Reliability-based network flow estimation with day-to-day variation: A model validation on real large-scale urban networks

References

• Aashtiani, H. Z., & Magnenti, T. L. (1981). Equilibria on a congested network. SIAM J Alg Disc Meth, 2(3), 213–226. doi:10.1137/0602024.
   Google Scholar
• Apostol, T. M. (1967). Calculus, Vol. 2, New York: John Wiley & Sons.
   Google Scholar
• Arena Simulation Software (2010). Rockwell Automation, Inc. https://www.arenasimulation.com
   Google Scholar
• Asakura, Y. (2006). Travel Time Reliability, 3rd COE Symposium. Seattle: University of Washington.
   Google Scholar
• Avineri, E., & Prashker, J. N. (2005). Sensitivity to travel time variability: Travelers' learning perspective, Transportation Research-Part C, 13, 157–183. doi:10.1016/j.trc.2005.04.006.
   Web of Science ®Google Scholar
• Beard, J. R., & Beard, C. (1854). Cassell's Latin Dictionary: In Two Parts. I. Latin-English; II. English-Latin, London: Oxford University Press (Digitized by Google 2006).
   Google Scholar
• Bhat, C. R., & Eluru, N. (2009). A copula-based approach to accommodate residential self-selection effects in travel behavior modeling. Transportation Research-Part B, 43(7), 749–765. doi:10.1016/j.trb.2009.02.001.
   Google Scholar
• Chen, A., & Recker, W. W. (2000). Considering risk taking behavior in travel time reliability, UCI-ITS-WP-00-24, Institute of Transportation Studies. Irvine: University of California.
   Google Scholar
• Chen, A., Ji, Z., & Recker, W. (2001). Travel time reliability with risk sensitive travelers, UCI-ITS-TS-WP-01-8, Institute of Transportation Studies. Irvine: University of California.
   Google Scholar
• Chen, C. H., Skabardonis, A., & Varaiya, P. (2003). Travel time reliability as a measure of service. Transportation Research Record, 1855, 74–79. doi:10.3141/1855-09.
   Google Scholar
• Clark, S., & Watling, D. (2005). Modeling network travel time reliability under stochastic demand. Transportation Research–Part B, 39, 119–140. doi:10.1016/j.trb.2003.10.006.
   Google Scholar
• Delhome, R., Billot, R., & El Faouzi, N.-E. (2017). Travel time statistical modeling with the Halphen distribution family, Journal of Intelligent Transportation Systems, 6(6), 1–13.
   Google Scholar
• dos Santos Silva, R., & Freitas Lopes, H. (2008). Copula, marginal distributions and model selection: A Bayesian note. Stat Comput, 18, 313–320. doi:10.1007/s11222-008-9058-y.
   Web of Science ®Google Scholar
• El Faouzi, N.-E., & Maurin, M. (2007). Reliability metrics for path travel time under log-normal distribution. The Netherlands: 3rd International Symposium on Transportation Network Reliability.
   Google Scholar
• Fang, Y., Madsen, L., & Liu, L. (2014). Comparison of two methods to check copula fitting. IAENG International Journal of Applied Mathematics, 44(1), 07
   Google Scholar
• FHWA (2006). Report: Traffic congestion and reliability trends and advanced strategies for congestion mitigation, prepared by Cambridge Systematic, with Texas Transportation Institute, http://ops.fhwa.dot.gov/congestion_report/
   Google Scholar
• Herman, R., & Lam, T. (1974). Trip characteristics of journeys to and from work. Proceedings of the 6th International Symposium on Transportation and Traffic Theory. Sydney: AH and AW Reed, 57–85.
   Google Scholar
• Higatani, A., Kitazawa, T., Tanabe, J., Suga, Y., Sekhar, R., & Asakura, Y. (2009). Empirical analysis of travel time reliability measures in Hanshin Expressway network. Journal of Intelligent Transportation Systems, 13(1), 28–38. doi:10.1080/15472450802644454.
   Web of Science ®Google Scholar
• INRO (1999). EMME/2 User Manual, Software release 9, Montreal, Canada.
   Google Scholar
• ITSR: Institute for Transportation Studies and Research. (1994). The traffic assignment model for the city of Mashhad and the performance of the network in this city, Report No. 76-09, Sharif University of Technology, Tehran (in Farsi).
   Google Scholar
• ITSR: Institute for Transportation Studies and Research. (2000). The traffic assignment model for the city of Shiraz and the performance of the network in this city, Report No. 79-17, Sharif University of Technology, Tehran (in Farsi).
   Google Scholar
• ITSR: Institute for Transportation Studies and Research. (2004). The proposed bus rapid transit system for the city of Mashhad, Report No. 87-02, Sharif University of Technology, Tehran (in Farsi).
