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Investigation of older driver’s takeover performance in highly automated vehicles in adverse weather conditions

Lookup NU author(s): Dr Shuo LiORCiD, Professor Phil BlytheORCiD, 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.

Publication metadata

Author(s): Li S, Blythe P, Guo W, Namdeo A

Publication type: Article

Publication status: Published

Journal: IET Intelligent Transport Systems

Year: 2018

Volume: 12

Issue: 9

Pages: 1157-1165

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


DOI: 10.1049/iet-its.2018.0104


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