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Assessing Feasibility of Deploying Transit Signal Priority with Connected Vehicle Technology using MSU Testbed

Project Abstract

This project seeks to enhance urban transportation efficiency through the development and implementation of Transit Signal Priority (TSP) integrated with Connected Vehicle (CV) technology using the existing infrastructure at Morgan State University (MSU). The proposed TSP with Connected Vehicles (TSPCV) will utilize advanced prediction models to refine bus arrival time predictions, ensuring optimized green light allocation and significantly improving the flow of public transit and overall traffic conditions. By leveraging data from real-time sensors and implementing a digital twin model for simulations, this project aims to create a more responsive and efficient urban transit system that can adapt to real-time traffic conditions and reduce delays for public transportation.

Universities Involved

University of Virginia (Lead)
Morgan State University

Principle Investigators

B. Brian Park, University of Virginia
Young-Jae Lee, Morgan State University
Di Yang, Morgan State University

Expected Research Outcomes & Impacts

The integration of TSPCV is anticipated to yield significant improvements in transit reliability and traffic flow, thereby enhancing the commuting experience across urban settings. By reducing bus delays and harmonizing the traffic signals with real-time transit needs, the project is expected to contribute to reduced overall traffic congestion and enhanced public transportation service. Additionally, the successful implementation of this system could serve as a model for other cities, promoting wider adoption of smart transportation solutions. Dissemination of the research findings through academic and professional channels and collaboration with industry partners will further amplify the impact, fostering advancements in transportation technology and policy.
Subject Areas

Connected Vehicles, Data Analytics, Traffic Signal Priority