Vehicle Path Replanning For Obstacle Avoidance Considering Driving Styles

The development of active and safe driving technology has been imperative. In this paper, we propose an obstacle avoidance path replanning method considering driving styles, the method can match current driving personalities in obstacle avoidance. Firstly, the driving data is collected in the experimental bench. Then it will be used for feature extraction and to build the drivers’ style classifier. The current drivers’ driving style parameters are obtained by identifying historical driving behavior data and classified into three typical categories. Secondly, an obstacle avoidance control strategy is given. In this strategy, the trajectory replanning layer is established above the trajectory tracking layer in MPC framework. The obstacle avoidance penalty functions and constraints are influenced by different driving styles. Finally, the effectiveness of obstacle avoidance strategy is verified.