Abstract
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.
Highlights
Non-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
Traffic incident duration analysis and prediction in Traffic Incident Management System (TIMS) and intelligent transportation systems are currently important topics that have been applied with different results in previous studies
The incident duration time is related to various factors, such as temporal characteristics; incident characteristics; road characteristics; traffic characteristics; and weather conditions
Summary
Non-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. 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. With the development of traffic detection techniques and TIMS over the past decades, researchers can collect data conveniently, conduct a detailed analysis of the influence factors of traffic incident duration time, and predict traffic incident duration time in a highly accurate manner [4]. The incident duration time is related to various factors, such as temporal characteristics (e.g., time of day, day of the week, and/or season); incident characteristics (e.g., number of vehicles involved in an incident, truck/taxi/pedestrian involvement, number of deaths and/or injured persons); road characteristics (e.g., incident location and road condition); traffic characteristics (e.g., traffic volume); and weather conditions (e.g., rain, fog, and/or snow)
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