Predicting Freeway Work Zone Delays and Costs with a Hybrid Machine-Learning Model
Joint Authors
Lee, Joyoung
Du, Bo
Chien, Steven I.
Spasovic, Lazar
Source
Journal of Advanced Transportation
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-07
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A hybrid machine-learning model, integrating an artificial neural network (ANN) and a support vector machine (SVM) model, is developed to predict spatiotemporal delays, subject to road geometry, number of lane closures, and work zone duration in different periods of a day and in the days of a week.
The model is very user friendly, allowing the least inputs from the users.
With that the delays caused by a work zone on any location of a New Jersey freeway can be predicted.
To this end, tremendous amounts of data from different sources were collected to establish the relationship between the model inputs and outputs.
A comparative analysis was conducted, and results indicate that the proposed model outperforms others in terms of the least root mean square error (RMSE).
The proposed hybrid model can be used to calculate contractor penalty in terms of cost overruns as well as incentive reward schedule in case of early work competition.
Additionally, it can assist work zone planners in determining the best start and end times of a work zone for developing and evaluating traffic mitigation and management plans.
American Psychological Association (APA)
Du, Bo& Chien, Steven I.& Lee, Joyoung& Spasovic, Lazar. 2017. Predicting Freeway Work Zone Delays and Costs with a Hybrid Machine-Learning Model. Journal of Advanced Transportation،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1170913
Modern Language Association (MLA)
Du, Bo…[et al.]. Predicting Freeway Work Zone Delays and Costs with a Hybrid Machine-Learning Model. Journal of Advanced Transportation No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1170913
American Medical Association (AMA)
Du, Bo& Chien, Steven I.& Lee, Joyoung& Spasovic, Lazar. Predicting Freeway Work Zone Delays and Costs with a Hybrid Machine-Learning Model. Journal of Advanced Transportation. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1170913
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170913