混合交通环境下普通交通使用公交专用道的车道使用策略
A Lane Usage Strategy for General Traffic Access on Bus Lanes under Mixed Traffic Environment
AI总结：
本文提出动态时空优先（DSTP）策略，在混合交通环境下利用信号配时和车辆数据识别公交专用道可用时空资源，并通过滚动时域优化通行权分配，在保证公交优先的同时提升整体交通效率并降低能耗与排放。
摘要：
允许普通交通使用公交专用道以提高利用率，同时确保公交优先的策略日益受到关注，尤其是在车联网（vehicle-to-everything）技术的支持下。在本研究中，我们提出了一种新颖的车道使用策略，称为动态时空优先（Dynamic Spatial-Temporal Priority，DSTP），以在混合交通环境中确保公交优先并优化公交专用道的使用。DSTP 利用动态方法识别车道中可用的时空资源，利用信号配时、道路信息和车辆数据。然后基于这些资源建立通行权分配优化模型，以确定哪些车辆可以进入公交专用道。该模型采用滚动时域方案动态执行，以适应时变的交通状况。数值研究验证了 DSTP 的优势，表明其能够保持公交优先、提高交通效率、减少燃料消耗并降低 CO2 排放，尤其是在高交通需求和公交集中到达的时段。
英文摘要：
The strategy of permitting general traffic to use the bus lane for improved utilization while ensuring bus priority has gained increasingly attention, particularly with the support of vehicle-to-everything technology. In this study, we propose a novel lane usage strategy called Dynamic Spatial-Temporal Priority (DSTP) to ensure bus priority and optimize bus lane usage in a mixed traffic environment. DSTP leverages dynamic methods to identify available spatial-temporal resources in the lane, utilizing signal timing, road information, and vehicle data. A Right-of-Way assignment optimization model is then developed based on these resources to determine which vehicles can enter the bus lane. The model is dynamically enacted using a rolling horizon scheme to accommodate time-varying traffic conditions. Numerical studies have validated the advantages of DSTP, showing maintained bus priority, improved traffic efficiency, reduced fuel consumption, and lower CO2 emissions, especially during periods of high traffic demand and concentrated bus arrivals.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
