Back to Search
Start Over
Resilient interactions between cyclists and drivers, and what does this mean for automated vehicles?
- Source :
-
Applied ergonomics [Appl Ergon] 2024 May; Vol. 117, pp. 104237. Date of Electronic Publication: 2024 Feb 13. - Publication Year :
- 2024
-
Abstract
- The road transport system is a complex sociotechnical system that relies on a number of formal and informal rules of the road to ensure safety and resilience. Interactions between vulnerable road users and drivers often includes informal communication channels that are tightly linked to social norms, user expectations and the environmental context. Automated vehicles have a challenge in being able to communicate and respond to these informal rules of the road, therefore additional technologies are required to better support vulnerable road users. This paper presents the informal rules that cyclists and drivers employ within a cyclist overtake manoeuvre, through qualitative data collected from focus groups and interviews with road users. These informal rules are classified into the key elements of resilience (monitor, detect, anticipate, respond and learn) to understand how they guide the resilient interactions between road users. Using a human factors approach, the Perceptual Cycle Model shows how information is communicated between different road users and created by the situational context. This is then used to inform how automation will alter the communication between cyclists and drivers, and what additional feedback mechanisms will be needed to support the systems resilience. Technologies that can support these feedback mechanisms are proposed as avenues for future development.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1872-9126
- Volume :
- 117
- Database :
- MEDLINE
- Journal :
- Applied ergonomics
- Publication Type :
- Academic Journal
- Accession number :
- 38354551
- Full Text :
- https://doi.org/10.1016/j.apergo.2024.104237