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Near-Miss Incident Data Classification Relating to Active Safety Measures
Published May 20, 2009 by Society of Automotive Engineers of Japan in Japan
Event: JSAE Spring Conference
800 cases of emergent near-miss data collected by incident data recorder were classified relating to vehicle active safety measures. Because the human errors can be observed in each incident, it is able to evaluate the effectiveness of related active safety equipment in reference to the operating conditions. Main features seen in the classified data are introduced as well as some analytical applications on evaluating active safety equipment.
- Toshiya Tsukahara - Mitsubishi Motors Corp.
- Hidetoshi Saruwatari - Honda R&D Co., Ltd.
- Tetsushi Mimuro - Akita Prefectural Univ.
- Yohei Satomi - Toyota Motor Corp.
- Mamoru Sekiguchi - Fuji Heavy Industries Ltd.
- Katsumi Moro - Society of Automotive Engineer of Japan, Inc.
- Yasuhiko Miura - Mazda Motor Corp.
- Masao Nagai - Tokyo University of Agriculture and Technology
- Hitoshi Uno - Nissan Motor Co., Ltd.
- Akinori Uno - Suzuki Motor Corp.
- Minoru Yoshida - Daihatsu Motor Co., Ltd.
- Minoru Kamata - The University of Tokyo