Developing Highway Capacity Manual Capacity Adjustment Factors for Connected and Automated Traffic on Freeway Segments
Developing Highway Capacity Manual Capacity Adjustment Factors for Connected and Automated Traffic on Freeway Segments
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DOI：
10.1177/0361198120934797
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发表时间：
2020-07
影响因子：
1.7
通讯作者：
Adekunle Adebisi;Yan Liu;Bastian Schroeder;Jiaqi Ma;Burak Cesme;A. Jia;Abby Morgan
中科院分区：
文献类型：
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作者：
Adekunle Adebisi;Yan Liu;Bastian Schroeder;Jiaqi Ma;Burak Cesme;A. Jia;Abby Morgan
互联和自动驾驶汽车（CAV）无疑将在未来改变交通系统的许多方面。与此同时，运输机构必须作出投资和政策决定，以满足运输系统的未来需求。这项研究提供了急需的指导机构规划层面的能力，在CAV的未来和量化公路通行能力手册（HCM）的能力作为CAV的渗透率和车辆行为，如汽车跟随，变道，并合并的函数。由于CAV实施政策的许多不确定性，研究考虑了许多情况，包括参数（包括CAV间隙/车头时距设置），道路几何形状和交通特征的变化。更具体地说，本研究认为，基本的高速公路，高速公路合并，高速公路交织段中的各种模拟方案进行评估，使用两个主要的CAV应用：合作自适应巡航控制和先进的合并。收集微观交通模拟数据，以开发CAV容量调整因子。结果表明，存在的CAV在交通流中可以显着提高道路容量（在某些情况下高达35%至40%），不仅在基本的高速公路，但也合并和交织段，随着CAV市场渗透率的增加。人类驾驶员的基线交通行为也会影响容量效益，特别是在CAV市场渗透率较低的情况下。最后，本研究结果的HCM实施能力调整因素和相应的回归模型的表。
Connected and automated vehicles (CAVs) will undoubtedly transform many aspects of transportation systems in the future. In the meantime, transportation agencies must make investment and policy decisions to address the future needs of the transportation system. This research provides much-needed guidance for agencies about planning-level capacities in a CAV future and quantify Highway Capacity Manual (HCM) capacities as a function of CAV penetration rates and vehicle behaviors such as car-following, lane change, and merge. As a result of numerous uncertainties on CAV implementation policies, the study considers many scenarios including variations in parameters (including CAV gap/headway settings), roadway geometry, and traffic characteristics. More specifically, this study considers basic freeway, freeway merge, and freeway weaving segments in which various simulation scenarios are evaluated using two major CAV applications: cooperative adaptive cruise control and advanced merging. Data from microscopic traffic simulation are collected to develop capacity adjustment factors for CAVs. Results show that the existence of CAVs in the traffic stream can significantly enhance the roadway capacity (by as much as 35% to 40% under certain cases), not only on basic freeways but also on merge and weaving segments, as the CAV market penetration rate increases. The human driver behavior of baseline traffic also affects the capacity benefits, particularly at lower CAV market penetration rates. Finally, tables of capacity adjustment factors and corresponding regression models are developed for HCM implementation of the results of this study.