Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making

International Journal of Advanced Robotic Systems

HongboGao¹ 

关键词: Car-following;    inverse reinforcement learning (IRL);    autonomous vehicle;    decision-making;    automatic driving;   

DOI  :  10.1177/1729881418817162

学科分类：自动化工程

来源: InTech

【 摘 要 】

There are still some problems need to be solved though there are a lot of achievements in the fields of automatic driving. One of those problems is the difficulty of designing a car-following decision-making system for complex traffic conditions. In recent years, reinforcement learning shows the potential in solving sequential decision optimization problems. In this article, we establish the reward function R of each driver data based on the inverse reinforcement learning algorithm, and r visualization is carried out, and then driving characteristics and following strategies are analyzed. At last, we show the efficiency of the proposed method by simulation in a highway environment.

【 授权许可】

CC BY