Development of ATMA/AIPV Deployment Guidelines Considering Traffic and Safety Impacts

University

Missouri University of Science & Technology

Principal Investigator

Xianbiao Hu (xbhu@mst.edu)

Total Project Cost

$185,144

Funding Type

2016 USDOT

Start Date

12/13/2019

End Date

12/31/2022

Agency ID or Contract Number

69A3551747107

Abstract

Autonomous Truck Mounted Attenuator/Impact Protection Vehicle (ATMA/AIPV) is a quickly emerging technology and is expected to bring considerable potentials in transportation infrastructure maintenance by removing drivers from the risk. The system includes a lead truck (LT), a follow truck (FT), a truck mounted attenuator (TMA) installed on the FT, and a leader-follower system that enables the FT to drive autonomously and follow the LT. While exciting technology is being developed and shows promising benefits in roadway maintenance, what’s not well studied is the impacts of such autonomous system to traffic operation and roadway safety, and subsequently how should DOT develop deployment strategies with those aspects taken into consideration.

Description

This project will produce open source software tool for the state DOT to deploy the ATMA system. No further technology implementation is applicable to this project.

Impacts/Benefits

This project aims to study the associated critical research questions, and in the end develop a practical software tool that takes in DOT inputs such as roadway network GIS shapefile, traffic counts and ATMA/AIPV system characteristics, and outputs a set of recommended deployment strategies, including the roadway maintenance sequence, staffing plan and needed resource, potential impacts to the traffic network and any suggested traffic management plan to ensure a smooth and safe traffic flow while effectively maintaining the roadway facilities.

Deliverables

Download the Final Report

Related Phases Phase II: MoDOT Autonomous Leader-Follower TMA System: Development of Autonomous Trucks Operation Guidelines and Driver Training Process

Phase III: Optimization of Transportation Infrastructure System Performance with Autonomous Maintenance Technology in Work Zones