Safe-D: Safety through Disruption

Real Time Risk Prediction at Signalized Intersection Using Graph Neural Network


Intersection related traffic crash and fatalities are one of the major concerns for road safety. In this project we aim to understand the major cause of conflicts at an intersection by studying the intricate interplay between all the roadway agents. We propose to use the current traffic camera systems to automatically process traffic video data. As manual annotation of video datasets is a very labor-intensive and costly process, A system that can process these traffic datasets automatically would strongly enhance the effectiveness of the analysis and enable new research questions to be addressed. Therefore, we propose to use computer vision algorithm to process the videos. Also, we propose to use advanced machine learning methods including graph neural network (GNN) to model the interaction of all the roadway agents at any given instance, and their role in road safety, both individually and as a composite system. As a result, the proposed model aims to develop a near real time risk score for a traffic scene.

Project Highlights

  • Coming soon

Final Report

Coming Soon

EWD & T2 Products

Coming Soon


Coming Soon

Final Dataset

The final datasets for this project are located in the Safe-D Collection on the VTTI Dataverse; Coming Soon

Research Investigators (PI*)

Abhijit Sarkar (VTTI)*
Zachary Doerzaph (VTTI/VT)*
Sparsh Jain (VTTI/VT Student)
Akash Sonth (VTTI/VT Student)
Hirva Bhagat(VTTI/VT Student)

Project Information

Start Date: 2022-05-01
End Date: 2023-06-30
Status: Active
Grant Number: 69A3551747115
Total Funding: 320,000
Source Organization: Safe-D National UTC
Project Number: 06-012

Safe-D Theme Areas

Big Data Analytics

Safe-D Application Areas

Risk Assessment
Vulnerable Users
Operations and Design
Infrastructure Technology
Planning for Safety

More Information

UTC Project Information Form

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