The work zone with lane closure will be an active bottleneck due to vehicles’ mandatory lane-changing conflicts. The emerging Connected Autonomous Vehicle (CAV) technology provides opportunities for vehicle motion planning to improve traffic performance. However, the literature using CAV technology mainly focuses on single-lane lane-changing control in the merging area. The algorithm dealing with multi-lane lane-changing control is absent. In this paper, a simulation system with a lane-changing optimal strategy embedded for the multi-lane work zone is presented under the heterogeneous traffic flow. First, the road upstream of the work zone is divided into several segments, and an optimal multi-lane lane-changing algorithm is designed. It is recommended that CAVs, on the closure lane and the merged lane, change lanes on each segment to balance traffic distribution and minimize traffic delay. Second, to validate the algorithm proposed, a typical three-lane freeway with one-lane closed for the work zone is researched, and the simulation platform based on cellular automata is developed. Third, the advantages of multi-lane control strategies are studied and discussed in traffic efficiency improvement and collision risk reduction by comparing previous lane-changing control algorithms.

中文翻译：

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在多车道工作区优化联网和自动驾驶汽车的换道咨询

由于车辆的强制换道冲突，车道封闭的工作区将成为一个活跃的瓶颈。新兴的联网自动驾驶汽车 (CAV) 技术为车辆运动规划提供了机会，以提高交通性能。然而，使用CAV技术的文献主要集中在并道区域的单车道变道控制。缺少处理多车道变道控制的算法。本文提出了一种在异构交通流下嵌入多车道工作区换道优化策略的仿真系统。首先，将工作区上游的道路划分为若干段，并设计了一种最优的多车道变道算法。建议 CAV 在封闭车道和合并车道上，改变每个路段的车道以平衡交通分布并最大限度地减少交通延误。其次，为了验证所提出的算法，研究了典型的三车道高速公路工作区封闭单车道，并开发了基于元胞自动机的仿真平台。第三，通过比较以往的变道控制算法，研究和讨论了多车道控制策略在提高交通效率和降低碰撞风险方面的优势。