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Predicting Real-Time Crash Risk for Urban Expressways in China
المؤلفون المشاركون
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-01-30
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
We developed a real-time crash risk prediction model for urban expressways in China in this study.
About two-year crash data and their matching traffic sensor data from the Beijing section of Jingha expressway were utilized for this research.
The traffic data in six 5-minute intervals between 0 and 30 minutes prior to crash occurrence was extracted, respectively.
To obtain the appropriate data training period, the data (in each 5-minute interval) during six different periods was collected as training data, respectively, and the crash risk value under different data conditions was defined.
Then we proposed a new real-time crash risk prediction model using decision tree method and adaptive neural network fuzzy inference system (ANFIS).
By comparing several real-time crash risk prediction methods, it was found that our proposed method had higher precision than others.
And the training error and testing error were minimum (0.280 and 0.291, resp.) when the data during 0 to 30 minutes prior to crash occurrence was collected and the decision tree-ANFIS method was applied to train and establish the real-time crash risk prediction model.
The prediction accuracy of the crash occurrence could reach 65% when 0.60 was considered as the crash prediction threshold.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Miaomiao& Chen, Yongsheng. 2017. Predicting Real-Time Crash Risk for Urban Expressways in China. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1191303
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Miaomiao& Chen, Yongsheng. Predicting Real-Time Crash Risk for Urban Expressways in China. Mathematical Problems in Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1191303
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Miaomiao& Chen, Yongsheng. Predicting Real-Time Crash Risk for Urban Expressways in China. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1191303
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1191303
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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