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Optimisation of timetable-based, stochastic transit assignment models based on MSA. (English) Zbl 1156.90404
Summary: Public transport assignment models have increased in complexity in order to describe passengers’ route choices as detailed and correctly as possible. Important trends in the development are (1) timetable-based assignment, (2) inclusion of feeder modes, (3) use of stochastic components to describe differences in passengers’ preferences within and between purposes and classes (random coefficients), as well as to describe non-explained variation within a utility theory framework, and (4) consideration of capacity problems at coach level, system level and terminal level. In the Copenhagen-Ringsted Model (CRM), such a large-scale transit assignment model was developed and estimated. The Stochastic User Equilibrium problem was solved by the Method of Successive Averages (MSA). However, the model suffered from very large calculation times. The paper focuses on how to optimise transit assignment models based on MSA combined with a generalised utility function. Comparable tests are carried out on a large-scale network. The conclusion is that there is potential of optimising MSA-based methods. Examples of different approaches for this is presented, tested and discussed in the paper.
90B80Discrete location and assignment
[1]Ben-Akiva, M. and Bierlaire. (1999). ”Discrete Choice Methods and their Applications to Short Term Travel Descisions.” In W. Hall (ed.), Handbook of Transportation Science. Randolph.
[2]Ben-Akiva, M., D. Bolduc, and A. Daly. (1993). ”Estimation of Travel Choice Models with Randomly Distributed Values of Time.” Transportation Research Record, 1413, 88–97.
[3]Bertsekas, D.P. (1998). Network Optimization–Continuous and Discrete Models. Athena Scientific, Belmont, Massachusetts.
[4]Bottom, J.A. (2000). Consitent Anticipatory Route Guidance. Ph.D.-afhandling.Massachusetts Istitute of Technology.
[5]Bottom, J.A. and I. Chabini. (2001). ”Accelerated Averaging methods for Fixed Point Problems in Transportation Analysis and Planning.” Triennial Symposium on Transportation Analysis (TRISTAN IV). S$ao Miguel, Azores, June. Preprints, Vol. 1/3, pp. 69–74.
[6]Brems, C.R. (2001). ”Transport Modelling with a focus on Public Transport.” Ph.D.-afhandling, der forventes publiceret i 2001, CTT/DTU.
[7]Cascetta, E. (2001). Transport System Engineering: Theory and Methods. Kluwer Academic Publishers.
[8]Cascetta, E., A. Nuzzolo, F. Russo, and A. Vivetta. (1996). ”A Modified Logit Route Choice Model Overcomming Path Overlapping Problems: Specification and Some Calibration Results for Interurban Networks.” In J.B. Lesort, (ed.), Transportation and Traffic Theory. Proceedings from the Thirteenth International Symphosium on Transportation and Traffic Theory, Lyon, France, Pergamon.
[9]Cormen, T.H., C.E. Leiserson, and R.L. Rivest (1998). Introduction to Algorithms. MIT Press.
[10]Daganzo, C.F. and Y. Sheffi. (1977). ”On Stochastic Models of Traffic Assignment.” Transportation Science 11(3), 253–274. · doi:10.1287/trsc.11.3.253
[11]de Palma, A. and C. Fontan. (2001). ”Stationarity Tests for Dynamic Traffic Simulations.” European Transport Conference (PTRC). Seminar on Methodological Innovations, Session on Networks and Assignment. CDROM with proceedings, PTRC. Cambridge, September.
[12]Dial, R.B. (1971). ”A Probabilistic Multipath Traffic Assignment Algorithm which Obviates Path Enumeration.” Transportation Research 5(2). 81–111. · doi:10.1016/0041-1647(71)90012-8
[13]Evans, S.P. (1976). ”Derivation and Analysis of Some Models for Combining Trip Distribution and Assignment.” Transportation Research, Vol. 10. Pergamon Press, UK, pp. 37–57.
[14]Florian, M. (1999). ”Deterministic Time Table Assignment.” Asian Emme/2 User Group Meeting.
[15]Florian, M. (2004). ”Finding Shortest Time-Dependent Paths in Schedule-Based Transit Networks.” In N.H.M. Wilson and A. Nuzzolo (eds.), Schedule-based dynamic transit modelling–Theory and applications, Kluwer Academic Publisher, pp. 43–52.
[16]Frank, M. and P. Wolfe. (1956). ”An Algorithm for Quadratic Programming.” Naval Research Logistics Quarterly, 3(1–2), 95–110. · doi:10.1002/nav.3800030109
[17]Lee, J.Y.S. and W.H.K. Lam. (2001). ”Pedestrian Simulation-Assignment Model for Hong Kong Mass Transit Railway Stations.” 9th World Conference on Transportation Research (WCTR), Pre-prints, session D1-01. Seoul, Korea.
[18]M$oller-Pedersen. (1999). ”Assignment Model for Timetable-Based Systems (TPSchedule).” In Proceedings of Seminar F, Transportation Planning Methods. 27th European Transport Forum (PTRC Annual Meeting), Vol. p 434. Cambridge, pp. 159–168.
[19]Nielsen, O.A. (1997). ”On the Distribution of the Stochastic Component in SUE Traffic Assignment Models 25 th European Transport Forum (PTRC Annual meeting), Proceedings.” Seminar F, Transportation Planning Methods, Vol. 2, pp. 77–94. Uxbridge, UK, 1997.
[20]Nielsen, O.A. (2000a). ”A Stochastic Transit Assignment Model Considering Differences in Passengers Utility Functions.” Transportation Research Part B Methodological 34B(5), 337–402. Elsevier Science Ltd.
