Incident Duration Modeling Using Flexible Parametric Hazard-Based Models
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers.
This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model.
Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008.
Results show that different factors significantly affect different incident time phases, whose best distributions were diverse.
Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents.
The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time.
American Psychological Association (APA)
Li, Ruimin& Shang, Pan. 2014. Incident Duration Modeling Using Flexible Parametric Hazard-Based Models. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1034654
Modern Language Association (MLA)
Li, Ruimin& Shang, Pan. Incident Duration Modeling Using Flexible Parametric Hazard-Based Models. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1034654
American Medical Association (AMA)
Li, Ruimin& Shang, Pan. Incident Duration Modeling Using Flexible Parametric Hazard-Based Models. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1034654
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1034654