1. bookVolume 22 (2021): Issue 3 (June 2021)
Journal Details
First Published
20 Mar 2000
Publication timeframe
4 times per year
Open Access

Travel Demand Estimation in Urban Road Networks as Inverse Traffic Assignment Problem

Published Online: 22 Jun 2021
Volume & Issue: Volume 22 (2021) - Issue 3 (June 2021)
Page range: 287 - 300
Journal Details
First Published
20 Mar 2000
Publication timeframe
4 times per year

1. Bar-Gera, H. (2006) Primal method for determining the most likely route flows in large road network. Transport. Sci. 40 (3), 269-286.10.1287/trsc.1050.0142 Search in Google Scholar

2. Beckman, M., C. B. McGuire, and C. B. Winsten. (1956) Studies in economics of transportation. New Haven, CT: Yale University Press. Search in Google Scholar

3. Bell, M. G. H. (1983) The Estimation of an Origin-Destination Matrix from Traffic Counts. Transportation Science. 17 (2), 198–217.10.1287/trsc.17.2.198 Search in Google Scholar

4. Bell, M. G. H. (1991) The Estimation of Origin-Destination Matrices by Constrained Generalised Least Squares. Transportation Research Part B. 25 (1), 13–22.10.1016/0191-2615(91)90010-G Search in Google Scholar

5. Bell, M. G., C. M. Shield, F. Busch, and C. Kruse. (1997) A stochastic user equilibrium path flow estimator. Transport. Res. Part C. 5 (34), 197–210.10.1016/S0968-090X(97)00009-0 Search in Google Scholar

6. Bianco, L., C. Cerrone, R. Cerulli, and M. Gentili. (2014) Locating sensors to observe network arc flows: exact and heuristic approaches. Computers and Operation Research. 46, 12–22.10.1016/j.cor.2013.12.013 Search in Google Scholar

7. Bierlaire, M. (2002) The total demand scale: a new measure of quality for static and dynamic origin-destination trip tables. Transportation Research Part B. 36, 837–850.10.1016/S0191-2615(01)00036-4 Search in Google Scholar

8. Brenninger-Gothe, M., Jornsten, K. O. and Lundgren, J. T. (1989) Estimation of origin-destination matrices from traffic counts using multiobjective programming formulations. Transportation Research Part B. 23 (4), 257–269.10.1016/0191-2615(89)90028-3 Search in Google Scholar

9. Cantelmo, G., M. Qurashi, A. A. Prakash, C. Antoniou, and F. Viti. (2019) Incorporating trip chaining within online demand estimation. Transportation Research Part B. Article in Press.10.1016/j.trpro.2019.05.025 Search in Google Scholar

10. Carey, M., C. Hendrickson, K. Siddharthan. (1981) A method for direct estimation of origin/destination trip matrices. Transport. Sci. 15 (1), 32–49.10.1287/trsc.15.1.32 Search in Google Scholar

11. Cascetta, E. (1984) Estimation of trip matrices from traffic counts and survey data: a generalized least squares estimator. Transportation Research Part B. 18, 289–299.10.1016/0191-2615(84)90012-2 Search in Google Scholar

12. Castillo, E., J. Menedez, P. Jimenez. (2008) Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations. Transportation Research Part B. 42, 455–481.10.1016/j.trb.2007.09.004 Search in Google Scholar

13. Castillo, E., J. Menendez, S. Sanchez-Cambronero. (2008) Traffic estimation and optimal counting location without path enumeration using Bayesian networks. Computer Aided Civil and Infrastructure Engineering. 23(3), 189–207.10.1111/j.1467-8667.2008.00526.x Search in Google Scholar

14. Castillo, E., M. Nogal, A. Rivas, and S. Sanchez-Cambronero. (2013) Observability of traffic networks. Optimal location of counting and scanning devises. Transportmetrica B: Transport Dynamics. 1(1), 68–102. Search in Google Scholar

