A Review of Motion Planning for Highway Autonomous Driving

• Published in: IEEE transactions on intelligent transportation systems Vol. 21; no. 5; pp. 1826 - 1848
• Main Authors: Claussmann, Laurene, Revilloud, Marc, Gruyer, Dominique, Glaser, Sebastien
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-05-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accidents; Advanced driver assistance systems; Algorithms; Automobile industry; Automobiles; Automotive engineering; Autonomous cars; autonomous driving; Autonomous vehicles; Car following; Context; Decision making; Drivers; Engineering Sciences; Feasibility; intelligent vehicles; Lane changing; Motion planning; Obstacle avoidance; Other; path planning; Planning; Roads; Roads & highways; Unmanned ground vehicles; DECISION MAKING; INTELLIGENT VEHICLES; AUTONOMOUS DRIVING; MOTION PLANNING; PATH PLANNING; ADVANCED DRIVER ASSISTANCE SYSTEMS (ADAS)
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2019.2913998

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.