考虑驾驶员特性的网联车辆行驶路径规划和路径跟踪控制

Shared control between the driver and the automated controller, and cooperated trajectory planning between the intelligent vehicles intervened by the drivers are two problems having not been well solved in the field of semi-autonomous vehicle system. The states and the drivers’ information of the neighboring vehicles can be shared among the connected vehicles with the technology of information networking. In this proposal, the algorithm of trajectory planning and path following for connected semi-autonomous vehicles will be investigated considering the characteristics of the drivers. Firstly, based on analysis of the difference of the different drivers’ handling potentials, the shared control algorithm for combining the driver handling and the automation will be studied based on the game theory. With this algorithm, a suitable intervention is implemented and added to the driver’s maneuver, for improving performance of the human-vehicle system, releasing workload of the driver and improving satisfaction of the driver, subjecting to the constraints of collision avoidance and vehicle stability. Secondly, by considering drivers’ characteristics and intentions of the connected vehicles, the connected neighboring vehicles will be described as Multi-Agent System. The feasible safe trajectories of these vehicles will be determined based on the constraints of collision avoidance and vehicle stability. Then the optimal trajectories of the connected vehicles will be planned cooperatively by tradeoff between goals of the vehicles and the global objective of the Multi-Agent System. Thirdly, a test platform for trajectory planning and path following of the connected vehicles will be built, and the field test will be conduct. Implementation of this proposal will be of great importance to the research of algorithms on the trajectory planning and path following for the connected vehicles and their industrial applications.

驾驶员与自动控制如何共享车辆操纵权，以及有驾驶员参与操纵的智能多车路径协同规划，是半自主车辆控制领域需要解决的难题。网联车辆可通过信息互联共享邻近车辆的状态和驾驶员相关信息。本申请研究网联半自主驾驶车辆在考虑驾驶员特性时的路径规划和路径跟踪控制。在分析不同特性驾驶员操纵潜能差异的基础上，基于博弈论研究驾驶员与自动控制共享控制权的路径跟踪算法，对驾驶员操纵实施合适程度的干预以提高人−车系统性能，在碰撞避免和车辆稳定前提下减轻驾驶员工作负荷并提高其满意程度；考虑各车驾驶员特性和意图，将邻近的网联多车系统描述成多智能主体，根据碰撞避免和车辆稳定性等约束计算各车可行的安全行驶路径，并权衡各车的目标与系统全局目标，进行该网联多车系统的最优行驶路径协同规划；建立网联车路径规划和路径跟踪控制实验平台并进行实车试验。项目的实施对网联半自主车辆路径规划和路径跟踪算法的研究和工程应用有十分重要的意义。

项目建立了线控转向、电动力矩辅助转向和独立轮差动驱动辅助转向三种转向条件下的驾驶员-车辆-道路系统模型，其中车辆模型采用动力学模型或者运动学模型，系统模型考虑了驾驶员的转向操纵特性和偏好。基于神经网络驾驶员模型来预测驾驶转向行为，研究了驾驶员-车辆系统模型参数在线辨识方法。为实现线控转向车辆的人机协同路径跟踪，设计了考虑转向行为特性参数摄动和纵向车速时变性的模糊鲁棒共享控制器。基于驾驶员和差动辅助转向共享的人-车-路模型，考虑驾驶员特性参数不确定性，进行了驾驶员-差动辅助转向的共享控制器设计。研究了考虑驾驶员操纵特性的车辆交叉换道轨迹重新规划算法，大曲率弯曲道路环境下的车-车合作路径规划算法，以及复杂交通环境下多车协同的路径规划。为提高算法的实时性，研究了基于运动学车辆道路模型的人-车-路系统建模和轨迹规划方法。利用Matlab/Simulink和Carsim软件搭建仿真平台，对所提出的模型和规划、控制算法进行仿真试验研究。采用4:1和2:1的线控驱动/线控转向电动模型车搭建网联车实验平台，对所提出的网联车辆路径规划和路径跟踪算法进行了实验研究。研究结果表明在网联自动驾驶/高级辅助驾驶的路径规划和路径跟踪控制中，考虑驾驶员的心理/生理机能所体现出来的操纵特性和驾驶偏好，可以提高自动驾驶和人机协同驾驶系统的个性化辅助性能，提高车辆行驶的安全性，减轻乘员/驾驶员的操纵负荷。