Macrolevel Traffic Crash Analysis: A Spatial Econometric Model Approach
المؤلفون المشاركون
Wang, Shaohua
Lu, Yao
Ning, Chen
Yan-yan, Chen
Huang, Jianling
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-05-06
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
This study presents a spatial approach for the macrolevel traffic crashes analysis based on point-of-interest (POI) data and other related data from an open source.
The spatial autoregression is explored by Moran’s I Index with three spatial weight features (i.e., (a) Rook, (b) Queen, and (c) Euclidean distance).
The traditional Ordinary Least Square (OLS) model, the Spatial Lag Model (SLM), the Spatial Error Model (SEM), and the Spatial Durbin Model (SDM) were developed to describe the spatial correlations among 2,114 Traffic Analysis Zones (TAZs) of Tianjin, one of the four municipalities in China.
Results of the models indicated that the SDM with the Rook spatial weight feature is found to be the optimal spatial model to characterize the relationship of various variables and crashes.
The results show that population density, consumption density, intersection density, and road density have significantly positive influence on traffic crashes, whereas company density, hotel density, and residential density have significant but negative effects in the local TAZ.
The spillover effects coefficient of population density and road density are positive, indicating that the increase of these variables in the surrounding TAZs will lead to the increase of crashes in the target zone.
The impacts of company density and hotel density are just the opposite.
In general, the research findings can help transportation planners and managers better understand the general characteristics of traffic crashes and improve the situation of traffic security.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Shaohua& Yan-yan, Chen& Huang, Jianling& Ning, Chen& Lu, Yao. 2019. Macrolevel Traffic Crash Analysis: A Spatial Econometric Model Approach. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1196069
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Shaohua…[et al.]. Macrolevel Traffic Crash Analysis: A Spatial Econometric Model Approach. Mathematical Problems in Engineering No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1196069
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Shaohua& Yan-yan, Chen& Huang, Jianling& Ning, Chen& Lu, Yao. Macrolevel Traffic Crash Analysis: A Spatial Econometric Model Approach. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1196069
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1196069
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر