Quick Link Selection Method by Using Pricing Strategy Based on User Equilibrium for Implementing an Effective Urban Travel Demand Management
This paper presents a two-stage model of optimization as a quick method to choose the best potential links for implementing urban travel demand management (UTDM) strategy like road pricing. The model is optimized by minimizing the hidden cost of congestion based on user equilibrium (MHCCUE). It forecasts the exact amount of flows and tolls for links in user equilibrium condition to determine the hidden cost for each link to optimize the link selection based on the network congestion priority. The results show that not only the amount of total cost is decreased, but also the number of selected links for pricing is reduced as compared with the previous toll minimization methods. Moreover, as this model just uses the traffic assignment data for calculation, it could be considered as a quick and optimum solution for choosing the potential links.
Murchland JD. Braess's paradox of traffic flow. Transportation Research. 1970;4(4):391-4.
Afandizadeh SH, Dehghani N, Mirzahossein H, Hamedi M. Improving SCATS operation during congestion periods using internal/external traffic metering strategy. Promet – Traffic & Transportation. 2016;28(1):41-47.
Jraiw K. Transport demand management – Impacts on congestion alleviation and road safety enhancement in urban areas. Journal of Local and Global Heath Science. 2015(2):83.
Luten K, Binning K, Driver D, Hall T, Schreffler E. Mitigating traffic congestion – the role of demand-side strategies. US Department of Transportation, Federal Highway Administration; 2004.
Ungemah D, Dusza C. Transportation demand management benchmark. Transportation Research Record: Journal of the Transportation Research Board. 2009;2118(1):55-66.
Triantis K, Sarangi S, Teodorović D, Razzolini L. Traffic congestion mitigation: combining engineering and economic perspectives. Transportation Planning and Technology. 2011;34(7):637-45.
Shaw J. The implementation and effectiveness of transport demand management measures: an international perspective. Journal of Transport Geography. 2010;18(6):762.
Broaddus A, Litman T, Menon G. Transportation demand management: Training document. Eschborn, Germany: Federal Ministry for Economic Cooperation and Development; 2009.
Saleh W, Sammer G. Travel demand management and road user pricing: Success, failure and feasibility. Ashgate Publishing, Ltd.; 2012.
De Lara M, de Palma A, Kilani M, Piperno S. Congestion pricing and long term urban form: Application to Paris region. Regional Science and Urban Economics. 2013;43(2):282-95.
Yildirim MB. Congestion toll pricing models and methods for variable demand networks. University of Florida; 2001.
Tezcan HO. Evaluating road pricing with an engineering perspective: aggregate and disaggregate analysis. Canadian Journal of Civil Engineering. 2009;36(6):1028-36.
Small KA, Verhoef ET. The economics of urban transportation: Routledge; 2007.
Pigou AC. The economics of welfare. 4th ed. London: Macmillan; 1920.
Knight FH. Some fallacies in the interpretation of social cost. Quarterly Journal of Economics. 1924;38(4):582-606.
Wardrop JG. Some theoretical aspects of road traffic research. Proceedings of the Institution of Civil Engineers. 1952;1(3):325-362.
Beckmann M, McGuire C, Winsten CB. Studies in the Economics of Transportation; New Haven: Yale University Press; 1956.
Sheffi Y. Urban transportation networks: equilibrium analysis with mathematical programming methods. Englewood Cliffs, New Jersey: Prentice-Hall, Inc.; 1985.
De Palma A, Lindsey R. Traffic congestion pricing methods and technologies. HAL archive; 2009. Available from: https://hal.archives-ouvertes.fr/hal-00414526/document
Yang H, Huang H-J. Principle of marginal-cost pricing: how does it work in a general road network? Transportation Research Part A: Policy and Practice. 1998;32(1):45-54.
Bergendorff P, Hearn DW, Ramana MV. Congestion toll pricing of traffic networks. Springer; 1997.
Hearn DW, Ramana MV. Solving congestion toll pricing models. Springer; 1998.
Hearn DW, Yildirim MB. A toll pricing framework for traffic assignment problems with elastic demand. Springer; 2002.
Patriksson M, Rockafellar RT. A mathematical model and descent algorithm for bilevel traffic management. Transportation Science. 2002;36(3):271-91.
Yildirim MB, Hearn DW. A first best toll pricing framework for variable demand traffic assignment problems. Transportation Research Part B: Methodological. 2005;39(8):659-78.
Florian M, Hearn D. Network equilibrium models and algorithms. Handbooks in Operations Research and Management Science. 1995;8:485-550.
Thorpe N, Hills P, Jaensirisak S. Public attitudes to TDM measures: a comparative study. Transport Policy. 2000;7(4):243-57.
Goodwin P, Lyons G. Public attitudes to transport: interpreting the evidence. Transportation planning and technology. 2010;33(1):3-17.
Gendreau M, Lucotte M, editors. Transportation and network analysis: Current trends – Miscellanea in honor of Michael Florian. Springer Science & Business Media; 2013.
Pardalos P, Hearn D, Hager WW. Network optimization. Springer; 1997.
Hearn D, Ribera J. Bounded flow equilibrium problems by penalty methods. Proceedings of IEEE International Conference on Circuits and Computers; 1980.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).