Title: VEHand: an in-vehicle information system to improve driving performance in an unfamiliar traffic regulation

Authors: Hasan J. Alyamani; Manolya Kavakli; Stephen Smith

Addresses: Faculty of Computing and Information Technology in Rabigh, King Abdulaziz University, Jeddah, KSA ' Department of Computing, Macquarie University, Sydney, Australia ' Department of Computing, Macquarie University, Sydney, Australia

Abstract: Driving under unfamiliar traffic regulations (UFTR) is associated with an increased number of traffic accidents. To drive safely in such conditions, drivers need to adapt their prior knowledge to a new driving situation. This ability is called cognitive flexibility (CF). CF is influenced by the degree of handedness of the performer. The goal of this research was to develop a driving-assistance system that adapts the information it provides based on the handedness degree of drivers under UFTR. Two empirical studies were conducted in a driving simulator. The results of the first study indicated that left/mixed-handed drivers made significantly fewer errors that could be attributed to CF impairment than did strong right-handed drivers. Accordingly, we developed a driving-assistance system ('VEHand'), which provides drivers with useful feedback based on their handedness degree. The results of the second study indicated that VEHand significantly assisted strong-right handed drivers to correctly enter roundabouts and intersections.

Keywords: cognitive flexibility; driving performance; in-vehicle information system; IVIS; degree of handedness; driving simulator; unfamiliar traffic regulation; UFTR; roundabout; intersections.

DOI: 10.1504/IJHFE.2019.105361

International Journal of Human Factors and Ergonomics, 2019 Vol.6 No.4, pp.355 - 389

Received: 22 Jan 2019
Accepted: 02 Oct 2019

Published online: 17 Feb 2020 *

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