Lookup NU author(s): Dr Shuo Li,
Professor Phil Blythe,
Dr Amy Guo,
Dr Anil Namdeo
This is the authors' accepted manuscript of an article that has been published in its final definitive form by The Institution of Engineering and Technology, 2018.
For re-use rights please refer to the publisher's terms and conditions.
Driving is important for older people to maintain mobility. In order to reduce age-related functional decline, older drivers may adjust their driving by avoiding difficult situations. One of these situations is driving in adverse weather conditions, such as in the rain, snow, and fog which reduce visual clarity of the road ahead. The upcoming highly automated vehicle (HAV) has the potential supporting older people. However, only limited work has been done to study older drivers’ interaction with HAV, especially in adverse weather conditions. This study investigates the effect of age and weather on take-over control performance among drivers from HAV. A driving simulation study with 76 drivers has been implemented. The participants took over the vehicle control from HAV under four weather conditions-clear weather, rain, snow and fog where the time and quality of the take-over control are quantified and measured. Results show age did affect the take-over time and quality. Moreover, adverse weather conditions, especially snow and fog, lead to a longer take-over time and worse take-over quality. The results highlighted that a user-centred design of human-machine interaction would have the potential to facilitate a safe interaction with HAV under the adverse weather for older drivers.
Author(s): Li S, Blythe P, Guo W, Namdeo A
Publication type: Article
Publication status: Published
Journal: IET Intelligent Transport Systems
Print publication date: 01/11/2018
Online publication date: 16/07/2018
Acceptance date: 08/05/2018
Date deposited: 10/05/2018
ISSN (print): 1751-956X
ISSN (electronic): 1751-9578
Publisher: The Institution of Engineering and Technology
Altmetrics provided by Altmetric