Open AccessChallenges and Possibilities of Overtaking Strategies for Autonomous Vehicles
Author(s) -
Tamás Hegedűs,
Balázs Németh,
Péter Gáspár
Publication year - 2020
Publication title -
periodica polytechnica. transportation engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 15
eISSN - 1587-3811
pISSN - 0303-7800
DOI - 10.3311/pptr.15848
Subject(s) - overtaking , computation , computer science , cluster analysis , process (computing) , graph , range (aeronautics) , artificial intelligence , theoretical computer science , engineering , algorithm , aerospace engineering , operating system , civil engineering
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.