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Towards a predictive model of driver acceptance of active collision avoidance systems

Large, David; Banks, Victoria; Burnett, Gary; Harvey, Catherine

Authors

DAVID LARGE David.R.Large@nottingham.ac.uk
Senior Research Fellow

Victoria Banks

GARY BURNETT GARY.BURNETT@NOTTINGHAM.AC.UK
Professor of Transport Human Factors



Abstract

Drivers’ acceptance of advanced-driver-assistance-systems (ADAS), such as pedestrian alert systems (PAS), is vital if the full benefits are to be realised. However, the adoption and continued use of such technology is not only contingent on the system’s technical competence, but is also dependent upon drivers’ attitudes towards the system, and the impact that it has on their driving behaviour and performance. Understanding and integrating the factors that affect and define acceptance in a driving context is therefore important, but complex. We present an in-depth literature review, enriched by a driving simulator study (both conducted as part of the EU-Horizon2020 PROSPECT project), that together begin to collate these factors and explore their interrelationship. A preliminary, descriptive model of driver acceptance is subsequently presented. Further work will enhance and validate the model, with the aim of creating a predictive model that can be used to inform the design of future in-vehicle technologies.

Start Date Apr 16, 2018
Publication Date Apr 17, 2018
Book Title Proceedings of 7th Transport Research Arena TRA 2018, April 16 - 19, 2018, Vienna, Austria
APA6 Citation Large, D., Banks, V., Burnett, G., & Harvey, C. (2018). Towards a predictive model of driver acceptance of active collision avoidance systems. In Proceedings of 7th Transport Research Arena TRA 2018, April 16 - 19, 2018, Vienna, Austriadoi:10.5281/zenodo.1222174
DOI https://doi.org/10.5281/zenodo.1222174
Publisher URL https://zenodo.org/record/1222174#.W_1pJ-j7SUk

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