Jointly analyzing freeway traffic incident clearance and response time using a copula-based approach

Yajie Zou, Xin Ye, Kristian Henrickson, Jinjun Tang, Yinhai Wang

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

Understanding factors that influence the duration time of incidents are important for traffic incident management agencies to design effective mitigation strategies. Previous studies have proposed different approaches for examining the impact of influential factors on incident clearance and response time. However, very few studies have considered incident clearance and response time as two dependent variables and used a joint modeling framework. The objectives of this paper are to investigate the dependence between incident clearance and response time and to examine the applicability of the copula approach to the joint analysis of these two variables. To demonstrate advantages of the proposed copula modelling framework, incident clearance and response time data collected on freeway road sections in Seattle, Washington State are examined. Parameter estimation and prediction results from the proposed copula models are presented and compared with the conventional accelerated failure time model. The modeling results suggest that the proposed copula model can better describe the estimated conditional survival probability of incident clearance time, and can provide marginally more accurate prediction results. The proposed model can also provide different inferences about effects of factors on incident clearance and response time data. Overall, the findings in this paper provide a framework for jointly modeling incident clearance and response time by considering their dependence.

Original languageEnglish (US)
Pages (from-to)171-182
Number of pages12
JournalTransportation Research Part C: Emerging Technologies
Volume86
DOIs
StatePublished - Jan 2018
Externally publishedYes

Keywords

  • Clearance time
  • Copula
  • Freeway incident
  • Response time

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications

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