Evaluation of travel delay and accident risk at moving work zones

Gan, Xiafan; Weng, Jinxian; Zhang, Jin

doi:10.1080/19439962.2019.1659464

Cited by 11 publications

(2 citation statements)

References 32 publications

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“…The work zone fatalities in U.S. increased to 857 in 2020 [7]. Compared to a stationary work zone, more factors would influence the safety of a moving work zone, such as the work zone moving speed, the position on the road, and the traffic condition [11]. Truck-Mounted Attenuator (TMA) has been adopted to enhance the visibility of work zones to passing vehicles, inform them to change to a work-free lane, and protect workers and equipment at the work zones from rear-end crashes [23].…”

Section: Introductionmentioning

confidence: 99%

A Simulation Study of Passing Drivers' Responses to the Automated Truck-Mounted Attenuator System in Road Maintenance

Liu¹,

Wang²,

Qin³

2022

Preprint

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The Autonomous Truck-Mounted Attenuator (ATMA) system is a lead-follower vehicle system based on autonomous driving and connected vehicle technologies. The lead truck performs maintenance tasks on the road, and the unmanned follower truck is designed to improve the visibility of the moving work zone to passing vehicles and to protect workers and equipment. While the ATMA has been under testing by transportation maintenance and operations agencies in recent years, a simulator-based testing capability is a supplement, especially if human subjects are involved. This paper aims to discover how passing drivers perceive, understand, and react to the ATMA system in road maintenance accordingly. A driving simulator for ATMA studies is developed for collecting the driving data. Then, driving simulation experiments were performed, wherein a screen-based eye tracker collected sixteen subjects' gaze points and pupil diameters. Data analysis has evidenced the changes in the visual attention pattern of subjects when they were passing the ATMA. On average, the ATMA starts to attract subjects' attention from 500 ft behind the follower truck. Most (87.50%) understood the follower truck's protection purpose, and the majority (86.67%) reasoned the association between the two trucks. But still, many (43.75%) did not recognize that ATMA is a connected autonomous vehicle system. While all subjects safely changed lanes and attempted to pass the slow-moving ATMA, their inadequate understanding of ATMA is a potential risk, like cutting into the ATAM. Results implied that transportation maintenance and operations agencies should take this into consideration in establishing the deployment guidance.

show abstract

Section: Introductionmentioning

confidence: 99%

A Simulation Study of Passing Drivers' Responses to the Automated Truck-Mounted Attenuator System in Road Maintenance

Liu¹,

Wang²,

Qin³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Work zone fatalities in the U.S.A. increased to 857 in 2020 ( 2 ). Compared to a stationary work zone, more factors influence the safety of a moving work zone, such as the work zone moving speed, the position on the road, and the traffic conditions ( 3 ). The truck-mounted attenuator (TMA) has been adopted to enhance the visibility of work zones to passing vehicles, inform them to change to a work-free lane, and protect workers and equipment in work zones from rear-end crashes ( 4 ).…”

mentioning

confidence: 99%

Simulation Study of Passing Drivers’ Responses to the Autonomous Truck-Mounted Attenuator System in Road Maintenance

Wang

Qin

2023

Transportation Research Record: Journal of the Transportation R

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The autonomous truck-mounted attenuator (ATMA) system is a lead–follower vehicle system based on autonomous driving and connected vehicle technologies. The lead truck performs maintenance tasks on the road, and the unmanned follower truck alerts passing vehicles about the moving work zone and protects workers and the equipment. While the ATMA has been under testing by transportation maintenance and operations agencies recently, a simulator-based testing capability is a supplement, especially if human subjects are involved. This paper aims to discover how passing drivers perceive, understand, and react to the ATMA system in road maintenance. With the driving simulator developed for this ATMA study, the paper performed a simulation study wherein a screen-based eye tracker collected 16 subjects’ gaze points and pupil diameters. Data analysis evidenced the change in subjects’ visual attention patterns while passing the ATMA. On average, the ATMA starts to attract subjects’ attention from 500 ft behind the follower truck. Most (87.50%) understood the follower truck’s protection purpose, and many (60%) reasoned the association between the two trucks. Nevertheless, nearly half of the participants (43.75%) did not recognize that the ATMA is a connected autonomous vehicle system. While all subjects safely changed lanes and attempted to pass the slow-moving ATMA, their inadequate understanding of the ATMA is a potential risk, for issues such as cutting into the ATMA. The results implied that transportation maintenance and operations agencies should consider this in establishing the deployment guidance.

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Spatial-temporal varying coefficient model for lane-changing behavior in work zone merging areas

Gan

Weng

et al. 2020

Journal of Transportation Safety & Security

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Evaluation of travel delay and accident risk at moving work zones

Cited by 11 publications

References 32 publications

A Simulation Study of Passing Drivers' Responses to the Automated Truck-Mounted Attenuator System in Road Maintenance

A Simulation Study of Passing Drivers' Responses to the Automated Truck-Mounted Attenuator System in Road Maintenance

Simulation Study of Passing Drivers’ Responses to the Autonomous Truck-Mounted Attenuator System in Road Maintenance

Spatial-temporal varying coefficient model for lane-changing behavior in work zone merging areas

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