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Overview of traffic incident duration analysis and prediction
by
Li, Ruimin
, Ben-Akiva, Moshe E
, Pereira, Francisco C
in
Discriminant analysis
/ Factor analysis
/ Heterogeneity
/ Literature reviews
/ Regression analysis
/ Regression models
/ Statistical analysis
/ Statistical tests
/ Traffic congestion
/ Traffic management
/ Traffic models
/ Transportation research
/ Travel time
2018
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Overview of traffic incident duration analysis and prediction
by
Li, Ruimin
, Ben-Akiva, Moshe E
, Pereira, Francisco C
in
Discriminant analysis
/ Factor analysis
/ Heterogeneity
/ Literature reviews
/ Regression analysis
/ Regression models
/ Statistical analysis
/ Statistical tests
/ Traffic congestion
/ Traffic management
/ Traffic models
/ Transportation research
/ Travel time
2018
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Do you wish to request the book?
Overview of traffic incident duration analysis and prediction
by
Li, Ruimin
, Ben-Akiva, Moshe E
, Pereira, Francisco C
in
Discriminant analysis
/ Factor analysis
/ Heterogeneity
/ Literature reviews
/ Regression analysis
/ Regression models
/ Statistical analysis
/ Statistical tests
/ Traffic congestion
/ Traffic management
/ Traffic models
/ Transportation research
/ Travel time
2018
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Overview of traffic incident duration analysis and prediction
Journal Article
Overview of traffic incident duration analysis and prediction
2018
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Overview
IntroductionNon-recurrent congestion caused by traffic incident is difficult to predict but should be dealt with in a timely and effective manner to reduce its influence on road capacity reduction and enormous travel time loss. Influence factor analysis and reasonable prediction of traffic incident duration are important in traffic incident management to predict incident impacts and aid in the implementation of appropriate traffic operation strategies. The objective of this study is to conduct a thorough review and discusses the research evolution, mainly including the different phases of incident duration, data resources, and the various methods that are applied in the traffic incident duration influence factor analysis and duration time prediction.MethodsIn order to achieve the goal of this study, we presented a systematic review of traffic incident duration time estimation and prediction methods developed based on various data resource, methodologies etc.Resultsbased on the previous studies, we analyse (i) Data resources and characteristics: different traffic incident time phases, data set size, incident types, duration time distribution, available data resources, significant influence factors and unobserved heterogeneity and randomness, (ii) traffic incident duration analysis methods, mainly including hazard-based duration model and regression and statistical tests, (iii) traffic incident duration prediction methods and evaluation of prediction accuracy.ConclusionsAfter a comprehensive review of literature, this study identifies and analyses future challenges and what can be achieved in the future to estimate and predict the traffic incident duration time.
Publisher
Springer Nature B.V
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