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Modelling total duration of traffic incidents including incident detection and recovery time.
Tavassoli Hojati, Ahmad; Ferreira, Luis; Washington, Simon; Charles, Phil; Shobeirinejad, Ameneh.
Afiliación
  • Tavassoli Hojati A; School of Civil Engineering, The University of Queensland, Australia. Electronic address: a.tavassoli@uq.edu.au.
  • Ferreira L; School of Civil Engineering, The University of Queensland, Australia.
  • Washington S; Faculty of Built Environment and Engineering, Queensland University of Technology, Australia.
  • Charles P; School of Civil Engineering, The University of Queensland, Australia.
  • Shobeirinejad A; School of ICT, Griffith University, Brisbane, Australia.
Accid Anal Prev ; 71: 296-305, 2014 Oct.
Article en En | MEDLINE | ID: mdl-24974360
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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Accidentes de Tránsito / Planificación Ambiental Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Oceania Idioma: En Revista: Accid Anal Prev Año: 2014 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Accidentes de Tránsito / Planificación Ambiental Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Oceania Idioma: En Revista: Accid Anal Prev Año: 2014 Tipo del documento: Article