Designing Motion: Lessons for Self-driving and Robotic Motion from Human Traffic Interaction
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Designing Motion : Lessons for Self-driving and Robotic Motion from Human Traffic Interaction. / Brown, Barry; Laurier, Eric; Vinkhuyzen, Erik.
I: Proceedings of the ACM on Human-Computer Interaction, Bind 7, Nr. GROUP, 5, 2023.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Designing Motion
T2 - Lessons for Self-driving and Robotic Motion from Human Traffic Interaction
AU - Brown, Barry
AU - Laurier, Eric
AU - Vinkhuyzen, Erik
N1 - Publisher Copyright: © 2023 ACM.
PY - 2023
Y1 - 2023
N2 - The advent of autonomous cars creates a range of new questions about road safety, as well as a new collaborative domain for CSCW to analyse. This paper uses video data collected from five countries - India, Spain, France, Chile, and the USA - to study how road users interact with each other. We use interactional video analysis to document how co-ordination is achieved in traffic not just through the use of formal rules, but through situated communicative action. Human movement is a rich implicit communication channel and this communication is essential for safe manoeuvring on the road, such as in the co-ordination between pedestrians and drivers. We discuss five basic movements elements: gaps, speed, position, indicating and stopping. Together these elements can be combined to make and accept offers, show urgency, make requests and display preferences. We build on these results to explore lessons for how we can design the implicit motion of self-driving cars so that these motions are understandable - in traffic - by other road users. In discussion, we explore the lessons from this for designing the movement of robotic systems more broadly.
AB - The advent of autonomous cars creates a range of new questions about road safety, as well as a new collaborative domain for CSCW to analyse. This paper uses video data collected from five countries - India, Spain, France, Chile, and the USA - to study how road users interact with each other. We use interactional video analysis to document how co-ordination is achieved in traffic not just through the use of formal rules, but through situated communicative action. Human movement is a rich implicit communication channel and this communication is essential for safe manoeuvring on the road, such as in the co-ordination between pedestrians and drivers. We discuss five basic movements elements: gaps, speed, position, indicating and stopping. Together these elements can be combined to make and accept offers, show urgency, make requests and display preferences. We build on these results to explore lessons for how we can design the implicit motion of self-driving cars so that these motions are understandable - in traffic - by other road users. In discussion, we explore the lessons from this for designing the movement of robotic systems more broadly.
KW - autonomous vehicles
KW - ethnomethodology
KW - video analysis
UR - http://www.scopus.com/inward/record.url?scp=85147257069&partnerID=8YFLogxK
U2 - 10.1145/3567555
DO - 10.1145/3567555
M3 - Journal article
AN - SCOPUS:85147257069
VL - 7
JO - Proceedings of the ACM on Human-Computer Interaction
JF - Proceedings of the ACM on Human-Computer Interaction
SN - 2573-0142
IS - GROUP
M1 - 5
ER -
ID: 335964583