面向混合编队领航CAVs的博弈换道决策模型

Game-based Lane-changing Decision Model for Leading CAVs in Mixed Platoons

以CAVs为领航车的混合编队有助于实现更顺畅和安全的道路交通,但当前研究较少关注于具有多车道分布特征的混合编队形成问题。对此,本文提出了一种面向混合编队领航CAVs的博弈换道决策模型。该模型建立数学优化与博弈论相结合的换道决策机制,建立以最小化CAVs换道次数为目标的领航CAVs目标车道初始化流程,并依据CAVs博弈换道收益,更新领航CAVs目标车道,实现混合编队多车道分布。同时,基于博弈论建立CAVs与HDVs非合作博弈矩阵,综合考虑换道效率和安全性,分别设计时间和安全收益函数,量化CAVs换道风险,并使用交通软件SUMO建立微观仿真。实验结果表明,与基准模型相比,本文提出的博弈换道策略在不同混合交通量下混合编队完成率维持在97%以上,每组领航CAVs换道时间平均缩短约40%,每组领航CAV换道次数保持较低水平。

The inclusion of connected and automated vehicles as leading vehicles in mixed platoons has the potential to achieve smoother and safer road traffic,but current research seldom focuses on the formation of mixed platoons with multi-lane distribution characteristics.To address this problem,a game-based lane-changing decision model is proposed for leading CAVs in mixed platoons.The model establishes a lane-changing decision mechanism that combines optimized and game-based approaches.It initiates a leading CAVs'target lane initialization process with the objective of minimizing the number of CAVs lane changes.Based on the payoff from CAVs'game-based lane-changing,it updates the target lanes of leading CAVs to achieve multi-lane distribution of mixed platoons.Furthermore,a non-cooperative game matrix between CAVs and HDVs is established based on game theory,considering both lane-changing efficiency and safety.Time and safety payoff functions are designed to quantify the lane-changing risk of CAVs.Microscopic simulations are conducted using the traffic software SUMO.Experimental results demonstrate that compared to the baseline model,the proposed game-based lanechanging strategy maintains a mixed formation completion rate of over 97%under different mixed traffic volumes,with an average reduction of about 40%in the lane-changing time for each group of leading CAVs,while keeping the lane-changing frequency of each group of leading CAVs at a low level.