Abstract:

In view of that in vehicle lane change and cut-in scenes， autonomous vehicles are prone to frequent false-deceleration and false-avoidance， leading to the reduction in traffic capacity and occupant comfort， a decision-making and planning algorithm based on the dynamic gaming between ego vehicle and adjacent vehicle is proposed. In the behavior decision-making layer， according to the conflicting relationship between ego vehicle and adjacent vehicle in the cut-in scene， the motion model of the whole system is established by combining the motion equations of relevant vehicles， and the cut-in game model considering the state of adjacent vehicle is constructed， to design the gain function of safety and rid comfort， conduct driving behavior game， and output behavior decision results. In the trajectory planning layer， the constraints for obstacle avoidance is established based on vehicle spacing， and the vehicle dynamics constraints are defined by the variable curvature of sigmoid function trajectory and the time component of speed tangent vector. Meanwhile， with concurrent considerations of the requirements of driving habits and ride comfort in weighted gain mode， a mathematical model of trajectory planning is established to solve out the motion trajectory， meeting the requirements of the upper-level game decision. The results of Carsim-Simulink co-simulation show that under different initial conditions， the ego vehicle and cut-in adjacent vehicle can conduct various forms of rational interactive decision-making， accurately complete the motion planning task in cut-in scene. In addition， the vehicles can accurately follow the output trajectory， more conforming the common driving habits and enhancing vehicle comfort.

Key words: autonomous vehicles, cut-in scenes, dynamic game, motion planning