考虑CAV专用道汇入需求的高速公路交织区集成控制策略

An integrated control strategy for freeway weaving area considering CAV dedicated lanemerging demand

关键词:  智能交通  交通管控  深度强化学习  高速公路交织区  CAV专用道  混合交通流

Key words:  intelligent transportation  traffic control  deep reinforcement learning  freeway weaving area  CAV dedicated lane  mixed traffic flow

摘要:

为提升高速公路通行效率,优化网联自动驾驶车辆（connected and autonomous vehicle,CAV）专用道设置条件下的交织区时空资源配置,以保证CAV高效安全汇入主线专用道,提出了一种基于深度强化学习的交织区集成控制策略。以主线三车道高速公路为研究对象,并设置内侧车道为CAV专用道,设计了充分考虑CAV专用道汇入需求同时兼顾主线通行效率和匝道排队长度的多目标奖励函数,利用深度确定性策略梯度（deep deterministic policy gradient,DDPG）算法实现包括入口匝道信号控制、主线车道级可变限速以及CAV车队间隙调整的集成控制策略,最后使用SUMO和Python搭建高速公路交织区仿真场景,验证所提集成控制策略的有效性。研究结果表明:CAV渗透率为30%时,在低、中、高不同水平交通需求场景下,对比无控制情况集成控制策略可使CAV汇入专用道的纵向位置有所提前,CAV汇入专用道成功率分别增加了19.34%、22.86%、25.55%；此外,车辆平均行程时间也分别降低了5.42%、17.41%、20.65%。所提出的交织区集成控制策略效果显著,不仅实现了CAV汇入专用道的有效引导,还提升了主线的通行效率及运行安全,为改善CAV专用道设置条件下高速公路交织区交通运行状况提供了理论依据和技术参考。

Abstract:

To improve freeway operational efficiency and optimize spatiotemporal resource allocation in weaving area under the setting of dedicated lane for connected and autonomous vehicles (CAVs), a deep reinforcement learning-based integrated control strategy is proposed. This strategy aims to ensure the efficient and safe merging of CAVs into the dedicated lane. The research focuses on a three-lane freeway configuration, with the innermost lane designated for CAVs. A multi-objective reward function is developed to address the dedicated lane merging demand of CAVs while simultaneously considering the efficiency of mainline traffic and the length of ramp queue. The deep deterministic policy gradient (DDPG) algorithm is employed to implement the integrated control strategy, which encompasses entrance ramp signal control, variable speed limit at the lane level, and adjustment to the gaps between CAV platoon. A simulation environment for the freeway weaving area is designed using SUMO and Python to assess the effectiveness of the proposed control strategy. The results demonstrate that, with a CAV penetration rate of 30%, the integrated control strategy advances the longitudinal positioning of CAVs entering the dedicated lane, merging success rate increases of 19.34%, 22.86%, and 25.55% under low, medium, and high traffic demand scenarios, respectively. Additionally, average vehicle travel time is reduced by 5.42%, 17.41%, and 20.65% under the same conditions. The proposed integrated control strategy for weaving area demonstrates significant effectiveness by not only achieving effective guidance for CAV merging dedicated lane but also enhancing the traffic efficiency and operational safety of the mainline, providing a theoretical basis and technical reference for optimizing the traffic operation in weaving areas of freeway under CAV dedicated lane conditions.