详情

Use of Crowdsource Passive Data to Evaluate Effectiveness of Access Management Projects Proof of Concept

项目名称：	Use of Crowdsource Passive Data to Evaluate Effectiveness of Access Management Projects Proof of Concept
摘要：	Implementation of access management projects has historically caused conflict between practitioners who support the safety and mobility benefits of access management and business/property owners who are concerned about the potential negative impacts of reduced access to adjacent properties. Elected officials who are responsible for supporting or approving project funding find themselves in a delicate balancing act in the debate between safety, economy, and mobility. Past evaluations of access management projects have been limited to manual traffic data collection, simulations, and evaluation of crash data many years after the project is implemented. In addition, evaluation of sales tax receipts before and after implementation of the project has been limited. The purpose of this project is to test the use of innovative data sources (Wejo connected vehicle data and SafeGraph point of interest data) to evaluate the safety, mobility, and economic effects of access management projects by comparing trips into adjacent development before and after implementation of the project. Wejo connected vehicle data is a rich data source that provides information about vehicle movements and vehicle events (e.g., hard braking, acceleration, etc.), so there are several aspects of this data that are beneficial to this evaluation. In addition, an economic analysis will be performed to evaluate the financial impacts on adjacent businesses.
状态：	Active
资金：	137045
资助组织：	Office of the Assistant Secretary for Research and Technology；National Institute for Congestion Reduction
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：	Albert, Debbie；Jha, Kartikeya
开始时间：	20220501
预计完成日期：	20230630
主题领域：	Data and Information Technology；Economics；Highways；Planning and Forecasting