文章基本信息

标题：Design and robustness analysis of autonomous vehicles in intersections
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作者：Péter Szilassy ; Balázs Németh ; Péter Gáspár 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：8
页码：321-326
DOI：10.1016/j.ifacol.2019.08.090
语种：English
出版社：Elsevier
摘要：AbstractThe paper proposes the design of a neural-network-based control strategy of autonomous vehicles in intersections. The motivation of the neural network approach is to reduce the numerically-intensive computation of the optimization problem in which the motions of autonomous vehicles are formed. In the method the neural network is trained through a preliminary optimal off-line solution. Moreover, a robustness analysis on the neural network based control strategy is proposed. The focus of the analysis is to consider the impact of the position and speed estimation errors on the motion of vehicles. The design and the analysis are illustrated through CarSim simulation examples.
关键词：Keywordsautonomous vehiclesneural networksintersectionsconstrained nonlinear optimization