   Google Scholar
• ITSR: Institute for Transportation Studies and Research. (2006). Evaluation of the transportation system for the city of Shiraz in 2021 horizon to pinpoint the intersection bottlenecks, Report No. 85-01, Sharif University of Technology, Tehran (in Farsi).
   Google Scholar
• Joe, H. (1997). Multivariate Models and Dependence Concepts. London: Chapman & Hall.
   Google Scholar
• König, A., & Axhausen, K. W. (2002). The reliability of the transportation system and its influence on the choice behavior, 2nd Swiss Transport Research Conference, Monte Verita, March 20–22.
   Google Scholar
• Lam, W. H. K., Shao, H., & Sumalee, A. (2008). Modelling impacts of adverse weather conditions on a road network with uncertainties in demand and supply. Transportation Research, Part B, 42(10), 890–910. doi:10.1016/j.trb.2008.02.004.
   Google Scholar
• Lei, F., Wang, Y., Lu, G., & Sun, J. (2014). A travel time reliability model of urban expressways with varying level of service. Transportation Research, Part C, 48, 453–467. doi:10.1016/j.trc.2014.09.019.
   Web of Science ®Google Scholar
• Lo, H. K., & Tung, Y. K. (2003). Network with degradable links: Capacity analysis and design. Transportation Research, Part B, 37 (4), 345–363. doi:10.1016/S0191-2615(02)00017-6.
   Google Scholar
• Lo, H. K., Luo, X. W., & Siu, B. W. Y. (2006). Degradable transport network: Travel time budget of travellers with heterogeneous risk aversion. Transportation Research, Part B, 40 (9), 792–806. doi:10.1016/j.trb.2005.10.003.
   Google Scholar
• Loustau, P., Morency, C., & Trepanier, M. (2010). Measuring, describing and modeling travel time reliability. Proceedings of TRB Annual Meeting, Washington D.C., 1–14.
   Google Scholar
• MATLAB and Statistics Toolbox, Release. (2012b). The MathWorks, Inc., Natick, MA, USA.
   Google Scholar
• Melchiori, M. R. (2003). Which Archimedean Copula Is the Right One? 3rd Version, e-journal: www.YieldCurve.com. Univ. Nacional del Litoral, Santa Fe, Argentina, 1–18.
   Google Scholar
• Nelsen, R. B.(1999). An Introduction to Copulas. New York: Springer Verlag.
   Google Scholar
• Ng, M. W., Kockelman, K., & Waller, T. (2010). Relaxing the multivariate normality assumption in the simulation of transportation system dependencies. Transportation Letters: The International Journal of Transportation Research, 2(2), 63–74. doi:10.3328/TL.2010.02.02.63-74.
   Web of Science ®Google Scholar
• Ng, M. W., Szeto, W. Y., & Waller, S. T. (2011). Distribution-free travel time reliability with probability inequalities. Transportation Research-Part B, 45, 852–866. doi:10.1016/j.trb.2011.03.003.
   Google Scholar
• Ng, M. W., & Waller, S. T. (2010). A computationally efficient methodology to characterize travel time reliability using a fast Fourier transform. Transportation Research-Part B, 44, 1202–1219. doi:10.1016/j.trb.2010.02.008.
   Google Scholar
• Pel, A. J., & Nicholson, A. J. (2013). Network effects of percentile-based route choice behavior for stochastic travel times under exogenous capacity variations. Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC), The Hague, The Netherlands, Oct. 6–9.
   Google Scholar
• Poorzahedy, H., & Shetab Bushehri, S. N. (2006). Pessimistic equilibrium flow and its network design implications. European Journal of Transport and Infrastructure Research, 6(2), 113–130.
   Google Scholar
• Pu, W. (2011). Analytic relationships between travel time reliability measures, TRB Annual meeting, Washington, DC.
   Google Scholar
• Qi, J., Sim, M., Sun, D., & Yuan, X.-M. (2010). Preferences for Travel Time under Risk and Ambiguity: Implications in Path Selection and Network Equilibrium. Accessed June 2016 www.math.nus.edu.sg/∼matsundf/
   Google Scholar
• Rakha, H., El-Shawarby, I., & Arafeh, M. (2010). Trip travel-time reliability: Issues and proposed solutions. Journal of Intelligent Transportation Systems, 14(4), 232–250. doi:10.1080/15472450.2010.517477.
   Web of Science ®Google Scholar
• R Core Team. (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. R i386 3.0.2, URL http://www.R-project.org/. More information at https://stat.ethz.ch/R-manual/R-devel/library/stats/html/ks.test.html.
   Google Scholar
• Richardson, A. G., & Taylor, M. A. P. (1978). A study of travel time variability on commuter journeys. High Speed Ground Transportation Journal, 2(1), 77–91.
