Design of the optimal motions of autonomous vehicles in intersections through neural networks.

Authors: 
Nemeth, Balazs & Gáspár, Péter & Szőcs, Dávid & Mihály, András
Title of journal: 
IFAC-PapersOnLine, Volume 51, Issue 9
Year: 
2018
Relevant pages: 
Pages 19-24
DOI: 
https://doi.org/10.1016/j.ifacol.2018.07.004
Open access: 
Yes
Abstract: 
The handling of vehicle interactions is a challenge in the research into the traveling of autonomous vehicles. This paper focuses on collision-free motion design of autonomous vehicles to guarantee their minimum traveling time in intersections. First, a decision logic of the order of the vehicles in intersections is proposed. Based on the decision logic a constrained nonlinear optimization method is also proposed, with which the minimum traveling time of the vehicles without their collision is guaranteed. Since the on-line solution of the nonlinear optimization task can be numerically complex, a neural network based approximation of the optimal solution is developed. The efficiency of the method with various intersection scenarios is shown in the CarSim simulation environment.
SCI: 
No
Kiemelt: 
No
Pdf: 
No
Place of publication: 
https://www.sciencedirect.com/science/article/pii/S2405896318307201