15. Cheng, L., S. Zhu, Z. Chu, and J. Cheng. (2014) A bayesian network model for origin-destination matrices estimation using prior and some observed link flows. Discrete Dyn. Nature Soc.10.1155/2014/192470 Search in Google Scholar

16. Chootinan, P., A. Chen, H. Yang. (2005) A bi-objective traffic location problem of origin-destination trip table estimation. Transportmetrica. 1, 65–80.10.1080/18128600508685639 Search in Google Scholar

17. Doblas, J., F. G. Benitez. (2005) Estimation of trip matrices from traffic counts and survey data: a generalized least squares estimator. Transportation Research Part B: Methodological. 39(7), 565–591.10.1016/j.trb.2004.06.006 Search in Google Scholar

18. Ehlert, A., M. Bell, S. Grosso. (2006) The optimisation of traffic count locations in road networks. Transportation Research Part B: Methodological. 40, 460–479.10.1016/j.trb.2005.06.001 Search in Google Scholar

19. Eisenman, S., X. Fei, X. Zhou, and H. Mahmassani. (2006) Number and location of sensors for real-time network traffic estimation and prediction. Transportation Research Record: Journal of the Transportation Research Board. 2006, 253–259.10.1177/0361198106196400128 Search in Google Scholar

20. Fisher, F. (1962) A Priori Information and Time Series Analysis. North-Holland Publishing Co. Search in Google Scholar

21. Fisk, C. (1988) On combining maximum entropy trip matrix estimation with user optimal assignment. Transport. Res. Part B. 22 (1), 69–73.10.1016/0191-2615(88)90035-5 Search in Google Scholar

22. Frank, M., and P. Wolfe. (1956) An algorithm for quadratic programming. Naval Research Logistics Quarterly. 3, 95–110.10.1002/nav.3800030109 Search in Google Scholar

23. Frederix, R., F. Viti, and C. M. J. Tampere. (2013) Dynamic origin-destination estimation in congested networks: theoretical findings and implications in practice. Transportmetrica A: Transport Science. 9 (6), 494–513.10.1080/18128602.2011.619587 Search in Google Scholar

24. Gan, L., H. Yang, and S. Wong. (2005) Traffic counting location and error bound in origin-destination matrix estimation problems. Journal of Transportation Engineering. 131 (7), 524–534.10.1061/(ASCE)0733-947X(2005)131:7(524) Search in Google Scholar

25. De Grange, L., F. Gonzalez, and S. Bekhor. (2017) Path flow and trip matrix estimation using link flow density. Networks Spatial Econ. 17 (1), 173–195.10.1007/s11067-016-9322-1 Search in Google Scholar

26. Gunn, H. (2001) Spatial and temporal transferability of relationships between travel demand, trip cost and travel time. Transportation Research Part E. 37, 163–189.10.1016/S1366-5545(00)00023-5 Search in Google Scholar

27. Hazelton, M. L. (2000) Estimation of origin-destination matrices from link flows on uncongested networks. Transportation Research Part B. 34, 549–566.10.1016/S0191-2615(99)00037-5 Search in Google Scholar

28. Hazelton, M. L. (2001) Inference for origin-destination matrices: estimation, prediction and reconstruction. Transportation Research Part B. 35, 667–676.10.1016/S0191-2615(00)00009-6 Search in Google Scholar

29. Hernandez, M. V. C., L. H. J. Valencia, and Y. A. R. Solis. (2019) Penalization and augmented Lagrangian for O-D demand matrix estimation from transit segment counts. Transportmetrica A: Transport Science. 15 (2), 915–943.10.1080/23249935.2018.1546780 Search in Google Scholar

30. Heydecker, B. G., W. H. K. Lam, and N. Zhang. (2007) Use of travel demand satisfaction to assess road network reliability. Transportmetrica. 3 (2), 139–171.10.1080/18128600708685670 Search in Google Scholar

31. Horowitz, A. J. (1991) Delay/Volume Relations for Travel Forecasting Based upon the 1985 Highway Capacity Manual. Milwaukee: Department of Civil Engineering and Mechanics University of Wisconsin–Milwaukee. Search in Google Scholar

