Abstract
Roadways in the City of Virginia Beach have consistently ranked in the top 10 crash cluster locations in the state of Virginia, many of which occur at signal controlled intersections that control flow on to and off of the only major interstate in the City, I-264 [1]. Further, the Virginia Department of Transportation’s (VDOT) Pedestrian Action Plan has identified Pacific Avenue, a major oceanfront resort corridor, as a priority pedestrian crash cluster location [2]. The City, like many municipalities, has invested a significant amount of resources in digitizing their transportation system infrastructure. Such is evident at signal controlled intersections where a myriad of sensors such as vision-based cameras, thermal-based cameras, radars, loop detectors, Wi-Fi detectors, Bluetooth detectors and in some cases wireless Dedicated Short Range Communication (DSRC) Road Side Units (RSU) are integrated. However, such assets are used primarily to adapt signal controller Signal Phase and Timing (SPaT) based on traffic flow. An opportunity exists where the City’s infrastructure investment can be leveraged to collect, process, analyze and make safety suggestions based on the sensors’ observations at dangerous intersections in the City. This proposal seeks to understand the existing systems and how they can be leveraged to provide the City with insight and suggested countermeasures to address the safety issues on these roadways. In addition, this project seeks to develop methods to populate data from such sensors into formats that can be utilized by the industry to assist in the development of connected and automated vehicle safety systems.
Project Highlights
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Final Report
EWD & T2 Products
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Presentations/Publications
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Research Investigators (PI*)
Abhijit Sarkar (VTTI)*
Reginald Viray (VTTI)
Thomas Gorman (VTTI/VT)
Eileen Herbers (VT)
Ioannis Papakis (VT)
Project Information
Start Date: 2019-01-01
End Date: 2022-03-31
Status: Completed
Grant Number: 69A3551747115
Total Funding: $168,706
Source Organization: Safe-D National UTC
Project Number: 04-121
Safe-D Theme Areas
Big Data Analytics
Automated Vehicles
Connected Vehicles
Safe-D Application Areas
Infrastructure Technology
Vulnerable Users
Driver Factors and Interfaces
Performance Measures
Planning for Safety
Operations and Design
Vehicle Technology
More Information
Sponsor Organization
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Performing Organization
Virginia Polytechnic Institute and State University
Virginia Tech Transportation Institute
3500 Transportation Research Plaza
Blacksburg, Virginia 24061
USA