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Risk-Averse Traffic Assignment with Elastic Demands: NCP Formulation and Solution Method for Assessing Performance Reliability

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Listed:
  • W. Szeto
  • L. O'Brien
  • M. O'Mahony

Abstract

How reliable the transport network is greatly affects the mobility and economy of a country. To assess the reliability of the network accurately and design a reliable transport network properly, one should consider the risk taking and elastic behaviour of travel demand. This paper develops a Nonlinear Complementarity Problem (NCP) formulation considering this behaviour. The NCP formulation is transformed to a smooth and unconstrained mathematical program via a Fischer function and then solved by the proposed modified αBB (branch and bound) algorithm, while guaranteeing finite convergence to a point arbitrarily close to the global minimum (ɛ-convergence). To speed up the computation, a sampling method is suggested. A small numerical study is set up to illustrate the properties and the performance of the algorithm. The results show that the bound improving strategy, the sampling size on estimating the value of α for the convex lower bounding function, and choice of α have a strong influence of the rate of convergence. Copyright Springer Science + Business Media, LLC 2006

Suggested Citation

  • W. Szeto & L. O'Brien & M. O'Mahony, 2006. "Risk-Averse Traffic Assignment with Elastic Demands: NCP Formulation and Solution Method for Assessing Performance Reliability," Networks and Spatial Economics, Springer, vol. 6(3), pages 313-332, September.
  • Handle: RePEc:kap:netspa:v:6:y:2006:i:3:p:313-332
    DOI: 10.1007/s11067-006-9286-7
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    References listed on IDEAS

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    1. 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.
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    Citations

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    Cited by:

    1. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    2. Chen, Anthony & Zhou, Zhong & Lam, William H.K., 2011. "Modeling stochastic perception error in the mean-excess traffic equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1619-1640.
    3. 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.
    4. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    5. Watling, David & Balijepalli, N.C., 2012. "A method to assess demand growth vulnerability of travel times on road network links," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 772-789.
    6. Connors, Richard D. & Sumalee, Agachai, 2009. "A network equilibrium model with travellers' perception of stochastic travel times," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 614-624, July.
    7. Zhi-Chun Li & William Lam & S. Wong, 2009. "The Optimal Transit Fare Structure under Different Market Regimes with Uncertainty in the Network," Networks and Spatial Economics, Springer, vol. 9(2), pages 191-216, June.
    8. Nie, Yu (Marco), 2011. "Multi-class percentile user equilibrium with flow-dependent stochasticity," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1641-1659.
    9. 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.
    10. ManWo Ng & Hong Lo, 2013. "Regional Air Quality Conformity in Transportation Networks with Stochastic Dependencies: A Theoretical Copula-Based Model," Networks and Spatial Economics, Springer, vol. 13(4), pages 373-397, December.
    11. Prakash, A. Arun & Seshadri, Ravi & Srinivasan, Karthik K., 2018. "A consistent reliability-based user-equilibrium problem with risk-averse users and endogenous travel time correlations: Formulation and solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 171-198.
    12. Xiangdong Xu & Anthony Chen & Lin Cheng, 2013. "Assessing the effects of stochastic perception error under travel time variability," Transportation, Springer, vol. 40(3), pages 525-548, May.
    13. Michael W. Levin & Melissa Duell & S. Travis Waller, 2020. "Arrival Time Reliability in Strategic User Equilibrium," Networks and Spatial Economics, Springer, vol. 20(3), pages 803-831, September.
    14. Xu, Xiangdong & Chen, Anthony & Cheng, Lin & Yang, Chao, 2017. "A link-based mean-excess traffic equilibrium model under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 53-75.
    15. Wang, Judith Y.T. & Ehrgott, Matthias & Chen, Anthony, 2014. "A bi-objective user equilibrium model of travel time reliability in a road network," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 4-15.
    16. Chen, Anthony & Zhou, Zhong, 2010. "The [alpha]-reliable mean-excess traffic equilibrium model with stochastic travel times," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 493-513, May.
    17. Li-Jun Tian & Hai-Jun Huang & Zi-You Gao, 2012. "A Cumulative Perceived Value-Based Dynamic User Equilibrium Model Considering the Travelers’ Risk Evaluation on Arrival Time," Networks and Spatial Economics, Springer, vol. 12(4), pages 589-608, December.
    18. Szeto, W.Y. & Farahani, R.Z. & Sumalee, Agachai, 2017. "Link-based multi-class hazmat routing-scheduling problem: A multiple demon approach," European Journal of Operational Research, Elsevier, vol. 261(1), pages 337-354.
    19. Xiangfeng Ji & Xuegang (Jeff) Ban & Mengtian Li & Jian Zhang & Bin Ran, 2017. "Non-expected Route Choice Model under Risk on Stochastic Traffic Networks," Networks and Spatial Economics, Springer, vol. 17(3), pages 777-807, September.

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