RAPID: Impact of Highway Infrastructure Failures on Transit Usage: The Case of the 11 June 2023 I-95 Bridge Collapse in Philadelphia, Pennsylvania

这项快速反应研究拨款(RAPID)奖将收集有关交通流模式、过境乘客、个人出行轨迹和出行行为的时间敏感数据，这些数据源于最近宾夕法尼亚州费城一座北行I-95州际公路桥的坍塌。除了I-95大桥坍塌对日常生活造成的破坏外，它还有可能带来个人行为的变化，促进可持续交通，特别是过境交通的使用。桥梁倒塌前、桥梁重建过程中以及桥梁完全修复后的高分辨率数据对于理解和利用这一潜力是必不可少的。然而，这样全面的数据还没有收集到与以前的高速公路基础设施故障相关联。由于桥梁修复预计将在几个月内完成，费城的交通模式已经开始改变，在重要信息丢失之前启动数据收集工作是当务之急。该项目旨在通过多尺度和多利益攸关方的数据收集方法来填补这一关键的数据缺口。生成的数据集将成为研究界和其他人调查高速公路基础设施故障对交通使用的影响的宝贵资源。虽然该项目的重点是费城最近发生的一起高速公路桥坍塌和交通使用情况，但这些数据有可能得出关于人为或自然灾害导致的被迫出行行为过程的概括性见解。该项目涉及多个范围的数据收集，通过与现有合作伙伴的合作，包括：(I)通过与费城街道部门的合作收集整个城市受影响地区道路的链路级交通流量数据；(Ii)通过与宾夕法尼亚州东南部运输局(SEPTA)的合作收集的路线级交通乘客数据；(Iii)使用Gravy Analytics从移动设备收集的GPS数据得出的个人旅行轨迹；以及(Iv)综合旅行行为调查提供的有关个人旅行行为、态度和社会人口学特征的信息。一种包容性和成本效益高的事件触发抽样方法将克服与数据收集有关的统计挑战。这种方法将确保在桥梁重建过程中从所有类型的社区和人口群体收集数据，方法是对关键的离散时间点进行采样，在这些时间点上，从低成本的聚合交通流量测量中观察到实质性的行为变化。生成的数据集将被转移并存储在德雷克塞尔大学的计算设施中，并与更广泛的研究社区和公众共享。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Grant for Rapid Response Research (RAPID) award will collect time-sensitive data on traffic flow patterns, transit ridership, individual travel trajectories, and travel behavior stemming from the recent collapse of a northbound I-95 interstate highway bridge in Philadelphia, Pennsylvania. In addition to the disruptive nature of the I-95 bridge collapse on daily lives, it also has the potential to bring about individual behavioral changes that promote sustainable transportation, particularly transit, usage. High-resolution data before the bridge collapse, during the bridge reconstruction process, and after the bridge is fully repaired is essential for understanding and harnessing this potential. However, such comprehensive data has not been collected in assocation with previous highway infrastructure failures. As the bridge repair is expected to be completed within months and traffic patterns in Philadelphia have already started to change, it is urgent to initiate data collection efforts before important information is lost. This project aims to fill this critical data gap through a multi-scale and multi-stakeholder data collection approach. The generated datasets will be a valuable resource for the research community and others to investigate the impact of highway infrastructure failures on transit usage. While the focus of this project is on a recent highway bridge collapse and transit use in Philadelphia, the data has the potential to derive generalizable insights about forced travel behavioral processes resulting from man-made or natural disasters.This project involves multiple scales of data collection by working with various stakeholders building on existing partnerships, including: (i) link-level traffic flow data from roads throughout the impacted region of the city collected via collaborations with the Philadelphia Streets Department; (ii) route-level transit ridership data collected via collaborations with the Southeastern Pennsylvania Transportation Authority (SEPTA); (iii) individual-level travel trajectories using GPS data from mobile devices collected using Gravy Analytics; and (iv) information on individual travel behavior, attitudes, and sociodemographic characteristics from a comprehensive travel behavior survey. An inclusive and cost-effective event-triggered sampling approach will overcome statistical challenges related to data collection. This approach will ensure that data are collected from all types of communities and population groups throughout the bridge reconstruction process by sampling critical discrete time points where substantial behavioral changes are observed from low-cost, aggregated traffic flow measures. The generated datasets will be transferred to and stored at computing facilities at Drexel University and shared with the broader research community and the public.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.