Interactive Decision-making and Trajectory Planning of Intelligent Vehicles in Lane-changing Scenarios

doi:10.3901/JME.2025.10.322

Abstract

Abstract: A game-based interactive decision-making and trajectory planning algorithm is proposed to address the problem that overly conservative or aggressive lane-changing behaviors will be exhibited by intelligent vehicles in complex dynamic scenarios due to lake of effective interaction with surrounding vehicles. A human-driven vehicle model is established based on driver operation characteristics and driving styles, by utilizing Bayesian inference algorithms to assess the conservativeness of driving behavior and enabling real-time prediction of interactive vehicle maneuvering actions. On this basis, a decision-making and planning model for lane-changing maneuvers of the ego-vehicle is developed. Initially, lane-changing endpoints are sampled to generate candidate lane-changing paths. Subsequently, an ego-vehicle reward function is constructed to evaluate lane-changing strategies during the game process. Finally, a dynamic programming algorithm is designed, which incorporates the idea of leader-follower games and fully considers the generation of optimal strategies and trajectories in interactive gaming scenarios. The human-in-the-loop simulation platform, built with Matlab/Simulink and PreScan, is utilized to validate and analyze multiple lane-changing scenarios. The results indicate that the algorithm effectively interacts with surrounding vehicles in complex and dynamic lane-changing scenarios, demonstrating rational behavioral decisions and producing trajectories that prioritize both safety and smoothness.

Key words: intelligent vehicles, lane changing interaction, decision planning, master-slave game, dynamic programming

CLC Number:

U467

HU Jie, ZHAO Wenlong, ZHENG Jiachen, ZHOU Silong, ZHANG Zhiling, WU Zuowei, CHEN Jiaji. Interactive Decision-making and Trajectory Planning of Intelligent Vehicles in Lane-changing Scenarios[J]. Journal of Mechanical Engineering, 2025, 61(10): 322-334.

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