Basic study of Haptic Navigation for Electric Scooter

Tomosuke Maeda･Keisuke Otaki･Takayoshi Yoshimura (Toyota Central R&D Labs.)･Tomoaki Mitsuhashi･Takafumi Horigome (Toyota Motor)･Hiroyuki Sakai (Toyota Central R&D Labs.)

Electric scooters (e-scooters, ES), are increasingly used as last-mile options in sharing services. At the same time, traffic accidents involving ESs have become a concern. Inappropriate riding behavior when using electric scooters is often cited as a main cause. This study compared a conventional navigation app and a haptic navigation method under conditions close to real traffic environments, and evaluated the characteristics and effectiveness of each.

Development of wakefulness maintenance support technology using stochastic resonance

Shimpei Kusumoto･Yutaro Sato･Masato Anegawa･Wataru Yoshida･Yoshitaka Fujihara (Mazda)･Yoshiharu Yamamoto･Ikuhiro Yamaguchi (The University of Tokyo)

Conventional drowsiness alerts encourage breaks but provide limited awakening, risking drowsiness before reaching a rest area. This study applies “stochastic resonance,” where subtle noise stimuli activate the body at optimal intensity, to propose a new HMI that maintains driver alertness without increasing discomfort, ensuring safe travel to the nearest rest stop.

Effect of the See-Through A-pillar using Mirror on Pedestrian Detection Time during Right Turn at Intersection

Yujiro Mizobuchi (MIRISE Technologies)･Kunitomo Aoki･Akio Hirano (Nagoya Univercity)･Kazuyuki Ishihara･Kojiro Tachi･Masaaki Kawauchi (MIRISE Technologies)･Hirohumi Aoki (Nagoya Univercity)

Blind spots caused by the A-pillar can delay pedestrian detection at intersections, potentially leading to traffic accidents. This study investigates the effectiveness of a device that renders the A-pillar transparent using mirrors, focusing on pedestrian detection time during right turns at intersections. Experimental results indicate that the device enables drivers to detect pedestrians on average 0.6 seconds earlier, suggesting a meaningful improvement in situational awareness and safety.

Study on Automotive Seat Vibration for Improving Driver Situational Awareness

Yukiyo Kuriyagawa (Nihon University)･Xinyue Zhang (Nihon University Graduate School)･Hidefumi Koizumi･Shinichi Sagawai･Hiroshi Wakuda･Toshiki Nakamura･Keigo Abe･Kunio Sato (ALPS ALPINE CO., LTD.)

This study aims to achieve comfortable intuitive driving assistance by using seat vibration as an alternative to, or in combination with, visual and auditory stimuli. To enhance the driver's situational awareness of the vehicle's surroundings, we present findings from investigations involving variations in seat vibration frequency.

Inclusive HMI Design to Mitigate Mode Confusion in Multilevel Driving Automation

Turkan Hentati (Human Factors Engineer)･Oana Moldovan (R+D Senior Engineer)

This paper investigates the challenge of mode confusion in automated driving through a dedicated use case about multilevel driving developed within the European project CERTAIN. Although automation promises more accessible and safer mobility, mode confusion remains a major obstacle, particularly for diverse user groups such as people with disabilities, older adults, novice and expert drivers. Building on state-of-the-art literature highlighting flexibility, personalization, and error tolerance as essential principles of inclusive HMI design, we underscore the need to explicitly capture and integrate the specific needs of these profiles. Our analysis will combine these insights with interviews conducted in CERTAIN, acknowledging that each individual is unique and requires tailored interaction strategies to support clearer mode awareness.

Vehicle automation: A framework on user-automation interaction

Jeroen Hogema･Jan Souman･Hari Subraveti･Marijke van Weperen･Chris van der Ploeg･Marieke Martens･Saarang Gaggar (TNO)

Effective user–automation interaction is critical for partial (SAE L2) and conditional (L3) vehicle automation. Users must clearly understand automation states, while HMIs should adapt to user behavior and promote safety. Current ISO standards lack comprehensive coverage and are inconsistently applied. This paper introduces a multi-perspective framework: evaluation of HMIs through a questionnaire; training requirements for users; teamwork based framework for assessing the interaction; and an adapted ISO 21448 (SOTIF) process to create a structured approach for the assessment of the interaction. Results from simulator experiments and ongoing studies demonstrate the framework's potential for guiding assessment of user–automation interaction.