Adaptive control for vehicle formation movement with multiple sensors
The adaptive motion algorithm based on predetermined motion trajectories is studied in this paper,addressing the problem of vehicle formation with multiple sensors.Firstly,optimal da-ta fusion estimation of sensor data from multiple sensors was obtained through processing using Kalman filtering,acquiring the optimal position information of the vehicle formation.Then,the next step of vehicle formation motion planning was obtained through the exchange of position es-timation information between vehicles.Two types of vehicle formation motion were considered:fixed bidirectional communication cluster movement without a leader vehicle and fixed unidirec-tional communication cluster movement with a leader vehicle.The proposed method,unlike situa-tions where only the movement of formation vehicles towards the destination was controlled,ena-bled the vehicle formation to move towards the endpoint along the predetermined trajectory through the exchange of position information between adjacent vehicle nodes.To meet the practi-cal requirement of maintaining an ideal distance between vehicles,two virtual force models,name-ly traction force and topological force were introduced.Traction force primarily guides vehicles a-long the predetermined path to reach the destination,while topological force mainly maintains the connection topology among following vehicles.Simulation results indicate that the proposed method,compared to existing methods,effectively shortens the safe distance between vehicles and improves road utilization efficiency,demonstrating the good applicability.
information fusionoptimal information fusion Kalman filtervehicle formationa-daptive control
万方数据
维普
