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Modeling the time to the next primary and secondary incident: A semi-Markov stochastic process approach

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  • Ng, ManWo
  • Khattak, Asad
  • Talley, Wayne K.

Abstract

Incidents are notorious for their delays to road users. Secondary incidents – i.e., incidents that occur within a certain temporal and spatial distance from the first/primary incident – can further complicate clearance and add to delays. While there are numerous studies on the empirical analysis of incident data, to the best of our knowledge, an analytical model that can be used for primary and secondary incident management planning that explicitly considers both the stochastic as well as the dynamic nature of traffic does not exist. In this paper, we present such a complementary model using a semi-Markov stochastic process approach. The model allows for unprecedented generality in the modeling of stochastics during incidents on freeways. Particularly, we relax the oftentimes restrictive Poisson assumption (in the modeling of vehicle arrivals, vehicle travel times, and incidence occurrence and recovery times) and explicitly model secondary incidents. Numerical case studies are provided to illustrate the proposed model.

Suggested Citation

  • Ng, ManWo & Khattak, Asad & Talley, Wayne K., 2013. "Modeling the time to the next primary and secondary incident: A semi-Markov stochastic process approach," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 44-57.
  • Handle: RePEc:eee:transb:v:58:y:2013:i:c:p:44-57
    DOI: 10.1016/j.trb.2013.09.013
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    References listed on IDEAS

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    1. Yafeng Yin, 2008. "A Scenario-based Model for Fleet Allocation of Freeway Service Patrols," Networks and Spatial Economics, Springer, vol. 8(4), pages 407-417, December.
    2. Nam, Doohee & Mannering, Fred, 2000. "An exploratory hazard-based analysis of highway incident duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(2), pages 85-102, February.
    3. Baykal-Gürsoy, M. & Xiao, W. & Ozbay, K., 2009. "Modeling traffic flow interrupted by incidents," European Journal of Operational Research, Elsevier, vol. 195(1), pages 127-138, May.
    4. Chen, Anthony & Yang, Hai & Lo, Hong K. & Tang, Wilson H., 2002. "Capacity reliability of a road network: an assessment methodology and numerical results," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 225-252, March.
    5. Ng, ManWo & Szeto, W.Y. & Travis Waller, S., 2011. "Distribution-free travel time reliability assessment with probability inequalities," Transportation Research Part B: Methodological, Elsevier, vol. 45(6), pages 852-866, July.
    6. Rajat Jain & J. Macgregor Smith, 1997. "Modeling Vehicular Traffic Flow using M/G/C/C State Dependent Queueing Models," Transportation Science, INFORMS, vol. 31(4), pages 324-336, November.
    7. Tom Van Woensel & Nico Vandaele, 2007. "Modeling Traffic Flows With Queueing Models: A Review," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 24(04), pages 435-461.
    8. Ng, ManWo & Waller, S. Travis, 2010. "A computationally efficient methodology to characterize travel time reliability using the fast Fourier transform," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1202-1219, December.
    9. Ng, ManWo & Waller, S. Travis, 2010. "Reliable evacuation planning via demand inflation and supply deflation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1086-1094, November.
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    Cited by:

    1. Wang, Jiawen & Zou, Linzhi & Zhao, Jing & Wang, Xinwei, 2024. "Dynamic capacity drop propagation in incident-affected networks: Traffic state modeling with SIS-CTM," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    2. Wang, Zhengli & Qi, Xin & Jiang, Hai, 2018. "Estimating the spatiotemporal impact of traffic incidents: An integer programming approach consistent with the propagation of shockwaves," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 356-369.

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