Highway Worker’s Perception of Autonomous Truck-Mounted Attenuator: A Case Study in Indiana DOT

Tuesday, June 10, 2025

9:00 AM – 9:15 AM MT

Primary Author(s)

CT

Chi Tian, PhD (he/him/his)

Assistant Professor of Instruction
University of Texas at Tyler
Tyler, TX, United States

Presenter(s)

CT

Chi Tian, PhD (he/him/his)

Assistant Professor of Instruction
University of Texas at Tyler
Tyler, TX, United States

Co-Author(s)

Yunfeng Chen, n/a

Associate Professor
School of Construction Management Technology, Purdue
West Lafayette, Indiana, United States
YF

Yiheng Feng, n/a

Assistant Professor
Lyles School of Civil and Construction Engineering, Purdue
West Lafayette, Indiana, United States
Jiansong Zhang, n/a

Associate Professor
School of Construction Management Technology, Purdue
West Lafayette, Indiana, United States

Submitter(s)

CT

Chi Tian, PhD (he/him/his)

Assistant Professor of Instruction
University of Texas at Tyler
Tyler, TX, United States

Abstract: Highway maintenance operations have been associated with high rates of crashes, leading to workers’ injuries and fatalities. To protect the state Department of Transportation (DOT)’s maintenance workers, autonomous systems have been implemented in various work zone maintenance operations, including the Autonomous Truck-Mounted Attenuator (ATMA). Though the ATMA has been tested in several DOTs, DOT workers’ perception of the ATMA has not been well studied. To understand workers’ perceptions of the ATMA system, this study collected evaluations from 14 Indiana DOT workers after six weeks of closed-road and open-road testing. The testing was conducted during four maintenance activities and under different roadway conditions. The findings of this study suggest that workers believe the ATMA system improves their safety and productivity in mobile work zone operations. Additionally, longer exposure to ATMA operation leads to more positive evaluations. In addition, the 14 workers from two INDOT maintenance units have different levels of exposure to ATMA testing. Although previous studies suggest that age is a key factor that influences users’ evaluations of emerging technologies, this study does not reveal any age-related differences. The findings of this study provide insights for future autonomous system implementation and suggest that proper training is an indispensable step for the adoption of such technologies.

Learning Objectives:

Attendees can expect to learn the following from this session:

Participants will gain insight into the latest advancements in implementing autonomous trucks for work zone safety
Participants will learn how age and experience influence workers' perceptions of the ATMA system.
Participants will explore future directions in autonomous truck testing and development.