基于DMPC的无信控交叉口智能网联车辆多车协同轨迹规划

Multi-vehicle cooperative path planning at untrusted intersections based on DMPC

为了解决智能网联自动驾驶环境下无信控十字交叉口多车协同通行的冲突问题,该文提出了一种基于分布式模型预测控制(DMPC)的多车协同轨迹规划方法。采用分布式模型预测框架实现多车协同轨迹规划的分布式独立计算,利用滚动时域预测周车轨迹实现车-车未来状态交互,基于智能网联环境车-车交互通信功能实现规划结果共享;引入道路边界约束、加速度约束与碰撞约束等车辆安全约束条件,通过二次规划求解可以安全通行十字路口的多车轨迹;基于MATLAB驾驶场景生成模块建立无信控十字交叉口环境,并在2种场景下验证了该方法的有效性。结果表明:在直行工况和左转工况下多车间最小距离分别为2.58 m和2.99 m,均满足避撞的安全距离约束,实现了多车之间的协同避撞并且能够保证通行效率。

A multi-vehicle collaborative path planning method based on distributed model predictive control(DMPC)was proposed to address the conflict issues in the intelligent connected autonomous driving environment at signal-free intersections with multiple vehicles,The approach employed a distributed model predictive control framework for independent calculations among multiple vehicles.It utilizes a rolling temporal prediction of surrounding vehicle trajectories to facilitate future state interactions between vehicles.The planning results were shared based on the vehicle-vehicle interaction communication feature in the intelligent connected environment.The method introduced safety constraints such as road boundary constraints,acceleration constraints,and collision constraints.The safety trajectory for multiple vehicles to safely navigate through a signal-free intersection was computed through quadratic programming.The effectiveness of the proposed method was validated by establishing a signal-free intersection environment using the MATLAB driving scenario designer module under two different scenarios.The results show that under straight and curved driving conditions,the inter-vehicle minimum distances are 2.58 m and 2.99 m,respectively,meeting the safety distance constraints for collision avoidance.The method achieves collaborative collision avoidance among multiple vehicles while ensuring passage efficiency.