Investigating the Effect of Connected Vehicles (CV) Route Guidance on Mobility and Equity (Collaborative Project)

Project Abstract

Traffic congestion is a serious and increasing national problem, especially for urban commuters. Providing accurate real-time traffic information is a key tool to reduce congestion.

Recent studies have shown that connected vehicles (CVs) can help improve traffic mobility and safety while saving energy and reducing emissions. The CV guidance system is an emerging form of dynamic route guidance. The proposed research will develop and calibrate a microscopic traffic simulation model to replicate the fairly realistic behavior of such vehicles in the traffic simulation environment. Unlike the majority of prior studies that have used hypothetical study areas with simple networks, this study will develop a real-world medium urban road network. Different penetration rates of CVs (0% - 100%) will be developed, and the system-wide effects of CV-equipped vehicles with route guidance features on mobility and equity will be analyzed.

Universities and Sponsoring Organizations Involved

Morgan State
University of Maryland - College Park

U.S. Department of Transportation Office of the Secretary-Research

Principal Investigators

Mansoureh Jeihani (MSU),
Ali Haghani (UMD),

Funding Sources and Amounts

USDOT: $135,000 (Federal), Morgan State University: $45,209 (Match), University of MD - College Park: $25,270 (match)

Expected Start Date


Expected Completion Date


Expected Research Outcomes

The proposed research will be the first microscopic traffic simulation model to simulate the driving behavior of CV guidance with various penetration rates of RSU and CVs, and various traffic conditions.

Expected Equity Impacts and Benefits of Implementation

The findings from this research will provide insight into the impacts of gradual deployment of CVs and RSU on mobility and equity, which helps planners develop public policies on advanced vehicle promotion and regulations. It will also help transportation agencies to equip roads with an optimum number of RSU to take advantage of their capabilities in incident detection and congestion relief. The study will also provide recommendations regarding after-market packages to be used for low income non-CV vehicle owners as well as information dissemination ways to accommodate mobility-challenged travelers in CVs.

Subject Areas

Connected Vehicles, ITS, Traffic Simulation, Transportation Planning