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Current and potential negative effects of autonomous vehicles

Authors: Carlo Polidori; Paola Di Mascio; Giuseppe Cantisani; Marco Petrelli;

Current and potential negative effects of autonomous vehicles

Abstract

There is a general enthusiastic approach toward autonomous vehicles, e.g. they are claimed to be the breakthrough solution for a drastic reduction of road accidents, largely caused by human errors. However, their current and potential negative effects have not been adequately addressed yet: decreasing driving skills, new “automotive digital divide”, additional reaction time, “last mile” issue for automated HGVs are only some examples of still pending issues that can jeopardize the expected advantages. This paper analyzes the levels of automated driving defined by SAEJ3016 according to the current literature and resumes the main issues not yet adequately solved, in order to give a clear picture of the current and potential negative effect of each level, starting from “Level 2 - Partial automation” up to “level 4 –High automation”. Level 5 is not analyzed because its deployment appears too far in the time and there are not enough data for an effective discussion. The position of the automotive industry and its need to re-invent the business is related to the present market approach and may have a relevant influence on the incoming paradigm shift.

Country
Italy
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Keywords

automated driving; connected vehicles; truck platooning; current and potential issues; industry needs., Automated driving, Connected vehicles, Truck platooning, Current and potential issues, Industry needs.

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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!
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