• Session No.28 Human Factor and Modeling for Driver (OS)
  • May 21Room G416+G4179:30-12:10
  • Chair: Motoki Shino (The University of Tokyo)
Contents
This session discuss driver characteristics and modeling for the system based on the human error human factors.
Committee
Active Safety Engineering Committee, Human Factor Committee, Driver Assessment Technologies Committee, Image Information Application Committee, Vehicle Characteristics Design Committee
Organizer
Motoki Shino (Institute of Science Tokyo), Kazumasa Onda (Suzuki Motor), Toshihiro Hiraoka (Japan Automobile Research Institute), Shuichi Enokida (Kyushu Institute of Technology), Takamitsu Tajima (Honda R&D)
For presentations that will not be available video streaming after congress, a “✕” is displayed in the “Video” column, so please check.
No. Video Title・Author (Affiliation)
1

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 (Institute of Innovation for Future Society Nagoya University)・Kan Shimazaki (Kindai University)・Rin Itou (Institute of Innovation for Future Society Nagoya University)・Satsuki Yamauchi (Nagoya University)・Sueharu Nagiri・Kunitomo Aoki・Akio Hirano (Institute of Innovation for Future Society 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.

2

Evaluation of Awakening Effect and Accident Risk of Conversations Considering Driver Acceptability

hideyuki ohashi・yuji matsuki (Fukuoka Institute of Technology)

Talking while driving has been shown to enhance alertness, making it a potential measure to prevent drowsy driving. However, research on its impact on driver acceptability and accident risk remains limited. This study comprehensively examines accident risk, arousal effects and acceptability to propose an optimal approach to the frequency and content of conversations during driving.

3

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.

4

Actual Status of Frailty, Driving Experience, and Safety Needs of Elderly Drivers
-Study on Driver Characteristics for Delaying Driving Cessation (45)-

Shunji Taniguchi・Aiko Inoue・Hiroyuki Umegaki (Nagoya University)・Naoshi Koide (Osaka University)・Masae Kojima・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).

5

Relationship between Driving Risk Assessment Using Touch Panel Display and Driving Risk Estimated from Image Analysis

Masumi Terayama ()・Masayuki Shimizu・Hiroyuki Aoki (Nagoya Univ.)

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.

6

Development of Abnormal Driving Detection Methods

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.

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