Document Type
Technical Report
Publication Date
2-2024
Keywords
Probe data, access management, connected vehicle data, safety, vehicle trajectory
Digital Object Identifier (DOI)
https://doi.org/10.5038/CUTR-NICR-Y3-1-8
Abstract
The impacts of access management projects have been evaluated, documented, and debated by practitioners and adjacent property owners for decades. This research aims to evaluate the potential of using new-age data sources such as crowdsourced connected vehicle (CV) data, crowdsourced consumer spending pattern data, and traditional sources for sales tax and vehicle crash data in quantifying the effects of access management projects on arterial roadways. Based on observations and analyses highlighted in this study, it can be concluded that crowdsourced data provide valuable information on travel patterns along access managed corridors. The same information, if sought through manual data collection, can be expensive, time consuming, potentially biased, and relatively unscalable. An evaluation of crowdsourced data, such as Wejo, revealed that different elements of these datasets can be useful for a different set of audiences. Current limitations of new-age crowdsourced data sources as well as traditional data sources used for evaluating access management projects are also noted. The insights into traffic patterns and driving behavior gained using CV data can be used to inform transportation planning and policy-making efforts, as well as to improve road safety and reduce traffic congestion. Additionally, this project demonstrates the power of advanced analytical techniques, such as geospatial analysis, in extracting insights from large datasets and applying that knowledge for engineering, planning, public outreach, and business community engagement activities.
Scholar Commons Citation
Albert, Debbie; Jha, Kartikeya; Ramenzani, Mahin; Steadman, Max; Glover, Brianne; and Albert, Luke, "Use of Crowdsourced Data for Access Management Evaluation" (2024). Research Reports. 28.
https://digitalcommons.usf.edu/cutr_nicr/28
Policy brief
