Spatio-Temporal Accident Impact Estimation Model and its Applications
Using Binary Integer Programming and Survival Analysis
(Sprache: Englisch)
This book introduces an analytic procedure that estimates the amount of traffic congestion (vehicle hours of delay) that is caused by different types of accidents that occur on urban freeways, as well as a model for prediction of real-time accident...
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This book introduces an analytic procedure that estimates the amount of traffic congestion (vehicle hours of delay) that is caused by different types of accidents that occur on urban freeways, as well as a model for prediction of real-time accident information such as how long an accident will affect traffic congestion and to the extent of the traffic congestion. The first part describes a method to separate the non-recurrent delay from any recurrent delay that is present on the road at the time and place of a reported accident, in order to estimate the contribution of non-recurrent delay caused by the specific accident. Since a number of estimated delay results were censored by time and/or space boundary conditions, an approach based on survival analysis was applied to analyze estimated delay and to predict traffic congestion impact in terms of time and space. Additionally, this book presents three prediction models regarding the spatio-temporal impact caused by a traffic accident as well as an accident duration model based on AFT metric model.
Autoren-Porträt von Younshik Chung
Chung, YounshikYounshik Chung is a research associate at The Korea Transport Institute. He has a Ph.D. in Civil and Environmental Engineering from the University of California, Irvine. He published papers regarding a transportation data fusion, freeway operation and control, GIS and GPS for transportation, and freeway congestion management.
Bibliographische Angaben
- Autor: Younshik Chung
- 2008, 300 Seiten, Maße: 15 x 22 cm, Kartoniert (TB), Englisch
- Verlag: VDM Verlag Dr. Müller e.K.
- ISBN-10: 3639003438
- ISBN-13: 9783639003437
Sprache:
Englisch
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