Vehicle-to-infrastructure (V2I) technology enables information interaction between vehicles and among vehicles and infrastructure, significantly enhancing the efficiency of lane-changing processes and stabilising traffic flow. Current research primarily focuses on single lane-changing events in fixed micro-level scenarios or studies involving small-scale vehicle fleets, neglecting the randomness of lane-changing vehicle arrivals and potential conflicts during lane-changing. This paper proposes a lane-changing decision model based on potential conflict analysis, specifically tailored to mandatory lane-changing requirements in high-density traffic conditions. The model comprises sub-models for lane-changing decision triggering, influence range calculation and lane-changing priority determination, capable of dynamically adjusting the lane-changing sequence, mitigating lane-changing conflicts, and improving driving safety and traffic efficiency. Simulation experiments indicate that, when compared to lane-changing patterns in real-world traffic scenarios, this model reduces travel time by 23.30%, delays by 21.95% and the number of stops by 23.84%, thereby providing a novel approach for lane-changing decision-making and control in V2I environments.
Fang et al. (Tue,) studied this question.