Modelling total duration of traffic incidents including incident detection and recovery time

Tavassoli Hojati, Ahmad, Ferreira, Luis, Washington, Simon, Charles, Phil and Shobeirinejad, Ameneh (2014) Modelling total duration of traffic incidents including incident detection and recovery time. Accident Analysis and Prevention, 71 296-305. doi:10.1016/j.aap.2014.06.006

Author Tavassoli Hojati, Ahmad
Ferreira, Luis
Washington, Simon
Charles, Phil
Shobeirinejad, Ameneh
Title Modelling total duration of traffic incidents including incident detection and recovery time
Journal name Accident Analysis and Prevention   Check publisher's open access policy
ISSN 0001-4575
Publication date 2014-10-01
Year available 2014
Sub-type Article (original research)
DOI 10.1016/j.aap.2014.06.006
Volume 71
Start page 296
End page 305
Total pages 10
Place of publication Oxford United Kingdom
Publisher Elsevier
Language eng
Abstract Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an 'integrated database' is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.
Keyword Total incident duration
Survival modelling
Motor vehicle crashes
Congestion management
Recurrent and non-recurrent congestion
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
Official 2015 Collection
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Citation counts: TR Web of Science Citation Count  Cited 11 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 12 times in Scopus Article | Citations
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