Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering ( IF 1.7 ) Pub Date : 2022-07-12 , DOI: 10.1177/09544070221109027 Weichen Wang, Junqiu Li, Fengchun Sun
Based on the artificial potential field theory, a hierarchical obstacle avoidance assisted driving framework is proposed in this paper, in order to solve the obstacle avoidance assisted driving problem of distributed heavy vehicles. Initially, a desired lateral position potential field (DLPPF) that reflects the driver’s driving intention is applied based on the constant turn rate and velocity (CTRV) model. And a real-time obstacle avoidance path can be obtained and further updated through a comprehensive consideration of the safety of obstacle avoidance and the obstacle repulsion potential field (ORPF). In addition, a differential drive assistance steering (DDAS) on the heavy vehicle steering bridge has been adopted to realize avoiding obstacles, and additional yaw moment to the vehicle’s non-steering axle has been utilized to ensure the maneuverability and stability of vehicle. Aiming to solve the lower layer control problem, a variable weight controller based on model predictive control (MPC) is designed to coordinate path tracking performance and dynamics control. Finally, through simulations and comparisons, the effectiveness of the obstacle avoidance strategy is verified.
中文翻译:
多轴分布式重型车辆避障辅助控制
为了解决分布式重型车辆的避障辅助驾驶问题,本文基于人工势场理论,提出了一种分层避障辅助驾驶框架。最初,基于恒定转弯率和速度 (CTRV) 模型应用反映驾驶员驾驶意图的期望横向位置势场 (DLPPF)。通过综合考虑避障安全性和障碍物斥力势场(ORPF),可以得到实时避障路径并进一步更新。此外,在重型车辆转向桥上采用差动驱动辅助转向(DDAS)实现避障,并利用车辆非转向轴的附加横摆力矩来保证车辆的机动性和稳定性。针对低层控制问题,设计了一种基于模型预测控制(MPC)的变权控制器,以协调路径跟踪性能和动态控制。最后通过仿真对比,验证了避障策略的有效性。