Evaluation of Vehicle Telematics and Infrastructure-based Connected Vehicle Data for Real-Time Safety and Mobility Application

Principal Investigator(s):

Xiaopeng Li, Professor of Civil and Environmental Engineering – University of Wisconsin-Madison
Pei Li, Assistant Professor of Civil and Architectural Engineering – University of Wyoming
Chengyuan Ma, Research Associate – University of Wisconsin-Madison

Project Abstract:
The emergence of connected vehicle (CV) data has provided unprecedented opportunities for developing real-time, proactive applications to enhance safety and mobility. This project utilizes and compares telematics and infrastructure-based CV data to determine optimal applications for each and explore integration strategies for safety and mobility solutions. Specifically, telematics CV data provide the location, speed, and other key information on approximately 5-10% of vehicles on the road. In contrast, infrastructure-based CV data from the connected corridor in the City of Madison contain information about traffic signals, vehicles, and road geometry. By comparing and integrating these data sources, this project proposes physics models and neural network algorithms to detect real-time safety issues such as crashes. The detection results can be used to issue immediate warnings to drivers, traffic managers, and automated vehicle systems. To disseminate these warnings, we propose utilizing roadside variable message signs and in-app notifications via platforms like HAAS, Google Maps, and Waze. The proposed applications can be piloted through field tests in the University of Wisconsin-Madison’s Level 3 CAV testbed and possibly later at Mcity.

Institution(s): University of Wisconsin-Madison

Award Year: 2025

Research Focus: Safety, Mobility

Project Form(s):