Skip to Content
My MSU

National Transportation Center


Development of a Pedestrian Collision Avoidance System for Connected and Autonomous Vehicles with Cooperative Perception

Project Abstract

This research proposal aims to enhance pedestrian safety by developing a novel Pedestrian Collision Avoidance System that integrates Connected Vehicle (CV) technology with cooperative perception for Connected and Autonomous Vehicles (CAVs). Spearheaded by Morgan State University and the University of Maryland, College Park, the project leverages advanced sensors and real-time data transmission to better detect and respond to pedestrian movements, particularly those that are sudden and unexpected. By creating a dynamic communication framework between vehicles and roadside infrastructures, this system promises to significantly improve CAVs' responsiveness to pedestrians, thereby reducing the incidence of collisions and enhancing overall traffic safety.

Universities Involved

Morgan State University (Lead)
University of Maryland, College Park

Principle Investigators

Di Yang, Morgan State University
Mansoureh Jeihani, Morgan State University
Xianfeng Yang, University of Maryland, College Park

Expected Research Outcomes & Impacts

The outcomes of this research will be transformative in improving pedestrian safety by advancing the capabilities of autonomous vehicles to detect and avoid collisions through enhanced situational awareness provided by CV technology. This project will potentially establish new benchmarks in CAV system design, contributing significantly to the evolution of intelligent transportation systems in smart cities. The findings are expected to influence future vehicle design and urban planning policies, aiming for a safer integration of autonomous vehicles in human-centric urban spaces. Moreover, the results will be disseminated through academic publications and partnerships with vehicle manufacturers and urban planners to ensure broad application and impact.
Subject Areas

Pedestrian Safety, Connected Vehicles, Intelligent Transportation Systems