32. Hu, S., S. Peeta, and C. Chu. (2009) Identification of vehicle sensor locations for link-based network traffic applications. Transportation Research Part B. 43 (8), 87–894.10.1016/j.trb.2009.02.008 Search in Google Scholar

33. Isard, W. (1960) Methods of Regional Analysis: An Introduction to Regional Science. New York: John Wiley and Sons, Inc. Search in Google Scholar

34. Kitamura, R., and Y. O. Susilo. (2005) Is travel demand instable? A study of changes in structural relationships underlying travel. Transportmetrica. 1 (1), 23–45.10.1080/18128600508685640 Search in Google Scholar

35. Krylatov, A. (2016) Network flow assignment as a fixed point problem. Journal of Applied and Industrial Mathematics. 10 (2), 243–256.10.1134/S1990478916020095 Search in Google Scholar

36. Krylatov, A. (2018) Reduction of a Minimization Problem of a Separable Convex Function Under Linear Constraints to a Fixed Point Problem. Journal of Applied and Industrial Mathematics. 12 (1), 98–111.10.1134/S199047891801009X Search in Google Scholar

37. Krylatov, A., V. Zakharov, and T. Tuovinen. (2020) Optimization Models and Methods for Equilibrium Traffic Assignment. Switzerland: Springer International Publishing.10.1007/978-3-030-34102-2 Search in Google Scholar

38. Krylatov, A., and A. Shirokolobova. (2017) Projection approach versus gradient descent for network’s flows assignment problem. Lecture Notes in Computer Science (including sub-series Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10556, 345–350.10.1007/978-3-319-69404-7_29 Search in Google Scholar

39. Krylatov, A., and A. Shirokolobova. (2018) Equilibrium route flow assignment in linear network as a system of linear equations. Vestnik Sankt-Peterburgskogo universiteta. Prikladnaya matematika. Informatika. Protsessy upravleniya. 14 (2), 103–115.10.21638/11701/spbu10.2018.203 Search in Google Scholar

40. Krylatov, A., A. Shirokolobova, and V. Zakharov. (2016) OD-matrix estimation based on a dual formulation of traffic assignment problem. Informatica. 40 (4), 393–398. Search in Google Scholar

41. Lessan, J., and L. Fu. (2019) Credit- and permit-based travel demand management state-of-the-art methodological advances. Transportmetrica A: Transport Science.10.1080/23249935.2019.1692963 Search in Google Scholar

42. Li, B., and B. De Moor. (2002) Dynamic identification of origin-destination matrices in the presence of incomplete observations. Transportation Research Part B. 36, 37–57.10.1016/S0191-2615(00)00037-0 Search in Google Scholar

43. Li, X., and Y. Ouyang. (2011) Reliable sensor deployment for network traffic surveillance. Transportation Research Part B. 45, 218–231.10.1016/j.trb.2010.04.005 Search in Google Scholar

44. Lia, T. and Y. Wanb. (2019) Estimating the geographic distribution of originating air travel demand using a bi-level optimization model. Transportation Research Part E. 131, 267–291.10.1016/j.tre.2019.09.018 Search in Google Scholar

45. Lundgren, J. T., and A. Peterson. (2008) A heuristic for the bilevel origin-destination matrix estimation problem. Transportation Research Part B. 42, 339–354.10.1016/j.trb.2007.09.005 Search in Google Scholar

46. Makowski, G. G. and K. C. Sinha. (1976) A statistical procedure to analyze partial license plate numbers. Transpn. Res. 10, 131–132. Search in Google Scholar

47. McNeil, S., and C. Hendrickson. (1985) A regression formulation of the matrix estimation problem. Transport. Sci. 19 (3), 278–292.10.1287/trsc.19.3.278 Search in Google Scholar

48. Medina, A., N. Taft, K. Salamatian, S. Bhattacharyya, and C. Diot. (2002) Traffic matrix estimation: existing techniques and new directions. Computer Communication Review. 32,161–174.10.1145/964725.633041 Search in Google Scholar

