Three social car visions to improve driver behaviour
The social cost of road injury and fatalities is still unacceptable. The driver is often mainly responsible for road crashes, therefore changing the driver behaviour is one of the most important and most challenging priority in road transport.
This paper presents three innovative visions that articulate the potential of using Vehicle to Vehicle (V2V) communication for supporting the exchange of social information amongst drivers. We argue that there could be tremendous benefits in socialising cars to influence human driving behaviours for the better and that this aspect is still relevant in the age of looming autonomous cars.
Our visions provide theoretical grounding how V2V infrastructure and emerging human–machine interfaces (HMI) could persuade drivers to:
(i) adopt better (e.g. greener) driving practices, (ii) reduce drivers aggressiveness towards pro-social driving behaviours, and (iii) reduce risk-taking behaviour in young, particularly male, adults.
The visions present simple but powerful concepts that reveal ‘good’ aspects of the driver behaviour to other drivers and make them contagious. The use of self-efficacy, social norms, gamification theories and social cues could then increase the likelihood of a widespread adoption of such ‘good’ driving behaviours.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Journal Article|
|Keywords:||social cars, pervasive computing, social norms, cooperative systems, Intelligent Transport Systems|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Computer-Human Interaction (080602)|
|Divisions:||Current > Research Centres > Centre for Accident Research & Road Safety - Qld (CARRS-Q)
Past > Schools > Computer Science
Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Current > Schools > School of Psychology & Counselling
|Copyright Owner:||Copyright 2014 Please consult the authors|
|Copyright Statement:||NOTICE: this is the author’s version of a work that was accepted for publication in Pervasive and Mobile Computing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pervasive and Mobile Computing, [VOL#, ISSUE#, (DATE)] DOI: 10.1016/j.pmcj.2014.06.004|
|Deposited On:||24 Jun 2014 22:54|
|Last Modified:||09 Nov 2016 11:41|
Repository Staff Only: item control page