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

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.

• Record URL:
  • https://doi.org/10.1016/j.trc.2017.11.004
• Record URL:
  • https://www.sciencedirect.com/science/article/pii/S0968090X17303108
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Zou, Yajie
  • Ye, Xin
  • Henrickson, Kristian
  • Tang, Jinjun
  • Wang, Yinhai
  • 0000-0002-4180-5628
• Publication Date: 2018-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 171-182
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 86
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Freeways; Traffic incidents
• Candidate Terms: Copula-based models
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01660568
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 20 2018 9:31AM