Subnetwork Origin-Destination Matrix Estimation Under Travel Demand Constraints
This paper proposes a subnetwork origin-destination (OD) matrix estimation model under travel demand constraints (SME-DC) that explicitly considers both internal-external subnetwork connections and OD demand consistency between the subnetwork and full network. This new model uses the maximum entropy of OD demands as the objective function and uses the total traffic generations (attractions) along with some fixed OD demands of the subnetwork OD nodes as the constraints. The total traffic generations and attractions along with the fixed OD demands of the subnetwork OD nodes are obtained through an OD node transformation and subnetwork topology analysis. For solving the proposed model, a convex combination method is used to convert the nonlinear SME-DC to the classical linear transportation problem, and a tabular method is used to solve the transportation problem. The Sioux Falls network and Kunshan network were provided to illustrate the essential ideas of the proposed model and the applicability of the proposed solution algorithm.
KeywordsSubnetwork topology analysis Origin-destination matrix estimation Travel demand constraints Convex combination method Tabular method
The authors are grateful to two anonymous referees for their constructive comments and suggestions to improve the quality and clarity of the paper. This research is supported by the National Natural Science Foundation of China (No. 71801115) and the Key Research and Development Projects of Zhenjiang City.
- Bazaraa MS, Sherali HD, Shetty CM (2013) Nonlinear programming: theory and algorithms, 3rd edn. Wiley, HobokenGoogle Scholar
- Bruton MJ (1975) Introduction to transportation planning. Hutchinson, LondonGoogle Scholar
- Facchinei F, Pang JS (2007) Finite-dimensional variational inequalities and complementarity problems. Springer Science & Business Media, BerlinGoogle Scholar
- Haghani AE, Daskin MS (1983) Network design application of an extraction algorithm for network aggregation. Transp Res Rec 944: 37-46Google Scholar
- Hendrickson C, McNeil S (1984) Matrix entry estimation errors. Proceedings of the 9th International Symposium on Transportation and Traffic Theory. Delft University The Netherlands, p 413–430Google Scholar
- Leblanc LJ (1973) Mathematical programming algorithms for large-scale network equilibrium and network design problems. Unpublished PhD dissertation, Northwestern University, EvanstonGoogle Scholar
- Mishra S, Wang Y, Zhu X, Moeckel R, Mahapatra S (2013) Comparison between gravity and destination choice models for trip distribution in Maryland. In: Transportation Research Board 92nd Annual MeetingGoogle Scholar
- Winston WL, Goldberg JB (2004) Operations research: applications and algorithms. Duxbury press, BelmontGoogle Scholar