Multi-vehicle cooperative path planning at untrusted intersections based on DMPC
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.
automotive engineeringsignal-free intersectionmulti-vehicle cooperationdistributed model predictive control(DMPC)path planning
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