Policy Iteration Based Approximate Dynamic Programming Toward Autonomous Driving in Constrained Dynamic Environment

In the area of autonomous driving, it typically brings great difficulty in solving the motion planning problem since the vehicle model is nonlinear and the driving scenarios are complex. Particularly, most of the existing methods cannot be generalized to dynamically changing scenarios with varying s...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 24; H. 5; S. 1 - 11
Hauptverfasser:	Lin, Ziyu, Ma, Jun, Duan, Jingliang, Li, Shengbo Eben, Ma, Haitong, Cheng, Bo, Lee, Tong Heng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms approximate dynamic programming Approximation algorithms Autonomous driving Autonomous vehicles constrained optimization Dynamic programming Heuristic algorithms Iterative methods Motion planning Multilayers Neural networks Path planning Path tracking Planning reinforcement learning Roads Task analysis Tracking control Vehicle dynamics
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
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