   Google Scholar
• Saw, K., Joshi, G. J., & Katti, B. K. (2015). Measures of travel time variability and reliability and its improvement strategies. Urban Transport Journal, 14(1), 39–52.
   Google Scholar
• Sekhar, C. R., Iryo, T., & Asakura, Y. (2012). Analysis of travel-time variation over multiple sections of Hanshin expressway in Japan. Current Science, 102(11), 1527–1533.
   Web of Science ®Google Scholar
• Sekhar, C. R., Kitazawa, T., Tanabe, J., Suga, Y., & Asakura, Y. (2007). Examining travel time reliability on Han-Shin Expressway network. Journal of the Eastern Asia Society for Transportation Studies, 7, 2274–2288.
   Google Scholar
• Sener, I. N., & Bhat, C. R. (2011). A copula-based sample selection model of telecommuting choice and frequency. Environment and Planning A, 43(1), 126–145. doi:10.1068/a43133.
   Web of Science ®Google Scholar
• Sheffi, Y. (1985). Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods. New Jersey: Prentice-Hall, Inc.
   Google Scholar
• SPSS Statistics 19.0 (2010). IBM SPSS statistics for windows. Armonk, NY.
   Google Scholar
• Stanley Smith, M. (2012). Bayesian approaches to copula modeling. In P. Damien, P. Dellaportas, N. Polson, & D. Stephens (Eds.), Hierarchical Models and MCMC: A Tribute to Adrian Smith. London: Oxford University Press.
   Google Scholar
• Sumalee, A., Watling, D. P., & Nakayama, S. H. (2006). Reliable network design problem: The case with uncertain demand and total travel time reliability, Proceedings of TRB Annual Meeting, Washington, D.C.
   Google Scholar
• Szeto, W. Y., Jiang, Y., & Sumalee, A. (2011). A cell-based model for multi-class doubly stochastic dynamic traffic assignment. Computer-Aided Civil And Infrastructure Engineering, 26(8), 595–611. doi:10.1111/j.1467-8667.2011.00717.x.
   Web of Science ®Google Scholar
• Taylor, M. A. P. (1999). Dense network traffic models, travel time reliability and traffic management (II) application to network reliability. Journal of Advanced Transportation, 33(2), 235–251. doi:10.1002/atr.5670330210.
   Web of Science ®Google Scholar
• TCTTC: Tehran Comprehensive Transportation and Traffic Company. (2011). The traffic assignment model for the city of Tehran and the performance of the network in this city. Unpublished report, Tehran.
   Google Scholar
• Torkjazi, M. (2011). Estimating traffic flows in urban networks with day-to-day travel time fluctuations. MSc. Thesis in Transportation Engineering, Dept. of Civil Eng., Sharif University of Technology, Tehran.
   Google Scholar
• Waller, S. T., Fajardo, D., Duell, M., & Dixit, V. (2013). Linear programming formulation for strategic dynamic assignment. Networks and Spatial Economics, 13, 427–443.
   Google Scholar
• Wang, J. Y. T., Ehrgott, M., & Chen, A. (2014). A bi-objective user equilibrium model of travel time reliability in a road network. Transportation Research, Part B, 66, 4–15. doi:10.1016/j.trb.2013.10.007.
   Google Scholar
• Watling, D. P. (2006). User equilibrium traffic network assignment with stochastic travel times and late arrival penalty. European Journal of Operational Research, 175(3), 1539–1556. doi:10.1016/j.ejor.2005.02.039.
   Web of Science ®Google Scholar
• Watling, D. (2008). Modeling and evaluation of reliability impacts in road networks: Concepts and methods for traffic assignment models. Association for European Transport and contributors. Institute for Transport Studies, University of Leeds, Leeds, UK.
   Google Scholar
• Yin, Y., & Ieda, H. (2001). Assessing travel time reliability of road networks considering day-to-day travel variations. Journal of the Eastern Asia Society for Transportation Studies, 4(2), 125–137.
   Google Scholar
• Yin, Y., Lam, W. H. K., & Iida, H. (2004). New technology and the modeling of risk-taking behavior in congested road networks. Transportation Research-Part C, 12, 171–192. doi:10.1016/j.trc.2004.07.009.
   Web of Science ®Google Scholar
• Zhang, L. (2012). Travel time reliability as an emergent property of transportation networks. TRB Annual Meeting, Washington, DC.
   Google Scholar
• Zhang, W.-Y., Guan, W., Song, L.-Y., & Sun, H.-J. (2013). Alpha-reliable combined mean traffic equilibrium model with stochastic travel times. Journal of Central South University of Technology, 20(12), 3770–3778. doi:10.1007/s11771-013-1906-z.
   Web of Science ®Google Scholar