Lane Keeping Control Strategy for Box Type Commercial Vehicles Based on Vehicle Rollover Risk Control

Commercial vehicles with full loads often exhibit frequent load variations and slow steering responses during complex road driving, while traditional control methods fail to dynamically track rollover risks on overloaded commercial vehicles. Although Active Disturbance Rejection Control (ADRC) demonstrates strong adaptability and system robustness, its empirical parameters show poor alignment with real-world vehicle data. To address this, this paper proposes a lane-keeping control strategy for box-type commercial vehicles based on rollover risk regulation. The system employs the Cooperative Particle Swarm Optimization (CPPSO) algorithm to tune rollover risk parameters and utilizes ADRC for steering control, significantly enhancing both precision and stability. TruckSim simulation results demonstrate that compared with traditional ADRC and Model Predictive Control (MPC), this approach reduces rollover risks caused by center-of-gravity shifts and enables rapid, precise correction of lane deviations in box-type commercial vehicles.