Safe-D: Safety through Disruption

Development of a Roadside LiDAR-Based Situational Awareness System for Work Zone Safety: Proof-of-Concept Study

 

Abstract

Roadway construction and maintenance have become increasingly common as the U.S. transportation system ages and the population and traffic volume increase. This places more and more work zone workers near high-speed vehicles and increases the probability of being struck by them. This project innovatively deployed 360-degree LiDAR sensors at the roadside and tested their potential to provide work zone safety in terms of detection accuracy, efficiency, and ease of use. Researchers developed a set of algorithms to collect and interpret real-time information for each approaching vehicle and worker (e.g., location, speed, and direction) in and outside work zones using roadside LiDAR. Ultimately, the outcome of this pilot study could lead to developing a full-scale warning system deployable in a real work zone environment. Such a system could detect and analyze live traffic and work zone activity, activate the appropriate warning scheme, and deliver information to roadway workers in work zones in a timely manner so they can take evasive actions instead of relying on traditional “passive” safety countermeasures. This kind of panoramic, trajectory-level data for work zone actors can be used to develop a next-generation work zone situational awareness system.

Project Highlights

Coming Soon!

Final Report

TTI 05-03 Final Report

EWD & T2 Products

Coming Soon!

Presentations/Publications

Coming Soon!

Final Dataset

The final datasets for this project are located in the Safe-D Collection on the VTTI Dataverse; DOI: 10.15787/VTT1/KUTAZD.

Research Investigators (PI*)

Jason (Dayong) Wu (TTI/TAMU)*
Minh Le (TTI/TAMU)*
Gerald (Jerry) Ullman (TTI/TAMU)
Srikanth Saripalli (TTI/TAMU)
Tianchen Huang (TTI/TAMU-Student)
Amir Darwesh (TTI/TAMU-Student)

Project Information

Start Date: 2020-05-01
End Date: 2023-06-30
Status: Active
Grant Number: 69A3551747115
Total Funding: $234,975
Source Organization: Safe-D National UTC
Project Number: TTI-05-03

Safe-D Theme Areas

Big Data Analytics

Safe-D Application Areas

Vulnerable Users
Risk Assessment
Infrastructure Technology
WorkZone
LiDar

More Information

RiP URL
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

Texas A&M University
Texas A&M Transportation Institute
3135 TAMU College Station, Texas 77843-3135
USA