Predicting Work Zone Collision Probabilities via Clustering: Application in Optimal Deployment of Highway Response Teams

المؤلفون المشاركون

Skibniewski, Miroslaw
Sekuła, Przemysław
Vander Laan, Zachary
Farokhi Sadabadi, Kaveh

المصدر

Journal of Advanced Transportation

العدد

المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-16، 16ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2018-09-18

دولة النشر

مصر

عدد الصفحات

16

التخصصات الرئيسية

هندسة مدنية

الملخص EN

This paper proposes a clustering approach to predict the probability of a collision occurring in the proximity of planned road maintenance operations (i.e., work zones).

The proposed method is applied to over 54,000 short-term work zones in the state of Maryland and demonstrates an ability to predict work zone collision probabilities.

One of the key applications of this work is using the predicted probabilities at the operational level to help allocate highway response teams.

To this end, a two-stage stochastic program is used to locate response vehicles on the Maryland highway network in order to minimize expected response times.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Sekuła, Przemysław& Vander Laan, Zachary& Farokhi Sadabadi, Kaveh& Skibniewski, Miroslaw. 2018. Predicting Work Zone Collision Probabilities via Clustering: Application in Optimal Deployment of Highway Response Teams. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1181121

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Sekuła, Przemysław…[et al.]. Predicting Work Zone Collision Probabilities via Clustering: Application in Optimal Deployment of Highway Response Teams. Journal of Advanced Transportation No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1181121

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Sekuła, Przemysław& Vander Laan, Zachary& Farokhi Sadabadi, Kaveh& Skibniewski, Miroslaw. Predicting Work Zone Collision Probabilities via Clustering: Application in Optimal Deployment of Highway Response Teams. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1181121

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1181121