Abstract
AbstractAnti-rollover is a critical factor to consider when planning the motion of autonomous heavy trucks. This paper proposed a method for autonomous heavy trucks to generate a path that avoids collisions and minimizes rollover risk. The corresponding rollover index is deduced from a 5-DOF heavy truck dynamic model that includes longitudinal motion, lateral motion, yaw motion, sprung mass roll motion, unsprung mass roll motion, and an anti-rollover artificial potential field (APF) is proposed based on this. The motion planning method, which is based on model predictive control (MPC), combines trajectory tracking, anti-rollover APF, and the improved obstacle avoidance APF and considers the truck dynamics constraints, obstacle avoidance, and anti-rollover. Furthermore, by using game theory, the coefficients of the two APF functions are optimised, and an optimal path is planned. The effectiveness of the optimised motion planning method is demonstrated in a variety of scenarios. The results demonstrate that the optimised motion planning method can effectively and efficiently avoid collisions and prevent rollover.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province
Publisher
Springer Science and Business Media LLC
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