详情

Selecting the Most Feasible Construction Phasing Plans for Urban Highway Rehabilitation

项目名称：	Selecting the Most Feasible Construction Phasing Plans for Urban Highway Rehabilitation
摘要：	Approximately one-fifth of the U.S. highway system is under construction, resulting in more than 3,000 construction work zones (CWZ) across cities and states. Since CWZ disrupt traffic flow, daily commuters, and business interests are facing a pressing need to improve mobility around work zones. The primary problem is a lack of standardized methods and analytical tools for proactively assessing the level of mobility disruption that is caused by a CWZ. To tackle this immediate concern, the main objective of this study is to create and test a novel data-driven decision-support model that predicts the level of mobility disruption of a CWZ under arbitrary and user-defined construction and lane closure alternatives. This aim will be achieved by conducting a three-stage methodology that articulates a new spatiotemporal big-data modeling framework where the level of mobility disruption is assessed, and the model’s prediction accuracy fused from a machine-learning algorithm is validated. The central hypothesis is that use of machine-learning techniques will inform the development of reliable mobility indicators for use in selecting the most feasible construction phasing plans. The proposed decision-support system will provide a theoretical basis for comparatively analyzing what-if lane closure scenarios of critical highway projects in urban corridors.
状态：	Completed
资金：	150000
资助组织：	Office of the Assistant Secretary for Research and Technology
项目负责人：	Melson, Christopher
执行机构：	Texas A&M University, College Station
开始时间：	20190815
预计完成日期：	20210215
主题领域：	Construction；Data and Information Technology；Highways；Maintenance and Preservation；Operations and Traffic Management；Planning and Forecasting