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Optimising Landmark-Based Route Guidance for Older Drivers

Lookup NU author(s): Simon Edwards, Dr Chris EmmersonORCiD, Dr Anil Namdeo, Professor Phil BlytheORCiD, Dr Amy Guo

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

In-vehicle navigation systems (IVNS) have the potential to benefit older drivers, reducing stress associated with way-finding and providing on-trip support, especially in unfamiliar locations. However, existing IVNS present challenges to usability, resulting in lack of uptake and over-reliance on pre-trip planning. This paper presents research aimed at identifying features that make IVNS user-friendly and appropriate for older drivers. Studying navigational performance within a simulated driving environment, it focuses on the use of landmarks with route guidance information, and the most appropriate method of information provision (audio only, visual only or a combination of audio and visual). It also assesses potential gender differences that might arise with landmark-based navigational information.Solutions include use of appropriate roadside landmarks, and information delivered through a combination of audio and icon-based visual format. These features result in lower workload and fewer navigational errors. The audio/ visual modality reduces the hazard of distraction by landmarks resulting in fewer visual glances and lower glance duration to the roadside compared to other modalities.Design and provision of IVNS tailored to older drivers’ needs can make a considerable contribution to maintaining individual mobility for longer.


Publication metadata

Author(s): Edwards SJ, Emmerson C, Namdeo A, Blythe PT, Guo W

Publication type: Article

Publication status: Published

Journal: Transportation Research F: Traffic Psychology and Behaviour

Year: 2016

Volume: 43

Pages: 225-237

Print publication date: 01/11/2016

Online publication date: 01/11/2016

Acceptance date: 09/10/2016

Date deposited: 14/11/2016

ISSN (print): 1369-8478

ISSN (electronic): 1873-5517

Publisher: Pergamon Press

URL: http://dx.doi.org/10.1016/j.trf.2016.10.017

DOI: 10.1016/j.trf.2016.10.017


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Funding

Funder referenceFunder name
EP/G066019/1Research Councils' UK Digital Economy programme
EP/KO37579/1Engineering and Physical Sciences Research Council
EP/K037579/1EPSRC
EP/GO66019/1
EP/KO37579/1

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