Abstract: The partial closure of bidirectional two-lane work zones often creates bottleneck delays, reducing road capacity. In order to improve the traffic efficiency of the two-way double-lane half-closed operation area, alleviate the vehicle delay on the road section, and give full play to the control advantages of intelligent connected vehicles (ICV), a speed guidance model is designed based on the improved TD3 algorithm, which enables ICV to pass through the signal port at high speed, with low delay and no stop. First, a signal timing method for bidirectional two-lane work zones is designed using the Webster model. Second, technical improvements to the TD3 algorithm are implemented: hybrid weighted averaging is introduced to mitigate Q-value overestimation bias, and a StepLR scheduler is integrated to optimize learning rate sensitivity. Third, the model’s state pace, action space, and reward function are systematically formulated. Numerical simulations demonstrated that the proposed model effectively guides most ICVs to arrive at intersections during green phases and execute alternating lane maneuvers under mixed traffic flows with varying ICV market penetration rates and traffic volumes. This work provides a novel framework for optimizing traffic operations in dual-lane work zones under mixed ICV-human driving conditions.

Key words: bidirectional two-lane road; alternatively passing work zone; reinforcement learning; mixed autonomy; ICV

摘要： 双向双车道半幅封闭公路作业易形成瓶颈延误区，降低道路可用通行能力。为提高双 向双车道半幅封闭作业区通行效率、缓解路段车辆延误，充分发挥智能网联汽车（ICV）控制 优势，基于改进 TD3 算法设计了一种引导 ICV 能够以高速度、低延误且不停车地通过信号口 的车速引导模型。首先，根据 Webster 模型给出双向双车道作业路段信号配时方法；然后， 针对 TD3 算法，使用混合加权平均值缓解 Q 值保守估计，并通过 StepLR 机制优化学习率敏 感问题；最后，给出了模型设计的状态空间、动作空间和奖励函数。数值仿真检验了模型的 效果，结果表明，所提模型在不同流量及不同 ICV 市场渗透率的混行交通流下，能引导大部 分 ICV 在绿灯时到达信号口并通过交替通行车道，可以提高道路平均驾驶速度、降低道路平 均停车延误。该模型为混行交通背景下双车道公路作业路段的通行优化提供了思路。

关键词: 双向双车道道路；半幅封闭作业区；强化学习；混行交通流；ICV