[21]Nielsen, O.A. (2000b). ”Udvikling af rutevalgsmodeller–fra heuristisk til teoretisk grundlag.” Prispapir for Professor Bendtsens Mindelegat for Transport Forskeres. Trafikdage p$ra AUC, Supplementsbind. pp. 51–82.
[22]Nielsen, O.A. (2004a). ”A Large Scale Stochastic Multi-Class Schedule-Based Transit Model with Random Coefficients.” In N. Wilson and A. Nuzzolo (eds.), Schedule-Based Dynamic Transit Modelling–Theory and Applications, Chapter 4 in Book. Kluwer Academic, pp. 51–77.
[23]Nielsen, O.A. (2004b). ”Behavioural Responses to Pricing Schemes: Description of the Danish AKTA Experiment.” Journal of Intelligent Transportation Systems, 8(4). 233–251. Taylor & Francis.
[24]Nielsen, O.A. and R.D. Frederiksen. (2000). ”A Stochastic Multi-Class Road Assignment Model with Distributed Time and Cost Coefficients.” Networks and Spatial Economics, 2, 327–346. Kluwer.
[25]Nielsen, O.A., A. Daly, and C.O. Hansen. (2001). ”A Large-Scale Model System for the Copenhagen-Ringsted Railway Project.” In D. Hensher (eds.), Travel Behaviour Research: The Leading Edge, Pergamon Press, 2002. Chapter 35, pp 573–596.
[26]Nielsen, O.A. and R.D. Frederiksen. (2001). ”Optimising Timetable-Based Stochastic Transit Assignment Models.” Triennial Symposium on Transportation Analysis (TRISTAN IV). S$ao Miguel, Zores, June. Preprints, Vol. 1/3, pp. 195–200.
[27]Nielsen, O.A. and R.D. Frederiksen. (2003). ”Rule-Based, Object-Oriented Modelling of Public Transport Systems–A Description of the Transportation Object Platform.” 9th World Conference on Transportation Research (WCTR). CDRom with Selected Proceedings, Elsevier.
[28]Nielsen, O.A. and G. Jovicic. (1999). ”A Large-Scale Stochastic Timetable-Based Transit Assignment Model for Route and Sub-Mode Choices.” In Proceedings of Seminar F, Transportation Planning Methods. 27th European Transport Forum (PTRC Annual meeting), Vol. P 434, pp. 169–184. Cambridge.
[29]Nielsen, O.A., N. Simonsen, and R.D. Frederiksen. (1998). ”Stochastic User Equilibrium Traffic Assignment with Turn-delays in Intersections.” International Transactions in Operational Research 5(6), 555–568. Pergamon, Elsevier Science Ltd.
[30]Nuzollo, A., U. Crisanni, and F. Russo. (2001). ”Schedule-Based Dynamic Path Choice and Assignment Models for Public Transport Networks.” 9th World Conference on Transportation Research (WCTR), Presentation/abstract, Special Session on Route Choice models, 26/7.Seoul, Korea.
[31]Nuzzolo, A. and U. Crisalli. (2000) ”The Schedule-Based Approach in Dynamic Transit Modelling: A General Overview.” In N.H.M. Wilson and A. Nuzzolo (eds.), Schedule-Based Dynamic Transit Modelling–Theory and Applications, Kluwer Academic Publisher, pp. 1–24.
[32]Nuzzolo, A., F. Russo, and U. Crisalli. (1997). ”A Pseudo-Dynamic Assignment to Extraurban Networks Using a C-Logit Route Choice Model.” 25th European Transport Forum, Proceedings of Seminar F, Transportation Planning Methods, 2, 95–105
[33]Prashker, J.N. and S. Bekhor. (1998). Investigation of Stochastic Network Loading Procedures. Transportation Research Record, 1645, 94–102. · doi:10.3141/1645-12
[34]Sheffi, Y. (1985). Urban Transportation Networks. Prentice Hall, Inc, Englewood Cliffs, NJ.
[35]Sheffi, Y. and W.B. Powell. (1982). ”An Algorithm, for the Equilibrium Assignment Problem with Random Link Times.” Networks, 12(2), 191–207. · Zbl 0485.90082 · doi:10.1002/net.3230120209
[36]Sjöstrand, H. (2001). Passengers Evaluation in Local Public Transport, Ph.D.-thesis, Lund University, Sweeden.
[37]S$orensen, M.V. and O.A. Nielsen. (2001). ”Estimation of a Complex Stochastic Traffic Model. Assessing Distributions of Error Components in a Complex Traffic Model.” 9th World Conference on Transportation Research (WCTR), Pre-prints, session D1-01, 23/7.Seoul, Korea.
[38]S$orensen, M.V., O.A. Nielsen, and D. Filges. (2001). ”Validation and Test of a Complex Stochastic Traffic Model.” European Transport Conference (PTRC). Seminar on Methodological Innovations, Session on Networks and Assignment. CDROM with proceedings, PTRC. Cambridge, September.
[39]Van Vuren, T. (1995) ”The Trouble with SUE Stochastic Assignment Options in Practice PTRC Summer Annual Meeting, Proceedings.” Seminar H. University of Warwick, England, 1995, pp. 41–52.
[40]Vovsha, P. and S. Bekhor. (1998). ”Link-Nested Logit Model of Route Choice–Overcomming Route Overlapping Problem.” Transportation Research Record, 1645, 133–142. · doi:10.3141/1645-17
[41]Walker, W.T., T.F. Rossi, and N. Islam. (1998). ”Method of Succesive Averages Verrsus Ecans Algorithm–Iterating a Regional Travel Simulation Model to the User Equilibrium Solution.” Transportation Research Record 1645, 133–142. · doi:10.3141/1645-05
[42]Wardrop, J.G. (1952). ”Some Theoretical Aspects of Road Traffic Research.” Institution of Civil Engineers, London.