Open Access

ARTICLE

Intelligent Vehicle Lane-Changing Strategy through Polynomial and Game Theory

Buwei Dang, Huanming Chen^*, Heng Zhang, Jixian Wang, Jian Zhou

College of Mechanical and Electrical Engineering, Qingdao University, Qingdao, 266071, China

* Corresponding Author: Huanming Chen. Email:

(This article belongs to the Special Issue: Intelligent Manufacturing, Robotics and Control Engineering)

Computers, Materials & Continua 2025, 83(2), 2003-2023. https://doi.org/10.32604/cmc.2025.062653

Received 24 December 2024; Accepted 03 February 2025; Issue published 16 April 2025

Abstract

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.

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Keywords

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