Effect of Acceleration and Deceleration Characteristics of Electric Vehicles on Pedal Operation of Elderly Drivers

Yusuke Hayashida (Tokyo University of Agriculture and Technology)･Tatsuya Iizuka･Akihiro Abe･Yoko Kato･Michiaki Sekine (NALTEC)

Electric vehicles exhibit larger acceleration and deceleration responses to accelerator pedal inputs than gasoline-engine vehicles. Therefore, elderly drivers accustomed to gasoline-engine vehicles may have difficulty operating them properly. In this research, a driving simulator was used to recreate a scenario in which a vehicle follows a preceding vehicle, and the pedal input and vehicle behavior of elderly drivers operating electric vehicles were evaluated using various evaluation indicators.

Regional Differences in Collision Avoidance Emergency Braking Frequency Measured by Dashcams of Elderly Drivers
-Study on Driver Characteristics for Delaying Driving Cessation (47)-

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

The previous report confirmed a correlation between collision avoidance emergency braking frequency per driving distance measured by elderly drivers' dashcams and their safe driving ability. This report compares collision avoidance emergency braking frequencies in the Nagoya and Tsukuba regions, which have different driving environments. Since the frequency was lower in the Tsukuba region, we propose a method for evaluation using collision avoidance emergency braking frequency adjusted for driving speed.

Estimation of Driving Style Based on Eye Tracking during Autonomous Driving

Yuki Mekata (Kanagawa University)

Personalizing the controls of a driving assistance system is expected to encourage drivers to use the system appropriately. This study attempted to estimate drivers' style in their braking operations based on eye tracking data corrected during autonomous driving using a driving simulator. The realization of such estimations is expected to expand the feasibility of personalization in driving assistance systems.

Driving Simulator Log Analysis in Rehabilitation for Resuming Driving

Chise Kobayashi (Kindai University)･Ryunosuke Hashimoto (Kindai University/Kishigawa Rehabilitation Hospital)･Takeshi Kohama (Kindai University)

To establish objective criteria for assessing the feasibility of driving resumption in patients with brain injury, driving behavior was analyzed using log data obtained during rehabilitation using a driving simulator. We compared three groups: healthy individuals, those who resumed driving, and those who did not. The findings indicated differences in driving behavior among the groups during steering maneuvers when vehicles approached from the right side.