The Effects of Traffic Composition on Freeway Crash Frequency by Injury Severity: A Bayesian Multivariate Spatial Modeling Approach
المؤلفون المشاركون
Wen, Huiying
Zeng, Qiang
Sun, Jiaren
Zhang, Xuan
Yuan, Quan
المصدر
Journal of Advanced Transportation
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-08-07
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الملخص EN
This study sets out to investigate the effects of traffic composition on freeway crash frequency by injury severity.
A crash dataset collected from Kaiyang Freeway, China, is adopted for the empirical analysis, where vehicles are divided into five categories and crashes are classified into no injury and injury levels.
In consideration of correlated spatial effects between adjacent segments, a Bayesian multivariate conditional autoregressive model is proposed to link no-injury and injury crash frequencies to the risk factors, including the percentages of different vehicle categories, daily vehicle kilometers traveled (DVKT), and roadway geometry.
The model estimation results show that, compared to Category 5 vehicles (e.g., heavy truck), larger percentages of Categories 1 (e.g., passenger car) and 3 (e.g., medium truck) vehicles would lead to less no-injury crashes and more injury crashes.
DVKT, horizontal curvature, and vertical grade are also found to be associated with no-injury and/or injury crash frequencies.
The significant heterogeneous and spatial effects for no-injury and injury crashes justify the applicability of the proposed model.
The findings are helpful to understand the relationship between traffic composition and freeway safety and to provide suggestions for designing strategies of vehicle safety improvement.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wen, Huiying& Sun, Jiaren& Zeng, Qiang& Zhang, Xuan& Yuan, Quan. 2018. The Effects of Traffic Composition on Freeway Crash Frequency by Injury Severity: A Bayesian Multivariate Spatial Modeling Approach. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1181594
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wen, Huiying…[et al.]. The Effects of Traffic Composition on Freeway Crash Frequency by Injury Severity: A Bayesian Multivariate Spatial Modeling Approach. Journal of Advanced Transportation No. 2018 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-1181594
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wen, Huiying& Sun, Jiaren& Zeng, Qiang& Zhang, Xuan& Yuan, Quan. The Effects of Traffic Composition on Freeway Crash Frequency by Injury Severity: A Bayesian Multivariate Spatial Modeling Approach. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1181594
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1181594
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