Reverse assignment: calibrating link cost functions and updating demand from traffic counts and time measurements

References

• Wardrop, JP, 1952. Some theoretical aspects of road traffic research, Proc. Inst. Civ. Eng. Part II 1 (1952), pp. 325–378.
   Google Scholar
• Beckman, M, McGuire, CB, and Winsten, CB, 1956. Studies in the Economics of Transportation. New Haven, CT: Yale University Press; 1956.
   Google Scholar
• Sheffi, Y, 1985. Urban Transportation Network. Englewood Cliffs, NJ: Prentice-Hall; 1985.
   Google Scholar
• Cantarella, GE, and Cascetta, E, 1995. Dynamic process and equilibrium in transportation networks, Transp. Sci. 29 (1995), pp. 305–329.
   Web of Science ®Google Scholar
• Ben-Akiva, M, Bierlaire, M, Koutsopoulos, H, and Mishalani, R, , DynaMIT: A simulation-based system for traffic prediction and guidance generation, TRISTAN III, San Juan, 1998.
   Google Scholar
• Mahmassani, HS, and Hawas, Y, , Data Requirement for Development, Calibration of Dynamic Traffic Models, and Algorithms for ATMS/ATIS, 76th Annual Meeting of the Transportation Research Board, Washington, DC, 1997.
   Google Scholar
• Bell, MGH, and Iida, Y, 1997. Transportation Network Analysis. Chichester: Wiley; 1997.
   Google Scholar
• Cascetta, E, 2009. Transportation Systems Analysis: Models and Applications. New York: Springer; 2009.
   Google Scholar
• Cascetta, E, and Nguyen, S, 1988. A unified framework for estimating or updating origin/destination matrices from traffic counts, Transp. Res. Part B. 22 (1988), pp. 437–455.
   Web of Science ®Google Scholar
• Van Zuylen, JH, and Willumsen, LG, 1980. The most likely trip matrix estimated from traffic counts, Transp. Res. Part B 14 (1980), pp. 281–293.
   Web of Science ®Google Scholar
• Willumsen, LG, , Estimating Time-dependent Trip Matrices from Traffic Counts, Ninth International Symposium on Transportation and Traffic Theory, VNU Science Press, Utrecht, 1984.
   Google Scholar
• Cascetta, E, 1984. Estimation of a trip matrices from traffic counts and survey data: A generalized least square estimator, Transp. Res. Part B 18 (1984), pp. 289–299.
   Web of Science ®Google Scholar
• Bell, MGH, 1991. The estimation of Origin/Destination matrices by constrained generalised least squares, Transp. Res. Part B 25 (1991), pp. 13–22.
   Web of Science ®Google Scholar
• Maher, MI, 1983. Interferences on trip matrices from observations on link volumes: A Bayesian statistical approach, Transp. Res. Part B 17 (1983), pp. 435–447.
   Web of Science ®Google Scholar
• Brenninger-Gothe, M, Jornsten, KO, and Lundgren, JT, 1989. Estimation of origin/destination matrices from traffic counts using multiobjective programming formulation, Transp. Res. Part B 23 (1989), pp. 257–269.
   Web of Science ®Google Scholar
• Ben-Akiva, M, Macke, PP, and Hsu, PS, , Alternative methods to estimate route-level trip tables and expand on-board surveys, Transportation Research Record 1037, Transportation Research Board, Washington, DC, 1985.
   Google Scholar
• McNeil, S, , Quadratic matrix entry estimation methods, Ph.D. diss., Department of Civil Engineering, Carnegie-Mellon University, Pittsburgh, PA, 1983.
   Google Scholar
• Nguyen, S, 1984. "Estimating origin-destination matrices from observed flows". In: Florian, M, ed. Transportation Planning Models. Amsterdam: Elsevier Science Publishers B.V. (North Holland); 1984. pp. 137–152.
   Google Scholar
• Hazelton, ML, 2000. Estimation of origin-destination matrices from link flows on uncongested networks, Transp. Res. Part B 34 (2000), pp. 549–566.
   Web of Science ®Google Scholar
• Chen, Y, and Florian, M, , O/D demand adjustment problem with congestion. Part I. model analysis and optimality conditions, CRT Publication 56, CRT Université de Montreal, Montreal, 1994.
   Google Scholar
• Fisk, CS, 1988. On combining maximum entropy trip matrix estimation with user optimal assignment, Transp. Res. Part B 22 (1988), pp. 69–79.
