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Elderly driver retraining using automatic evaluation system of safe driving skill

In Japan, although the rapid aging of the population has caused serious traffic problems, only a few studies have investigated the behaviour of elderly drivers in real traffic conditions. The authors have been developing a system to automatically evaluate safe-driving skill through small wireless we...

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Bibliographic Details
Published in:IET intelligent transport systems 2014-05, Vol.8 (3), p.266-272
Main Authors: Tada, Masahiro, Noma, Haruo, Utsumi, Akira, Segawa, Makoto, Okada, Masaya, Renge, Kazumi
Format: Article
Language:English
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Summary:In Japan, although the rapid aging of the population has caused serious traffic problems, only a few studies have investigated the behaviour of elderly drivers in real traffic conditions. The authors have been developing a system to automatically evaluate safe-driving skill through small wireless wearable sensors that directly measure the driver's behaviour. The authors aim is to promote safe driving by providing a personalised training program according to the individual's own shortcomings in driving behaviour. By employing the sensors together with GPS and driving instructors’ knowledge, our system can automatically identify shortcomings in driving skill with an accuracy of over 80%. In February 2010, the Kyoto Prefecture Public Safety Commission, in Japan, certified our system as the first and only support tool for its ‘mandatory retraining course for elderly drivers’ that all elderly drivers, aged over 70 years, are required to take when renewing their driver's license. In this study, the authors discuss the effectiveness of our system and investigate elderly drivers’ behaviour through a large-scale demonstration experiment, involving 749 elderly drivers, in the mandatory driver-retraining course on public roads. The authors results reveal that although elderly drivers are able to maintain a safe vehicle speed, their tendency to not scan around their vehicle to ensure safety makes their driving risky.
ISSN:1751-956X
1751-9578
1751-9578
DOI:10.1049/iet-its.2013.0027