Perceptions on the Future of Automation in r/Truckers

Orii, Lisa; Tosca, Diana; Kun, Andrew L.; Shaer, Orit

doi:10.1145/3411763.3451637

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…In the field of autonomous driving, understanding the experiences of human drivers -an important part of future traffic by working alongside automation systems -will contribute to future research in human-autonomy interactions and challenges posed by automation [2,63]. Previous studies have explored drivers' experiences, perspectives, attitudes, and acceptance of autonomous systems.…”

Section: From Driver Experiences To Autonomy Experiencesmentioning

confidence: 99%

Work with AI and Work for AI: Autonomous Vehicle Safety Drivers’ Lived Experiences

Chu

Zong

Shu

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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The development of Autonomous Vehicle (AV) has created a novel job, the safety driver, recruited from experienced drivers to supervise and operate AV in numerous driving missions. Safety drivers usually work with non-perfect AV in high-risk real-world traffic environments for road testing tasks. However, this group of workers is under-explored in the HCI community. To fill this gap, we conducted semi-structured interviews with 26 safety drivers. Our results present how safety drivers cope with defective algorithms and shape and calibrate their perceptions while working with AV. We found that, as front-line workers, safety drivers are forced to take risks accumulated from the AV industry upstream and are also confronting restricted self-development in working for AV development. We contribute the first empirical evidence of the lived experience of safety drivers, the first passengers in the development of AV, and also the grassroots workers for AV, which can shed light on future human-AI interaction research.

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Section: From Driver Experiences To Autonomy Experiencesmentioning

confidence: 99%

Work with AI and Work for AI: Autonomous Vehicle Safety Drivers’ Lived Experiences

Chu

Zong

Shu

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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“…In terms of the perception of automation in trucking, Dodel and Mesch (2020) have shown how workers in occupations involving a greater number of manual or physical tasks, such as in the case of long haul trucking, can have more negative perceptions regarding the impact of automation on their livelihood. Orii et al (2021) analyzed discussions related to automation among the members of the r/Truckers subreddit and found that <1% of comments had positive views on automation.…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of automation on long haul trucking operator-hours in the United States

Mohan

Vaishnav

2022

Humanit Soc Sci Commun

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Automated long haul trucking is being developed for commercial deployment in the United States. One possible mode of deployment for this technology is a “transfer-hub” model where the operationally less complex highway driving is automated, while human drivers drive the more complex urban segment of the route. We study the possible net impacts on tractor-trailer operator-hours from this mode of deployment. Using data from the 2017 Commodity Flow Survey, we gather information on trucking shipments and the operator-hours required to fulfill those shipments. We find that up to 94% of long haul trucking operator-hours may be impacted as the technology improves to operate in all weather conditions. If the technology is however restricted to the southern states where the majority of companies are currently testing automated trucking, we find that only 10% of operator-hours are impacted. We conduct interviews with industry stakeholders including tractor-trailer operators on the feasibility of such a system of deployment. We find that an increase in short haul operation is unlikely to compensate for the loss in long haul operator-hours, despite public claims to this effect by the developers of the technology. Policymakers should consider the impact of different scenarios of deployment on the long haul trucking workforce.

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