   Web of Science ®Google Scholar
• Florian, M, and Chen, Y, 1995. A coordinate descent method for the bi-level O/D matrix adjustment problem, Int. Trans. Oper. Res. 2 (1995), pp. 165–179.
   Google Scholar
• Yang, H, 1995. Heuristic algorithms for the bilevel origin/destination matrix estimation problem, Transp. Res. Part B 29 (1995), pp. 231–242.
   Web of Science ®Google Scholar
• Bell, MGH, Lam, WHK, and Iida, Y, , A Time-dependent Multiclass Path Flow Estimator, Proceedings of 13th Symposium on Transportation and Traffic Theory, Lyon, July, 1996.
   Google Scholar
• Ly, B, and De Moor, B, 2002. Dynamic identification of origin-destination matrices in the presence of incomplete observations, Transp. Res. Part B 36 (2002), pp. 37–57.
   Web of Science ®Google Scholar
• Cascetta, E, and Postorino, MN, 2001. Fixed point models for the estimation of O/D matrices using traffic counts on congested networks, Transp. Sci. 35 (2001), pp. 134–147.
   Web of Science ®Google Scholar
• Nguyen, S, , Estimating an O/D matrix from network data: A network equilibrium approach, CRT Publication 60/87, CRT Université de Montreal, Montreal, 1977.
   Google Scholar
• Hogberg, P, 1976. Estimation of parameters in models for traffic prediction: A non-linear regression approach, Transp. Res. Part B 10 (1976), pp. 263–265.
   Google Scholar
• Willumsen, LG, 1981. Simplified transport models based on traffic count, Transportation 10 (1981), pp. 257–278.
   Web of Science ®Google Scholar
• Cascetta, E, , A class of travel demand estimators using traffic flows, CRT Publication 375, CRT Université de Montreal, Montreal, 1986.
   Google Scholar
• Willumsen, LG, and Tamin, OZ, 1989. Transport demand model estimation from traffic counts, Transportation 16 (1989), pp. 3–26.
   Web of Science ®Google Scholar
• Cascetta, E, and Russo, F, 1997. Calibrating aggregate travel demand models with traffic counts: Estimators and statistical performance, Transportation 24 (1997), pp. 271–293.
   Web of Science ®Google Scholar
• Yang, H, Bell, MGH, and Meng, Q, 2001. Simultaneous estimation of the origin destination matrices and travel cost coefficient for congested networks in a stochastic user equilibrium, Transp. Sci. 35 (2001), pp. 107–123.
   Web of Science ®Google Scholar
• García-Ródenas, R, and Marín, Á, 2009. Simultaneous estimation of the origin–destination matrices and the parameters of a nested logit model in a combined network equilibrium model, Eur. J. Oper. Res. 197 (2009), pp. 320–331.
   Web of Science ®Google Scholar
• Xu, G, Chan, KS, and Lam, WHK, 2004. Integrated approach for trip matrix updating and network calibration, J. Transp. Eng. 130 (2) (2004), pp. 231–244.
   Google Scholar
• Holland, JH, 1975. Adaptation in Natural and Artificial Systems. Ann Arbor, MI: The University of Michigan Press; 1975.
   Google Scholar
• Goldberg, DE, 1989. Genetic Algorithms in Search. Boston, MA: Optimization and Machine Learning, Addison-Wesley; 1989.
   Google Scholar
• Lobo, FG, Lima, CF, and Michalewicz, Z, 2007. Parameter Settings in Evolutionary Algorithms. Heidelberg: Springer; 2007.
   Google Scholar
• Russo, F, and Vitetta, A, 2006. A topological method to choose optimal solutions after solving the multi-criteria urban road network design problem, Transportation 33 (2006), pp. 347–370.
   Web of Science ®Google Scholar
• Cantarella, GE, Pavone, G, and Vitetta, A, 2006. Heuristics for urban road network design: Lane layout and signal settings, Eur. J. Oper. Res. 175 (2006), pp. 1682–1695.
   Web of Science ®Google Scholar
• Bureau of Public Roads, Traffic assignment manual, US Department of Commerce, Planning Division, Washington, DC, 1964.
   Google Scholar
• TRRL, A study of speed/flow/geometry relations on rural single carriageways, Leaflet LF 923, 1980.
   Google Scholar
• TRRL, Speed/flow/geometry relations on rural single carriageways, Leaflet LF 924, 1980.
   Google Scholar
• TRRL, Changes in speeds on rural roads, Leaflet LF 925, 1980.
