Adaptive Coordinated Control of Cornering Steering and Speed for Intelligent Vehicles
Addressing the issues of low trajectory tracking accuracy and poor steering stability when vehicles are driving at high speeds on curves,a set of longitudinal-lateral coupled control algorithms based on the vehicle ki-nematics model is proposed.This employs a predictive desired front wheel angle calculation method different from pure pursuit,and uses lateral acceleration constraints for longitudinal control,while also designing a predictive two-stage deceleration control algorithm for high-speed conditions to achieve combined steering and speed con-trol.To improve the adaptability of the algorithm to different conditions,a Sparrow Search Algorithm is used to op-timize the predictive time based on road curvature and vehicle speed.The control effects under different curvature bends are verified through joint simulation based on Simulink and Prescan.The results show that the predictive longitudinal-lateral coupled control algorithm,optimized using the Sparrow Search Algorithm,can significantly improve trajectory tracking precision and steering smoothness,and the algorithm is highly adaptable to different road curvature scenarios.A comparison of simulation results with driving simulation data indicates that the algo-rithm closely matches the natural human driving style.
intelligent vehiclecurvy trajectory trackingsparrow search algorithmsteering and speed coordina-ted control algorithm
NETL
NSTL
万方数据
维普
