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  • Summary & Details

A Study of ADS Safety Assessment Methodology Using Near-Miss Data on Logistics Trucks

高速道でのトラックニアミスデータによる自動運転車の安全性評価手法の考察

Detailed Information

Author(J)1) 伊藤 祥司, 2) 中野 泰彦, 3) 上原 健一, 4) Aekanan Sakulraemrung, 5) 福田 泰志, 6) 三浦 基嗣, 7) 井上 秀雄
Author(E)1) Shoji Ito, 2) Yasuhiko Nakano, 3) Kenichi Uehara, 4) Aekanan Sakulraemrung, 5) Hiroshi Fukuda, 6) Mototsugu Miura, 7) Hideo Inoue
Affiliation(J)1) 神奈川工科大学, 2) 神奈川工科大学, 3) 神奈川工科大学, 4) 神奈川工科大学, 5) BIPROGY, 6) PTVグループジャパン, 7) 神奈川工科大学
Affiliation(E)1) Kanagawa Institute of Technology, 2) Kanagawa Institute of Technology, 3) Kanagawa Institute of Technology, 4) Kanagawa Institute of Technology, 5) BIPROGY, 6) PTV Group Japan, 7) Kanagawa Institute of Technology
Abstract(J)経済産業省デジタルライフラインプロジェクトでは,約40万Kmに亘る物流トラックのニアミス画像からリスクシナリオを生成し,シミュレーション活用の安全性評価手法を構築した.本稿では,ニアミスの類型化,リスク反映の各エージェントモデルと交通流の設定方法,危険度と発生頻度の評価指標,の一連の基盤技術を述べる.

Translation

Abstract(E)METI (The Ministry of Economy, Trade and Industry)'s Digital Lifeline Project established a safety assessment methodology utilizing simulations with generating risk scenarios from near-miss images captured by approximately 400,000 km of logistics trucks,. This paper describes a series of foundational technologies: the categorization of near-misses, the configuration methods for agent driver models and traffic flow reflecting risks, and evaluation metrics for severity and exposure.

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