Challenges and Possibilities of Overtaking Strategies for Autonomous Vehicles

Authors

  • Tamás Hegedűs
    Affiliation

    Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Stoczek street 2, Hungary

  • Balázs Németh
    Affiliation

    Institute for Computer Science and Control, H-1111 Budapest, Kende street 13-17, Hungary

  • Péter Gáspár
    Affiliation

    Institute for Computer Science and Control, H-1111 Budapest, Kende street 13-17, Hungary

https://doi.org/10.3311/PPtr.15848

Abstract

This paper present three distinct probability-based methods for decision making and trajectory planning layers of overtaking maneuvering functionality for autonomous vehicles. The computation time of the proposed decision-making algorithms may be high, because the number of describing parameters of the traffic situations may vary in a high range. The presented clustering-based, graph-based and dynamic-based methods differ in the complexity of their computation algorithms. Since the decision-making process may require considerable online computation effort, a neural-network-based approach is presented for implementation purposes.

Keywords:

overtaking, decision making, trajectory planning, autonomous vehicles

Published Online

2020-08-07

How to Cite

Hegedűs, T., Németh, B., Gáspár, P. (2020) “Challenges and Possibilities of Overtaking Strategies for Autonomous Vehicles”, Periodica Polytechnica Transportation Engineering, 48(4), pp. 320–326. https://doi.org/10.3311/PPtr.15848

Issue

Section

Articles