   Google Scholar
• Transportation Research Board, Highway capacity manual, Transportation Research Board, Washington, DC, 1985.
   Google Scholar
• Srinivasan, K, and Jovanis, P, 1996. Determination of number of probe vehicles required for reliable travel time measurement in urban network. Washington, DC: Transportation Research Record 1537; 1996, pp. 15–22.
   Google Scholar
• Bolla, R, Davoli, F, and Giordano, A, , Estimating Road Traffic Parameters from Mobile Communications, 7th World Congress on ITS, Turin, 2000.
   Google Scholar
• Ishida, H, Mura, H, and Okamoto, N, , Sampling Rates for Travel Speed Survey with Car Navigation System, 7th World Congress on 1TS, Turin, 2000.
   Google Scholar
• Lehmann, H, and Kwella, B, 1998. Empirical traffic flow modelling: Floating cars in urban networks, Trans. Soc. Comput. Simul. Int. 15 (3) (1998), pp. 133–136.
   Google Scholar
• Mussone, L, Deflorio, F, and Mascia, M, 2001. Potenzialità dei sistemi di monitoraggio veicolare basato su floating car data, Trasporti e Trazione. 2 (2001), p. 51.
   Google Scholar
• Astarita, V, 2002. Analisi preliminare delle possibilità offerte nel controllo e regolazione del traffico dalla localizzazione dei telefoni cellulari sulle reti stradali. Metodi e Tecnologie dell'Ingegneria dei Trasporti Seminario 2000; 2002. pp. 552–566.
   Google Scholar
• Hoose, N, 1991. Computer Image Processing in Traffic Engineering. Taunton: Research Studies Press; 1991.
   Google Scholar
• Torday, A, and Dumont, AG, , Probe vehicles based travel time estimation in urban networks, Preprints of TRISTAN V, Guadeloupe, 2004.
   Google Scholar
• Friedrich, B, Heinig, K, and Matschke, I, , Data fusion technique in the context of traffic state estimation, TRISTAN V, Guadeloupe, 2004.
   Google Scholar
• Liu, S, and Fricker, J, 1996. Estimation of a trip table and the θ parameter in a stochastic network, Transp. Res. 30A (1996), pp. 287–305.
   Google Scholar
• Kunde, K, , Calibration of mesoscopic traffic simulation models for dynamic traffic assignment, Master's thesis, Massachusetts Institute of Technology, 2002.
   Google Scholar
• Antoniou, C, , Online calibration for dynamic traffic assignment, Ph.D. diss., Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 2004.
   Google Scholar
• Balakrishna, R, Koutsopoulos, HN, and Ben-Akiva, M, , Simultaneous Offline Demand and Supply Calibration of Dynamic Traffic Assignment Systems, 85th Annual Meeting of the Transportation Research Board, Washington, DC, 2006.
   Google Scholar
• Balakrishna, R, Ben-Akiva, M, and Koutsopoulos, HN, , Off-line Calibration of Dynamic Traffic Assignment: Simultaneous Demand-supply Estimation, 86th Annual Meeting of the Transportation Research Board, Washington, DC, 2007.
   Google Scholar
• Bilegan, IC, Cosenza, CAN, Gonzàlez-Rojo, S, and Mora-Camino, F, 2007. A maximum entropy approach to update airlines demand distributions, Inverse Probl. Sci. Eng. 15 (1) (2007), pp. 19–29.
   Web of Science ®Google Scholar
• Handou, A, Oumarou, A, Mancel, C, and Mora-Camino, F, 2009. A two level optimization approach for long-term planning in a large air transportation network, Inverse Probl. Sci. Eng. 17 (2) (2009), pp. 275–286.
   Web of Science ®Google Scholar
• Cantarella, GE, 1997. A general fixed point approach to multi-mode multi-user equilibrium assignment with elastic demand enumeration, Transp. Sci. 29 (1997), pp. 107–128.
   Google Scholar
• Sheffi, Y, and Powell, WB, 1981. A comparison of stochastic and deterministic traffic assignment over congested network, Transp. Res. Part B 15 (1981), pp. 53–64.
   Web of Science ®Google Scholar
• Russo, F, and Vitetta, A, 2003. An assignment model with modified Logit, which obviates enumeration and overlapping problems, Transportation 30 (2003), pp. 177–201.
   Web of Science ®Google Scholar
• Leyffer, S, , Mathematical programs with complementarity constraints, Technical Report ANL/MCS-P1026-0203, Argonne National Laboratory, Argonne, IL, 2003.
   Google Scholar