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Perceptions of Fully Autonomous Freight Trucks

Authors: Sean Dougherty; Pamela Ellen; John Stowell; Aleta Williams Richards;

Perceptions of Fully Autonomous Freight Trucks

Abstract

Long-standing truck driver shortages in the US freight transportation trucking industry could be relieved by the use of autonomous freight trucks, but realizing that potential requires access to and sharing of the roadway infrastructure with other drivers. Prior research has focused on consumer perceptions of personal autonomous automobiles rather than sharing the road with autonomous trucks. As an initial examination of consumers’ perceived benefits and risks of autonomous trucks, the authors conducted thirteen semi-structured interviews, eliciting both general issues and then response to risk mitigation scenarios under consideration by the industry and regulators. While interviewees expressed safety concerns and the potential impact on the employment of truck drivers, they also acknowledged the inevitability of the technology. Safety benefits were often expressed concurrently with concerns about the risks. In addition, a theme emerged around the technology needing to prove itself. Despite the authors anticipating a need for autonomous trucks to gain the support of the public, little opposition to automation was expressed and the mitigators under consideration by industry and regulators did not significantly improve perceptions of the technology. However, if safety risks are not mitigated, the concerns expressed could be elevated and alter perceptions of inevitability.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
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