Damage assessment of cyclists collided by high-velocity runaway vehicles
-Risk assessment between high-velocity runaway vehicle and bicycle collision from statistical accident data analysis-

Yasufumi Sekine (Fukuyama University)

When discussing the dangers of high-velocity runaway vehicles, the potential for causing personal injury to victims cannot be ignored. This study analyzed the relationship between vehicle collision velocity and the fatal or serious injury rates among cyclists using traffic accident statistics. Based on these analysis results, the author attempted to clarify the risk (the injury level of cyclists) of collisions between bicycles and high-velocity runaway vehicles.

Validation of the Traffic Offence Traits Scale (TOTS)
-An Examination Using Cognitive Tasks-

Masae Kojima (Nagoya University)･Kojiro Shojima (National Center for University Entrance Examination)･Kazuko Okamura (National Research Institute of Police Science)･Chieko Nishizawa･Shota Matsubayashi･Kazunori Ban (Toyota Technical Development)

This study examines the validity of the Traffic Offence Traits Scale (TOTS), a self-report measure developed for risk assessment of offending traits. Building on previous studies confirming its 7-factor, 24-item structure, we verify that TOTS factors correspond to objective performance-based measures. A sample of general drivers will complete TOTS alongside three cognitive tasks via web panel survey: the Balloon Analogue Risk Task (BART) for risk-taking, the Iowa Gambling Task (IGT) for decision-making, and the Stop-Signal Task (SST) for response inhibition. Significant associations between TOTS factors and corresponding cognitive measures will demonstrate TOTS as a valid tool for traffic offence risk assessment.

Educational Policies Designed for Traffic Offenders: Analysis of Traits and Behavior

Chieko Nishizawa･Shota Matsuayashi (Toyota Technical Development)･Masae Kojima (Nagoya University)･Takuma Yamaguchi･Kazunori Ban (Toyota Technical Development)

Conventional educational programs for traffic offenders may not be effective for all individuals, because the programs are applied regardless of offender traits. Our goal is to develop more effective educational policy for traffic offenders. This study investigates appropriate feedback methodology as a preliminary step This paper reports the results of analyses of offender traits and behavior conducted to support the design of such feedback.

Study on Electric Kick Scooter Accident Analysis Using ITARDA Macro Data and TUAT Drive Recorder Data

Toru Kiuchi (ITARDA)･Masami Aga (Tokyo University of Agriculture and Technology)･Mayu Ishii (ITARDA)･Yukiko Ookita･Masao Nagai (Tokyo University of Agriculture and Technology)

Since July 2023, persons aged 16 and older have been permitted to ride electric kick scooters without a license. The National Police Agency’s accident statistics database, revised in 2022, added “stand-up electric vehicles” to the “Vehicle Type” category, and a further revision in 2024 added “specified small mopeds”. The authors attempted to examine electric kick scooters’ accident situation using ITARDA macro data from 2023 and 2024.

Investigation of Impact Behavior of Electric Scooter Riders in Head-on Collisions with Automobiles

Ryo Oga (Japan Safe Driving Center)

Research on electric scooter collisions using moving vehicles is scarce. This report details a head-on collision experiment between a moving automobile and a stationary electric scooter to verify rider impact behavior. Results showed the rider rode up onto the hood and struck the windshield. Due to a higher initial body position than pedestrians from the step height, the rider's hood override increased. Although the handlebar is at waist height, the stem fractured at an impact speed of 30 km/h, suggesting the handlebar minimally affects rider impact behavior.

Who Benefits from Which Driving Assistance? A Large-Scale Cross-Sectional Study on the Psychological Effects of Driving Assistance

Yoh Yamazaki (Mazda/Hirosaki University)･Nanae Michida･Masanori Honda･Hiromune Obayashi･Yosuke Furuya (Mazda)･Yoshinori Tamada･Ken Itoh･Tatsuya Mikami･Koichi Murashita･Shigeyuki Nakaji (Hirosaki University)

Driver assistance tailored to individual driver characteristics is essential for safe and comfortable driving. In this study, approximately 900 participants were classified into four groups based on driving attention ability and driving self-efficacy. We investigated the psychological effects of three types of driving assistance designed to support different cognitive functions. The results showed that the effectiveness of driving assistance differed depending on driver characteristics.