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A path-based traffic assignment algorithm based on the TRANSYT traffic model

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  • Wong, S. C.
  • Yang, Chao
  • Lo, Hong K.

Abstract

This paper presents a path-based traffic assignment formulation and its solution algorithm for solving an asymmetric traffic assignment problem based on the TRANSYT traffic model, a well-known procedure to determine the queues and delays in a signal-controlled network with explicit considerations of the signal co-ordination effects and platoon dispersion on the streets. The solution algorithm employs a Frank-Wolfe method to identify the descent direction at each iteration, which requires the input of the derivatives information. A post-simulation sensitivity analysis is developed to estimate the derivatives in the TRANSYT traffic model. Good agreement of results with the values determined by numerical differentiation is obtained. Using these derivatives information, the Frank-Wolfe method shows a good convergence behavior to the equilibrium solution. Comparison with other methods is also discussed in a numerical example to demonstrate the effectiveness of the proposed methodology.

Suggested Citation

  • Wong, S. C. & Yang, Chao & Lo, Hong K., 2001. "A path-based traffic assignment algorithm based on the TRANSYT traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 35(2), pages 163-181, February.
  • Handle: RePEc:eee:transb:v:35:y:2001:i:2:p:163-181
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    1. repec:cdl:uctcwp:qt2hf4541x is not listed on IDEAS
    2. Wong, S. C., 1995. "Derivatives of the performance index for the traffic model from TRANSYT," Transportation Research Part B: Methodological, Elsevier, vol. 29(5), pages 303-327, October.
    3. Wong, S. C., 1996. "Group-based optimisation of signal timings using the TRANSYT traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 217-244, June.
    4. Meneguzzer, Claudio, 1995. "An equilibrium route choice model with explicit treatment of the effect of intersections," Transportation Research Part B: Methodological, Elsevier, vol. 29(5), pages 329-356, October.
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    2. Jang, Wonjae & Ran, Bin & Choi, Keechoo, 2005. "A discrete time dynamic flow model and a formulation and solution method for dynamic route choice," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 593-620, August.
    3. Liu, Ronghui & Smith, Mike, 2015. "Route choice and traffic signal control: A study of the stability and instability of a new dynamical model of route choice and traffic signal control," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 123-145.
    4. Chen, Anthony & Lo, Hong K. & Yang, Hai, 2001. "A self-adaptive projection and contraction algorithm for the traffic assignment problem with path-specific costs," European Journal of Operational Research, Elsevier, vol. 135(1), pages 27-41, November.
    5. Maadi, Saeed & Schmöcker, Jan-Dirk, 2017. "Optimal hyperpaths with non-additive link costs," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 235-248.
    6. Lo, Hong K. & Szeto, W. Y., 2002. "A cell-based variational inequality formulation of the dynamic user optimal assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 421-443, June.
    7. Ying, Jiang Qian & Lu, Huapu & Shi, Jing, 2007. "An algorithm for local continuous optimization of traffic signals," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1189-1197, September.
    8. C. K. Wong & Yi Liu, 2017. "Lane-Based Optimization for Macroscopic Network Configuration Designs," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-18, July.
    9. Chow, Andy H.F. & Lo, Hong K., 2007. "Sensitivity analysis of signal control with physical queuing: Delay derivatives and an application," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 462-477, May.
    10. Michael Patriksson, 2004. "Sensitivity Analysis of Traffic Equilibria," Transportation Science, INFORMS, vol. 38(3), pages 258-281, August.
    11. Luca D’Acierno & Marilisa Botte, 2021. "Railway System Design by Adopting the Merry-Go-Round (MGR) Paradigm," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    12. Han, Deren & Lo, Hong K., 2004. "Solving non-additive traffic assignment problems: A descent method for co-coercive variational inequalities," European Journal of Operational Research, Elsevier, vol. 159(3), pages 529-544, December.
    13. Wong, C. K. & Wong, S. C., 2003. "Lane-based optimization of signal timings for isolated junctions," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 63-84, January.

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