更安全的
背景(考古学)
运动规划
汽车工业
计算机科学
自动化
自动驾驶
运输工程
避障
运动(物理)
风险分析(工程)
人工智能
机器人
障碍物
工程类
计算机安全
业务
移动机器人
航空航天工程
政治学
法学
古生物学
机械工程
生物
作者
Laurène Claussmann,Marc Revilloud,Dominique Gruyer,Sébastien Glaser
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2019-05-15
卷期号:21 (5): 1826-1848
被引量:481
标识
DOI:10.1109/tits.2019.2913998
摘要
Self-driving vehicles will soon be a reality, as main automotive companies have announced that they will sell their driving automation modes in the 2020s. This technology raises relevant controversies, especially with recent deadly accidents. Nevertheless, autonomous vehicles are still popular and attractive thanks to the improvement they represent to people's way of life (safer and quicker transit, more accessible, comfortable, convenient, efficient, and environment-friendly). This paper presents a review of motion planning techniques over the last decade with a focus on highway planning. In the context of this article, motion planning denotes path generation and decision making. Highway situations limit the problem to high speed and small curvature roads, with specific driver rules, under a constrained environment framework. Lane change, obstacle avoidance, car following, and merging are the situations addressed in this paper. After a brief introduction to the context of autonomous ground vehicles, the detailed conditions for motion planning are described. The main algorithms in motion planning, their features, and their applications to highway driving are reviewed, along with current and future challenges and open issues.
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