RAPID: Transit Network Disruption, Service Reliability, and Travel Behavior
RAPID:交通网络中断、服务可靠性和出行行为
基本信息
- 批准号:1649189
- 负责人:
- 金额:$ 5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-08-01 至 2017-10-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Major transit disruptions have become more frequent due to increasing maintenance needs for an aging infrastructure, system failures, and disasters. Both transportation agencies and travelers need better information to prepare for such events. Considering the significant public distress caused by such events, the objectives of this research are crucial to the well-being of our society. Understanding travelers' behavioral responses over time are essential to effective planning and management of multimodal transportation systems for infrastructure maintenance and disaster response. This Rapid Response Research (RAPID) project will collect unique and perishible data on system performance and travel behavior before, during and after each of the 15 Metro service disruption events (the SafeTrack project) in the Washington D.C. metropolitan area scheduled between June 2016 and March 2017. The analysis will advance our understanding on the impact of major transit service disruptions on a multi-modal transportation system, yielding insights on how to optimize the planning and execution of maintenance events. The field of transportation systems analysis will benefit from the detailed travel behavior adjustment and system-level re-equilibration observations collected from this project. Mass transit may be the only option for many low-income or disadvantaged travelers, and this research will also reveal members of these groups respond to transit service disruptions.The objectives of the research are to 1) collect unique system performance and travel behavior data sets before, during and after each of the 15 Metro service disruption events using state-of-the-art longitudinal behavior data collection methods; 2) test hypotheses on the impact of major transit service disruptions on a multi-modal transportation system; 3) advance understanding of human behavioral responses and system re-equilibration after such disruptions; and 4) systematically discover planning and operations strategies that can minimize the impact of major transit service shutdowns based on this improved understanding of travel behavior. This project will be the first comprehensive study on transit network disruption of this magnitude with complete before-and-after travel behavior and system performance data. Longitudinal travel behavior data produced from this project will also stimulate future research on transit network reliability, resiliency, and incident response. This project will fill a major gap in the literature on multi-modal, multi-dimensional travel behavioral responses to major transit network disruptions. This will also be a first research effort that explores the transportation system re-equilibration (or lack of it) after major transit network disruptions. Understanding how travelers respond to transit service disruptions is a critically theoretical prerequisite toward developing and implementing effective strategies (e.g., how to optimally deploy the reserved bus fleet) that minimize system impact and improve transit system reliability and resiliency.
由于老化的基础设施、系统故障和灾害的维护需求增加,重大交通中断变得更加频繁。运输机构和旅行者都需要更好的信息来为此类事件做准备。考虑到这类事件造成的重大公共痛苦,这项研究的目标对我们社会的福祉至关重要。了解旅客的行为反应随着时间的推移是必不可少的有效规划和管理的多式联运系统的基础设施维护和灾害响应。该快速响应研究(RAPID)项目将在2016年6月至2017年3月期间计划在华盛顿大都市区发生的15起地铁服务中断事件(SafeTrack项目)之前、期间和之后收集有关系统性能和出行行为的独特且易损坏的数据。该分析将促进我们对主要运输服务中断对多式联运系统影响的理解,从而了解如何优化维护事件的规划和执行。交通系统分析领域将受益于本项目收集的详细的出行行为调整和系统级再平衡观察。本研究的主要目的是:1)采用最先进的纵向行为数据收集方法,收集15次地铁服务中断事件发生前、发生时和发生后的系统性能和出行行为数据集; 2)测试假设的影响,主要的公共交通服务中断的多式联运系统; 3)提前了解人类行为的反应和系统的重新平衡后,这种中断;和4)系统地发现规划和运营策略,可以最大限度地减少影响的主要公共交通服务关闭的基础上,这种改进的理解旅行行为。该项目将是第一个对这种规模的交通网络中断进行全面研究的项目,包括完整的出行行为和系统性能数据。从这个项目产生的纵向旅行行为数据也将刺激未来的研究交通网络的可靠性,弹性和事件响应。 该项目将填补文献中的一个主要空白,多模式,多维度的旅行行为的反应,主要的交通网络中断。这也将是第一个研究工作,探讨交通系统重新平衡(或缺乏它)后,主要的交通网络中断。了解旅客如何应对交通服务中断是制定和实施有效战略的重要理论前提(例如,如何最佳地部署预留的公交车队),以最大限度地减少系统影响并提高交通系统的可靠性和弹性。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Travel Behavior Reactions to Transit Service Disruptions: Study of Metro SafeTrack Projects in Washington, D.C.
出行行为对交通服务中断的反应:华盛顿特区地铁 SafeTrack 项目研究
- DOI:10.3141/2649-09
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Zhu, Shanjiang;Masud, Hamza;Xiong, Chenfeng;Yang, Zhuo;Pan, Yixuan;Zhang, Lei
- 通讯作者:Zhang, Lei
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Shanjiang Zhu其他文献
Enhancing Transportation Education Through On-Line Simulation Using an Agent-Based Demand and Assignment Model
使用基于代理的需求和分配模型通过在线模拟加强交通教育
- DOI:
10.1061/(asce)ei.1943-5541.0000038 - 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
Shanjiang Zhu;F. Xie;D. Levinson - 通讯作者:
D. Levinson
Integrating an Agent-Based Travel Behavior Model with Large-Scale Microscopic Traffic Simulation for Corridor-Level and Sub-Area Transportation Operations and Planning Applications
将基于代理的出行行为模型与大规模微观交通仿真相结合,用于走廊级和分区交通运营和规划应用
- DOI:
10.1061/9780784412442.357 - 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Lei Zhang;G. Chang;Shanjiang Zhu;Chenfeng Xiong;Longyuan Du;Mostafa Mollanejad;N. Hopper;S. Mahapatra - 通讯作者:
S. Mahapatra
The Hierarchy of Roads, the Locality of Traffic, and Governance
道路的等级、交通的局部性和治理
- DOI:
10.2139/ssrn.1736216 - 发表时间:
2010 - 期刊:
- 影响因子:0
- 作者:
D. Levinson;Shanjiang Zhu - 通讯作者:
Shanjiang Zhu
Improving Inventory of and Investment in Bicycle and Pedestrian Facilities Through Targeted Public Outreach
通过有针对性的公众宣传改善自行车和行人设施的库存和投资
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Shanjiang Zhu - 通讯作者:
Shanjiang Zhu
The roads taken: theory and evidence on route choice in the wake of the I-35W Mississippi River bridge collapse and reconstruction.
- DOI:
- 发表时间:
2010-09 - 期刊:
- 影响因子:0
- 作者:
Shanjiang Zhu - 通讯作者:
Shanjiang Zhu
Shanjiang Zhu的其他文献
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{{ truncateString('Shanjiang Zhu', 18)}}的其他基金
RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area
RAPID:协作研究:2024 年 3 月 26 日 DC-马里兰-弗吉尼亚地区 Francis Scott Key 大桥倒塌事故后果的多方面数据收集
- 批准号:
2427233 - 财政年份:2024
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
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