49. Minguez, R., S. Sanchez-Cambronero, E. Castillo, and P. Jimenez. (2010) Optimal traffic plate scanning location for OD trip matrix and route estimation in road networks. Transportation Research Part B. 44, 282–298.10.1016/j.trb.2009.07.008 Search in Google Scholar

50. Ng, M. (2012) Synergistic sensor location for link flow inference without path enumeration: a node-based approach. Transportation Research Part B: Methodological. 46 (6), 781–788.10.1016/j.trb.2012.02.001 Search in Google Scholar

51. Ng, M. (2013) Partial link flow observability in the presence of initial sensors: solution without path enumeration. Transportation Research Part E: Logistics and Transportation Review. 51, 62–66.10.1016/j.tre.2012.12.002 Search in Google Scholar

52. Nguyen, S. (1977) Estimating an OD matrix from network data: A network equilibrium approach. Publication 60, Centre de Recherche sur les Transports, Universitet de Motreal. Search in Google Scholar

53. Nie, Y., H. Zhang, and W. Recker. (2005) Inferring origin-destination trip matrices with a decoupled gls path flow estimator. Transport. Res. Part B. 39 (6), 497–518.10.1016/j.trb.2004.07.002 Search in Google Scholar

54. Ohazulike, A. E., G. Still, W. Kern, and E. C. van Berkum. (2013) An origin-destination based road pricing model for static and multi-period traffic assignment problems. Transportation Research Part E. 58, 1–27.10.1016/j.tre.2013.06.003 Search in Google Scholar

55. Parry, K., and M. L. Hazelton. (2012) Estimation of origin-destination matrices from link counts and sporadic routing data. Transportation Research Part B. 46, 175–188.10.1016/j.trb.2011.09.009 Search in Google Scholar

56. Patriksson, M. (1994) The traffic assignment problem: models and methods. The Netherlands: VSP, Utrecht. Search in Google Scholar

57. Quandt, R. E., and W. J. Baumol. (1966) The Demand for Abstract Transport Modes: Theory and Measurement. Journal of Regional Science. 6 (2), 13–26.10.1111/j.1467-9787.1966.tb01311.x Search in Google Scholar

58. Rajagopal, R., and P. Varaiya. (2007) Health of California’s loop detector system. California PATH Research Report. Search in Google Scholar

59. Sheffi, Y. (1985) Urban transportation networks: equilibrium analysis with mathematical programming methods. N.J.: Prentice-Hall, Inc, Englewood Cliffs. Search in Google Scholar

60. Shen, W., and L. Wynter. (2012) A new one-level convex optimization approach for estimating origin-destination demand. Transportation Research Part B. 46, 1535–1555.10.1016/j.trb.2012.07.005 Search in Google Scholar

61. Sherali, H. D., and T. Park. (2001) Estimation of dynamic origin-destination trip tables for a general network. Transportation Research Part B. 35, 217–235.10.1016/S0191-2615(99)00048-X Search in Google Scholar

62. Shvetsov, V. I. (2003) Mathematical modelling of traffic flows. Automation and Remote Control. 64 (11), 1651–1689.10.1023/A:1027348026919 Search in Google Scholar

63. Simonelli, F., V. Marzano, A. Papola, and I. Vitello. (2012) A network sensor location procedure accounting for o-d matrix estimate variability. Transportation Research Part B. 46, 1624–1638.10.1016/j.trb.2012.08.007 Search in Google Scholar

64. Spiess, H. (2012) A maximum likelihood model for estimating origin-destination matrices. Transportation Research Part B. 21 (5), 395–412. Search in Google Scholar

65. Viti, F., M. Rinaldi, F. Corman, and C. Tampere. (2014) Assessing partial observability in network sensor location problems. Transportation Research Part B. 70, 65–89.10.1016/j.trb.2014.08.002 Search in Google Scholar

