为研究网联车辆借道城市公交专用道中所存在的车道利用率低和高交通需求下效果差等问题，本文提出一种新型借道公交专用道的动态控制逻辑与方法，不仅确保了公交优先，且可动态实时识别公交专用道中的剩余资源，并提升其时空资源利用效率。首先，定义公交专用道剩余时空资源识别方法，并基于车辆运动学特性和车辆驾驶类型，设计包含右转车辆的车辆行程时间计算方法;其次，根据预设的借道规则识别可借道车辆备选集，并构建路权分配优化模型，允许部分获得路权的网联人工车辆/自动车辆使用公交专用道，使公交专用道中的剩余时空资源得到有效利用;最后，以济南市某道路为例，利用SUMO(Simulation of Urban Mobility)软件进行仿真实验予以验证。结果表明，在交通需求、公交到达间隔和右转车辆比例等参数与实际道路完全一致的仿真实验中，相比于实际道路的传统公交专用道使用方法，以及既有文献中提出的"公交专用道间歇动态优先"方法，本文所提出的方法在优化目标上均有明显的改进。相比实际和文献中的控制方法，非右转车辆延误分别降低了30%与16%，右转车辆延误分别降低了24%与26%，且能确保公交优先通行。同时，参数敏感性分析显示，在不同交通需求、右转车辆比例、网联渗透率及公交到达间隔下，本文方法展现出更优的适用性。
Right-of-way Optimization and Dynamic Control Strategy for Connected Vehicles Accessing on Bus Lanes
A novel dynamic control logic and method for optimizing the Right-of-Way of connected vehicles utilizing urban bus lanes is proposed to address issues such as low lane utilization and poor performance under high traffic density.This approach ensures priority for buses and dynamically identifies and enhances the spatiotemporal resource utilization in bus lanes.A method for identifying the remaining spatiotemporal resources in bus lanes is defined,and a vehicle travel time calculation method is designed,taking into account the vehicle kinematics and driving behavior,including right-turning vehicles.Based on predefined rules for accessing bus lanes,a candidate set of vehicles eligible for lane borrowing is identified,and a road rights allocation optimization model is constructed,allowing selected connected human-driven/automated vehicles to utilize bus lanes.This enables effective utilization of the remaining spatiotemporal resources in bus lanes.The proposed method is validated through simulation experiments using a road in Jinan City,with parameters such as traffic flow intensity,bus arrival intervals,and proportion of right-turning vehicles matching the actual road conditions.The results demonstrate significant improvements in optimization objectives compared to traditional bus lane usage methods on the actual road and the"bus lane with intermittent dynamic priority"method proposed in the existing literature.Compared to the actual and literature-based control methods,the proposed method reduces delays for non-right-turning vehicles by 30%and 16%,and for right-turning vehicles by 24%and 26%,while ensuring bus priority.Moreover,the optimization effectiveness of the proposed method becomes more significant with increasing traffic intensity.
intelligent transportationbus prioritytraffic simulationdriving on bus laneconnected vehicle
万方数据
维普
