评估主要交通中断的影响-旧金山湾区案例研究

IF 4.3 Q2 TRANSPORTATION
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引用次数: 0

摘要

交通网络的制约因素是灾难规划的基础。如果能够评估大型交通事故背景下此类网络的突发动态,就能为交通管理策略的设计提供参考。2019 年 2 月 7 日,位于旧金山湾区的里士满-圣拉斐尔大桥由于上层桥面结构性故障,不得不突然关闭 9 个多小时,该大桥连接多个城市,每天运载车辆超过 10 万辆。这一事故对该地区造成了重大影响,因为通常情况下交通都会中断,旅客需要寻找其他路线绕行。在本研究中,我们以里士满-圣拉斐尔大桥关闭为案例,展示了对重大网络中断进行大规模交通影响评估的能力。利用高性能并行离散事件交通模拟,我们评估了大桥关闭在区域系统和城市层面造成的交通影响。据我们的模型估计,由于大桥的关闭,该地区额外增加了 14000 个车时的延误和 600000 英里的行车距离。该事件影响了超过 55000 次出行;某些出行的延误时间增加了 46 分钟,行程增加了 26 英里。旧金山、瓦莱约和圣拉斐尔附近街道的交通流量中值分别增加了 30%、22% 和 13%。结果表明,这些城市的地方道路为分散交通流量提供了额外的适应能力。通过使用动态改道能力、完整的道路网络和全面的需求对关键网络中断进行大规模建模,我们对这一特定事件的响应动态提供了宝贵的见解。在此过程中,我们证明了此类区域分析对事件和灾难规划的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the impacts of major transportation disruptions – San Francisco Bay Area case study
The constraints of transportation networks are fundamental to disaster planning. Having the capability of evaluating the emergent dynamics of such networks in the context of large traffic incidents can inform the design of traffic management strategies. On February 7, 2019, the Richmond-San Rafael Bridge in the San Francisco Bay Area, connecting multiple cities and carrying over 100 000 vehicles daily, had to be suddenly closed for over 9 hours due to a structural failure of its upper deck. This incident caused major disruptions in the region as the typical traffic was interrupted and detoured as travelers found alternate routes. In this study, we demonstrate the capability of large-scale traffic impact assessments of major network disruptions using the Richmond-San Rafael Bridge closure as a case study. Using a high-performance, parallel-discrete event traffic simulation, we assess the traffic impacts resulting from the bridge closure at both the regional system and city levels. Our model estimates that the region incurred an additional 14 000 vehicle hours of delay and 600 000 vehicle miles in distance due to the bridge closure. The incident affected over 55 000 trips; certain trips experienced an increase of 46 min in delay and 26 miles in travel distance. The median traffic volume on neighborhood streets in San Francisco, Vallejo, and San Rafael increased by 30%, 22%, and 13%, respectively. The results suggest that the cities’ local roads provided the additional adaptive capacity to disperse the traffic. With large-scale modeling of a critical network disruption using dynamic rerouting capability, complete road network, and full demand, we provide valuable insights into the response dynamics of this specific event. In doing so, the value of such regional analyses to incident and disaster planning is demonstrated.
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来源期刊
International Journal of Transportation Science and Technology
International Journal of Transportation Science and Technology Engineering-Civil and Structural Engineering
CiteScore
7.20
自引率
0.00%
发文量
105
审稿时长
88 days
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