Stochastic non‐cooperative game for safety control of shared control vehicle in uncertain environments

Abstract

Abstract There are great challenges in the driving of human–machine shared control vehicles (HSCVs) in uncertain environments. Aiming at solving the collision avoidance problem of HSCV considering the uncertainty of surrounding vehicles (SVs), a human–machine cooperative control method for collision avoidance based on stochastic non‐cooperative game (SNCG) is proposed. This method realizes the safe driving of HSCV combined with the prediction of surrounding environment and constructs the interaction model between a driver and an automation system based on the game theory. Firstly, a vehicle–driver coupling model with driver's lateral and longitudinal operation characteristics is established. Next, utilizing the prediction equation, the prediction of the SV motion considering uncertainty is realized. Then, the safety constraints of HSCV are established by considering the chance constraints and the saturation characteristics of the actuators. Finally, based on the distributed stochastic model predictive control (DSMPC) method, the coupled optimization problem with chance constraints is constructed. To solve the coupled optimization problem with chance constraints, the idea of Nash equilibrium solution and the method of chance constraints tightening is adopted. The simulation results illustrate that the proposed method ensures the safe driving of HSCV under uncertain environments and realize the cooperative control between the automation system and the driver.

Keywords

• intelligent control
• road vehicles
• vehicles