Abstract
Truck-Mounted Attenuators (TMAs) are energy-absorbing devices added to heavy shadow vehicles to provide a mobile barrier that protects work crews from errant vehicles entering active work zones. In mobile and short-duration operations, drivers manually operate the TMA – keeping pace with the work zone as needed to function as a mobile barrier protecting work crews. While the TMA is designed to absorb and/or redirect the energy from a colliding vehicle, there is still a significant risk of injury to the TMA driver when struck. TMA crashes are a serious problem in Virginia where they have increased each year from 2011 (17 crashes) to 2014 (45 crashes),2 despite a decrease in the number of active construction sites between 2013 and 2014. Although various efforts have been made to improve TMA driver crashworthiness (e.g., by adding interior padding, harnesses, and supplemental head restraints),1 the most effective way to protect TMA drivers may be to remove them from the vehicle altogether. Recent advances in automated vehicle technologies—including advanced sensing, high-precision differential GPS, inertial sensing, advanced control algorithms, and machine learning—have enabled the development of automated systems capable of controlling TMA vehicles. Furthermore, the relatively low operating speeds and platoon-like operating movements of leader-follower TMA systems make an automated control concept feasible for a variety of mobile and short-duration TMA use cases. This project seeks to develop an automated control system for TMA vehicles using a short following distance, leader-follower control concept which will remove the driver from the at-risk TMA vehicle.
Project Highlights
- Coming Soon
Final Report
Coming Soon
EWD & T2 Products
Coming Soon
Presentations/Publications
Coming Soon
Final Dataset
Coming Soon
Research Investigators (PI*)
Mike Mollenhauer (VTTI/VT)*
Elizabeth White (VTTI/VT)*
Jean Paul Talledo Vilela (VTTI/VT)*
Will Vaughan (VT)*
Project Information
Start Date: 2022-01-01
End Date: 2023-09-30
Status: Active
Grant Number: 69A3551747115
Total Funding: $274,974
Source Organization: Safe-D National UTC
Project Number: 06-005
Safe-D Theme Areas
Automated Vehicles
Connected Vehicles
Safe-D Application Areas
Risk Assessment
Vulnerable Users
Driver Factors and Interfaces
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
Virginia Polytechnic Institute and State University
Virginia Tech Transportation Institute
3500 Transportation Research Plaza
Blacksburg, Virginia 24061
USA