Modeling Human Vehicle Driving by Model Predictive Online Optimization

• DOI: 10.1076/vesd.35.1.19.5614
• Publication Date: 2003-02-23T06:50:05Z
• Authors: G�nther Prokop
• Keywords: Model Predictive Control; Sequential quadratic programming

Abstract A driver model is designed which relates the driver's action to his perception, driving experience, and preferences over a wide range of possible traffic situations. The basic idea behind work that human uses sensory perception expert knowledge predict vehicle's future behavior for next few seconds (prediction model). At certain sampling rate motion optimized using this prediction model, in order meet objectives. tries follow optimal compensatory controller. Based on hypothesis, vehicle modeled by hierarchical repetitive nonlinear optimization employed plan (trajectory planning task), an SQP algorithm. This combined with PID tracking control minimize its deviations. trajectory scheme experimentally verified undisturbed situations employing various objectives, namely ride comfort, lane keeping, minimized speed variation. then applied study path during curve negotiation under preferences. highly dynamic avoidance maneuver (standardized ISO double change) simulated investigate overall stability closed loop vehicle/driver system.