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

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

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Authors

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

Victoria Banks

Gary Burnett



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.

Conference Name 7th European Transport Research Arena TRA 2018
Conference Location Vienna, Austria
Start Date Apr 16, 2018
End Date Apr 19, 2018
Acceptance Date Apr 16, 2018
Online Publication Date Apr 16, 2018
Publication Date Apr 17, 2018
Deposit Date Nov 23, 2018
Publicly Available Date Nov 28, 2018
Book Title Proceedings of 7th Transport Research Arena TRA 2018, April 16 - 19, 2018, Vienna, Austria
DOI https://doi.org/10.5281/zenodo.1222174
Public URL https://nottingham-repository.worktribe.com/output/1217488
Publisher URL https://zenodo.org/record/1222174#.W_1pJ-j7SUk

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