Development and validation of a method for evaluating spatial accident risk that make use of pedestrian collision warning information

2022 Fiscal Year Final Research Report

• Project/Area Number: 19K04652
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 22050:Civil engineering plan and transportation engineering-related
• Research Institution: Toyohashi University of Technology
• Principal Investigator: Matsuo Kojiro 豊橋技術科学大学, 工学(系)研究科(研究院), 准教授 (50634226)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: 歩行者衝突警報（PCW） / プローブデータ / 歩行者事故 / 事故危険地点 / 生活道路 / 統計モデル / 実用性検証

Outline of Final Research Achievements

The purpose of this study was to develop a method for evaluating the risk of locational pedestrian accidents, especially on community streets, by using pedestrian collision warning (PCW) information collected from the advanced driver assistance systems and to verify the validity of the method. Specifically, we developed a statistical model to evaluate the risk of pedestrian crashes at each location by using the probe data with PCW information, in addition to accident data, general vehicle probe data, and road environment condition data. The results showed that the PCW incidence rate estimated by empirical Bayesian estimation improves the goodness of fit of the model for the number of pedestrian accidents. Then, a certain validity of the method developed in this study was examined from the viewpoints of road managers and road users.

Free Research Field

交通工学

Academic Significance and Societal Importance of the Research Achievements

既往研究では，事故データに加え自動車プローブデータによる交通量，経路，速度，急
減速度などの情報を活用することで，予防的視点から事故危険地点を抽出できることが認められていたが，それらは自動車側の情報のみであった．本研究では，歩行者事故の危険性評価において最も重要な道路上の歩行者量（リスク暴露量）の情報として，歩行者衝突警報情報の発生地点や発生状況などの情報を活用することで，適切な歩行者事故危険性評価および予防的視点による事故危険地点の抽出に寄与する手法を構築した．これにより，的確な優先対策地点の抽出や道路利用者への効果的な情報提供や注意喚起が期待される．