Ageing and Driving Performance in the UK Using Normal Mixture Model Cluster Analysis Technique

• Main Authors: Khan, M.T., Khan, R., Khan, A.
• Format: Article
• Published: Palacky University Olomouc 2023
• Online Access: http://scholars.utp.edu.my/id/eprint/38075/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173435548&doi=10.5507%2ftots.2023.007&partnerID=40&md5=7d8020ecff20b66a11a028aa5c9e85fc

This research addresses the issue of an individual's ability to drive and especially of those individuals that are questionably demented (dementia is suspected) or are in a state of very mild dementia and are therefore the most difficult to identify. A methodology has been developed for categorization of drivers by considering three driving performance indices/parameters simultaneously. This novel approach precluded the previous technique whereby only a single driving performance index (an omnibus approach without the ability to discriminate between normal driving behavior and risky driving habits primarily due to cognitive decline) is considered. Driving performance of 28 young and 28 old drivers was gauged by 24 driving performance parameters through two designed drives on driving simulator. Normal Mixture Model Cluster Analysis was used in the performance-based categorization of drivers. It was found that out of a total of 56 drivers, 8 turned out to be "poor drivers". Results from neuropsychological/cognitive tests showed on average lower cognitive performance for the "poor drivers" group. This methodology will preclude the need for measurement of driving skills through driving instructors. © 2023 The Korea Association of Teachers of English.