Open AccessElderly driver retraining using automatic evaluation system of safe driving skill
Author(s) -
Tada Masahiro,
Noma Haruo,
Utsumi Akira,
Segawa Makoto,
Okada Masaya,
Renge Kazumi
Publication year - 2014
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2013.0027
Subject(s) - retraining , advanced driver assistance systems , computer science , safe driving , automotive engineering , transport engineering , artificial intelligence , engineering , simulation , business , international trade
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.