Relationship between Evaluation of Elderly Drivers Urban Driving by Driving Instructors and Cognitive-Physical Characteristics and Driving Attitudes
-Study on Driver Characteristics for Delaying Driving Cessation (44)-

Takashi Yonekawa･Masae Kojima･Hirofumi Aoki (Nagoya University)･Kan Shimazaki (Kindai University)･Rin Itou･Sueharu Nagiri･Satsuki Yamauchi･Kunitomo Aoki･Akio Hirano (Nagoya University)

The increase in the number of traffic accidents involving elderly drivers has raised the issue of age-related decline in driving ability. Driving instructors evaluated the driving ability of 141 elderly drivers aged 59 to 88 years old in urban areas. The results showed that there was a correlation between the instructors' overall driving evaluation scores and cognitive and physical characteristics and driving awareness.

Developing an Integrated Driver Model for Risk Assessment
-Reproduction of Driver's Visual and Cognitive Functions-

Miki Hayashima･Yuji Matsuki (Fukuoka Institute of Technology)

To assess driver’s risk of traffic accidents quantitatively, we propose an integrated driver model incorporating visual and cognitive functions closely resembling human characteristics. The model reproduces the process from visual information acquisition to driving operation, accounting for human-specific perception and judgement ambiguities. By simulating driving behavior precisely, this approach enables a realistic and versatile evaluation of traffic accident risks across diverse scenarios.

Determinants of Elderly Drivers' Needs for Driving Aptitude Tests, Safe Driving Learning, and Advanced Driver Assistance Systems
-Study on Driver Characteristics for Delaying Driving Cessation (45)-

Shunji Taniguchi･Aiko Inoue･Hiroyuki Umegaki (Nagoya University)･Naoshi Koide (Osaka University)･Hirofumi Aoki (Nagoya University)

In order to clarify the actual situation of elderly drivers' frailty and driving experience (driving skills, safe driving skills, and near accidents), as well as the demand for safe driving skill diagnosis/learning programs and safe driving support equipment for elderly drivers, we conducted a survey on driving cars on a daily basis. We report the results of a questionnaire survey conducted among elderly drivers (2,069 people aged 60 and over).

Relationship between Driving Risk Assessment using Touch Panel Display and Driving Risk Estimated from Image Analysis (First Report)

Masumi Terayama ()･Masayuki Shimizu･Hiroyuki Aoki (Nagoya University)

It is thought that the driver perceives the change in the driving environment while driving and feels it as a risk.
Based on this hypothesis, we report the relationship between the points pointed out in the driving risk assessment test using 3DCG using a touch panel display and the points of change in the optical flow of the images.

Development of Drunk Driving Detection Models using Machine Learning with Driving Simulator and Actual Vehicle Data

Norimasa Nakamura･Masaki Yamaoka･Minori Yamataka･Takafumi Ito (DENSO)

To reduce traffic accidents, we are developing technology to detect abnormal driver driving. In this paper, we report a method for detecting abnormal driving using data collected from a driving simulator and an actual vehicle.