TY  - EJOU
AU  - Dang, Buwei 
AU  - Chen, Huanming 
AU  - Zhang, Heng 
AU  - Wang, Jixian 
AU  - Zhou, Jian 

TI  - Intelligent Vehicle Lane-Changing Strategy through Polynomial and Game Theory
T2  - Computers, Materials \& Continua

PY  - 2025
VL  - 83
IS  - 2
SN  - 1546-2226

AB  - This paper introduces a lane-changing strategy aimed at trajectory planning and tracking control for intelligent vehicles navigating complex driving environments. A fifth-degree polynomial is employed to generate a set of potential lane-changing trajectories in the Frenet coordinate system. These trajectories are evaluated using non-cooperative game theory, considering the interaction between the target vehicle and its surroundings. Models considering safety payoffs, speed payoffs, comfort payoffs, and aggressiveness are formulated to obtain a Nash equilibrium solution. This way, collision avoidance is ensured, and an optimal lane change trajectory is planned. Three game scenarios are discussed, and the optimal trajectories obtained are compared using the NGSIM dataset. Comparison of trajectory tracking effects by the model predictive control (MPC) and linear quadratic regulator (LQR). Finally, the left lane change, right lane change, and abort lane change operations are verified in the autonomous driving simulation platform. Simulation and experimental results show that the strategy can plan appropriate lane change trajectory and accomplish tracking in complex environments.
KW  - Lane-changing strategy; trajectory planning; game theory; tracking control; automated driving

DO  - 10.32604/cmc.2025.062653