Bottleneck areas on expressways plague the operational efficiency of entire road systems. In mixed traffic flow environments consisting of connected and autonomous vehicles (CAVs) and connected human-driven vehicles (CHVs), it is believed that road capacity can be improved to relieve traffic congestion in bottleneck areas by setting CAV dedicated lanes (CDLs) on expressways. Existing static CDL setup methods provide fixed exclusive right-of-way for CAVs but cannot accommodate dynamic changes in traffic demand. To address this issue, utilizing lane control signals and CAV active lane-changing technology, a cooperative method involving dynamic CAV dedicated lane control (CDLC) and active lane-changing control (LCC) in the bottleneck areas of expressways is proposed in this paper. First, a fundamental diagram of traffic flow with CDLs is established based on the microscopic car-following model of mixed traffic flow, which can be used to determine the conditional thresholds for setting the CDLs of multilane expressways. Second, an expressway traffic model with CDLs is established by improving the lane-level cell transmission model. Finally, cooperative control of dynamic CAV dedicated lanes and active lane changing (CDLLC) is proposed based on the model predictive control (MPC) framework for solving the congestion problem at expressway bottlenecks in a mixed driving environment. The simulation results show that the proposed CDLLC strategy can effectively reduce the total vehicle travel time and decrease the risk of congestion propagation at expressway bottlenecks when compared to the LCC-only strategy.

中文翻译：

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高速公路瓶颈区动态CAV专用车道与车辆主动换道协同控制

高速公路的瓶颈问题困扰着整个道路系统的运营效率。在由互联自动驾驶车辆（CAV）和互联人类驾驶车辆（CHV）组成的混合交通流环境中，相信可以通过在高速公路上设置CAV专用车道（CDL）来提高道路通行能力，缓解瓶颈地区的交通拥堵。现有的静态CDL设置方法为CAV提供固定的独占路权，但无法适应交通需求的动态变化。针对这一问题，本文利用车道控制信号和CAV主动换道技术，提出了一种在高速公路瓶颈区域动态CAV专用车道控制（CDLC）和主动换道控制（LCC）协同的方法。首先，基于混合交通流微观跟驰模型，建立了含CDL的交通流基本图，可用于确定多车道高速公路CDL设置的条件阈值。其次，通过改进车道级单元传输模型，建立了CDL的高速公路交通模型。最后，基于模型预测控制（MPC）框架，提出了动态CAV专用车道和主动变道协同控制（CDLLC），以解决混合驾驶环境下高速公路瓶颈的拥堵问题。仿真结果表明，与仅 LCC 策略相比，所提出的 CDLLC 策略可以有效减少车辆总行程时间，并降低高速公路瓶颈处拥堵传播的风险。