详情

Predicting Travel and Congestion in a Post-Pandemic America Phase 2: Implications for Urban Mobility

项目名称：	Predicting Travel and Congestion in a Post-Pandemic America Phase 2: Implications for Urban Mobility
摘要：	COVID-19 has affected travel behavior in many ways. Changes include a predictable reduction in overall travel, and even larger reductions in transit travel, carpooling, and travel on toll facilities. Now, two years into the pandemic we see signs of long-term impacts on the transportation system. What happens to travel and congestion once we return to a ‘new normal’ There is concern that transit ridership will not fully rebound due to concerns of close physical contact in public settings, and other alternatives for commuting and work locations. Will this change cause additional congestion in dense urban areas that previously relied on transit and therefore escalate equity issues for underserved sectors and populations? Also, toll road and managed lane traffic may not rebound causing both inefficient use of that road space and revenue shortfalls. This project will examine recent trends and attempt to predict travel in a ‘new normal’ (post-pandemic) environment utilizing behavioral economics, psychology, big data, and transportation expertise. Phase 1 identified the changes in travel and the potential recovery rates for the travel modes. Phase 2 integrates these changes in planning-level analysis to predict future traffic levels using real world scenarios. In Phase 2, researchers will use available data from large-scale origin-destination data sets along with findings from Phase 1 to better predict travel, congestion, farebox revenues and toll revenues in a ‘new normal’ along with impacts on travelers of different income levels and ethnicities.
状态：	Active
资金：	140197
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	National Institute for Congestion Reduction
项目负责人：	Zhang, Yu
执行机构：	Texas A&M Transportation Institute (TTI)
主要研究人员：	Burris, Mark
开始时间：	20220415
预计完成日期：	20230630
主题领域：	Highways；Planning and Forecasting；Public Transportation