Development and application of traffic accident density estimation models using kernel density estimation

作     者：Seiji Hashimoto Syuji Yoshiki Ryoko Saeki Yasuhiro Mimura Ryosuke Ando Shutaro Nanba 

作者机构：Graduate School of Environmental and Life ScienceOkayama UniversityOkayama 700-0807Japan Department of Civil EngineeringFukuoka UniversityFukuoka 814-0180Japan Fukuyama Consultants Co.Ltd.Futeuotea 812-0013Japan International Development Consultants Co.Ltd.Aichi 460-0008Japan Toyota Transportation Research InstituteAichi 471-0024Japan 

出 版 物：《Journal of Traffic and Transportation Engineering(English Edition)》 (交通运输工程学报（英文版）)

年 卷 期：2016年第3卷第3期

页      面：262-270页

学科分类：02[经济学] 03[法学] 07[理学] 08[工学] 070103[理学-概率论与数理统计] 0202[经济学-应用经济学] 020208[经济学-统计学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0838[工学-公安技术] 0813[工学-建筑学] 0714[理学-统计学（可授理学、经济学学位）] 0814[工学-土木工程] 0701[理学-数学] 0823[工学-交通运输工程] 0306[法学-公安学] 

基　　金：supported by a grant from the Takata Foundation 

主　　题：Traffic safety Kernel density estimation (KDE) Hotspots Zone 30 

摘      要：Traffic accident frequency has been decreasing in Japan in recent years. Nevertheless, many accidents still occur on residential roads. Area-wide traffic calming measures including Zone 30, which discourages traffic by setting a speed limit of 30 km/h in residential areas, have been implemented. However, no objective implementation method has been established. Development of a model for traffic accident density estimation explained by GIS data can enable the determination of dangerous areas objectively and easily, indicating where area-wide traffic calming can be implemented preferentially. This study examined the relations between traffic accidents and city characteristics, such as population, road factors, and spatial factors. A model was developed to estimate traffic accident density. Kernel density estimation （KDE） techniques were used to assess the relations efficiently. Besides, 16 models were developed by combining accident locations, accident types, and data types. By using them, the applicability of traffic accident density estimation models was examined. Results obtained using Spearman rank correlation show high coefficients between the predicted number and the actual number. The model can indicate the relative accident risk in cities. Results of this study can be used for objective determination of areas where area-wide traffic calming can be implemented preferentially, even if sufficient traffic accident data are not available.