66. Wang, J.-P., T.-L. Liu, and H.-J. Huang. (2018) Tradable OD-based travel permits for bimodal traffic management with heterogeneous users. Transportation Research Part E. 118, 589–605.10.1016/j.tre.2018.08.015 Search in Google Scholar

67. Watling, D. P. (1994) Maximum Likelihood Estimation of an Origin-Destination Matrix from a Partial Registration Plate Survey. Transportation Research Part B. 28 (4), 289–314.10.1016/0191-2615(94)90003-5 Search in Google Scholar

68. Wardrop, J. G. (1952) Some theoretical aspects of road traffic research. Proc. Institution of Civil Engineers. 2, 325–378.10.1680/ipeds.1952.11259 Search in Google Scholar

69. Wei, C. and Y. Asakura. (2013) A bayesian approach to traffic estimation in stochastic user equilibrium networks. Transport. Res. Part C. 36, 446–459. Search in Google Scholar

70. Xie, C., K. M. Kockelman, and S. T. Waller. (2011) A maximum entropy-least squares estimator for elastic origin-destination trip matrix estimation. Transport. Res. Part B. 45 (9), 1465–1482.10.1016/j.trb.2011.05.018 Search in Google Scholar

71. Xie, C., K. M. Kockelman, and S. T. Waller. (2010) Maximum entropy method for subnetwork origin-destination trip matrix estimation. Transport. Res. Rec.: J. Transport. Res. Board. 2196, 111–119.10.3141/2196-12 Search in Google Scholar

72. Yang, Y., and Y. Fan. (2015) Data dependent input control for origin-destination demand estimation using observability analysis. Transportation Research Part B. 78, 385–403.10.1016/j.trb.2015.04.010 Search in Google Scholar

73. Yang, Y., Y. Fan, and J. O. Royset. (2015) Estimating probability distributions of travel demand on a congested network. Transportation Research Part B. 122, 265–286.10.1016/j.trb.2019.01.008 Search in Google Scholar

74. Yang, Y., Y. Fan, and R. J. B. Wets. (2018) Stochastic travel demand estimation: Improving network identifiability using multi-day observation sets. Transportation Research Part B. 107, 192–211.10.1016/j.trb.2017.10.007 Search in Google Scholar

75. Yang, H., Y. Iida, and T. Sasaki. (1991) An analysis of the reliability of an origin-destination trip matrix estimated from traffic counts. Transportation Research Part B. 5, 351–363.10.1016/0191-2615(91)90028-H Search in Google Scholar

76. Yang, H., T. Sasaki, Y. Iida, and Y. Asakura. (1992) Estimation of origin-destination matrices from link traffic counts on congested networks. Transportation Research Part B. 26 (6), 417–434.10.1016/0191-2615(92)90008-K Search in Google Scholar

77. Yang, H., and J. Zhou. (1998) Optimal traffic counting locations for origin-destination matrix estimation. Transportation Research Part B. 32 (2), 109–126.10.1016/S0191-2615(97)00016-7 Search in Google Scholar

78. Zakharov, V. V. and A. Yu. Krylatov. (2014) OD-matrix estimation based on plate scanning. 2014 International Conference on Computer Technologies in Physical and Engineering Applications, ICCTPEA 2014 - Proceedings, 209–210.10.1109/ICCTPEA.2014.6893364 Search in Google Scholar

79. Zhou, X., and G. List. (2010) An information-theoretic sensor location model for traffic origin-destination demand estimation applications. Transportation Science. 40 (2), 254–273.10.1287/trsc.1100.0319 Search in Google Scholar

80. Zhou, X. and H. S. Mahmassani. (2007) A structural state space model for real-time traffic origin-destination demand estimation and prediction in a day-to-day learning framework. Transportation Research Part B. 41, 823–840.10.1016/j.trb.2007.02.004 Search in Google Scholar

81. Van Zuylen, H.J., and L. G. Willumsen. (1980) The most likely trip matrix estimated from traffic counts. Transportation Research Part B. 14, 281–293.10.1016/0191-2615(80)90008-9 Search in Google Scholar

Recommended articles from Trend MD