, Balázs Németh, and Péter Gáspár. 2020. "Design of a Low-complexity Graph-Based Motion-Planning Algorithm for Autonomous Vehicles" Applied Sciences 10, no. 21: 7716. https://doi.org/10.3390/app10217716

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