EKF-RF融合的越野路面识别与纵向力自适应控制策略

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中图分类号：U463.6 文献标识码：A 文章编号：1003-8639（2025）10-0009-03

【Abstract】Aiming at the problem of deterioration of vehicle longitudinal dynamic control performance caused by variableroad surfaces inof-road environments，anadaptivecontrol strategy integrating Extended Kalman Filter （EKF）and Random Forest （RF）isproposed.This strategyadoptsamultimodal perceptionframework.Firstly，ituses the RFalgorithm to identify theroad surface type inreal time，and thentakes theresult as the prior knowledge of the EKF estimator toachievepreciseestimationof thepeakadhesioncoeffcientoftheroadsurface.Verification shows thatthis strategycaneffectivelyadapt todiffrentroadsurfaces.Itcansignificantlysuppress excessive whel slippageonbothhigh andlowadhesion roads，stabilize the slipratio within theoptimal range，which isconducive to improving the vehicle's acceleration and braking performance，shortening the braking distance，and enhancing the safetyof of-road driving.

【Key Words】road surface recognition;longitudinal force control;EKF；RF；adaptive control

0 引言

车辆纵向动力学控制对驾驶安全、舒适性及能耗经济性至关重要。（剩余3824字）