A model of the rise and fall of roads
Keywords:Transport, Land Use, Networks
AbstractThis paper analyzes the relationship between network supply and travel demand and describes a road development and degeneration mechanism microscopically at the link (road-segment) level. A simulation model of transportation network dynamics is developed, involving iterative evolution of travel demand patterns, network revenue policies, cost estimation, and investment rules. The model is applied to a real-world congesting network for Minneapolis-St. Paul, Minnesota (Twin Cities), which comprises nearly 8000 nodes and more than 20,000 links, using network data collected since 1978. Four experiments are carried out with different initial conditions and constraints, the results of which allow us to explore model properties such as computational feasibility, qualitative implications, potential calibration procedures, and predictive value. The hypothesis that road hierarchy is an emergent property of transportation networks is corroborated and the underlying reasons discovered. Spatial distribution of capacity, traffic flow, and congestion in the transportation network is tracked over time. Potential improvements to the model, in particular, and future research directions in transportation network dynamics, in general, are also discussed.
AASHTO. 2011. A Policy on Geometric Design of Highways and Streets, 6th edition. Washington DC: American Association of State Highway and Transportation Officials.
Bar-Gera, H., and D. Boyce. 2003. Origin-based algorithm for combined travel forecasting models. Transportation Research 37B(5): 405–22.
Barthelemy, M. 2015. Time Evolution of Road Networks. InTraffic and Granular Flow’13, pp. 317–337. Cham, Switzerland: Springer International Publishing.
Bureau of Public Roads. 1964. Traffic Assignment Manual. Washington, DC: US Department of Commerce.
Fulton, L. M., R. B. Noland, D. J. Meszler, and J. V. Thomas. 2000. A statistical analysis of the induced travel effects in the US Mid-Atlantic region. Journal of Transportation and Statistics 3(1): 1–14.
Haynes, K. E., and A. S. Fotheringham. 1984. Gravity and Spatial Interaction Models. Beverly Hills, CA: Sage Publications.
Horner, M. W., and M. E. O’Kelly. 2001. Embedding economies of scale concepts for hub network design. Journal of Transport Geography 9(4): 255–265.
Hutchinson, B. G. 1974. Principles of Urban Transportation Systems Planning. New York: McGraw-Hill.
Janson, M., and D. Levinson. 2014. HOT or not: Driver elasticity to price on the MnPASS HOT lanes. Research in Transportation Economics 44: 21–32.
Levinson, D. 1995. An evolutionary transportation planning model. Transportation Research Record 1493: 64–73.
Levinson, D., and R. Karamalaputi. 2003. Induced supply: A model of highway network expansion at the microscopic level. Journal of Transport Economics and Policy 37(3): 297–318.
Levinson, D., F. Xie, and S. Zhu. 2007. The co-evolution of land use and road networks. InTransportation and Traffic Theory 2007, edited by R. E. Allsop, M. G. H. Bell, and B. Heydecker, pp. 839–859. Bingley, UK: Emerald Group Pub.
Levinson, D., F. Xie, and N. Montes de Oca. 2012.
Forecasting and evaluating network growth. Networks and Spatial Economics 12(2): 239–262.
Miyagawa, M. 2011. Hierarchical system of road networks with inward, outward, and through traffic. Journal of Transport Geography 19(4): 591–595.
Montes de Oca, N., and D. Levinson. 2006. Network expansion decision making in Minnesota’s Twin Cities. Transportation Research Record 1981: 1–11.
Newman, M. E. J. 2001. The structure and function of networks. Computer Physics and Communications 147: 40–45.
Noland, R. B. 1998. Relationship between highway capacity and induced vehicle travel. Transportation Research Board 78th Annual Meeting Preprint CD-ROM. Washington, DC: Transportation Research Board, National Research Council.
Parthasarathi, P., D. Levinson, and R. Karamalaputi. 2003. Induced demand: A microscopic perspective. Urban Studies 40(7): 1335–1353.
Schelling, T. C. 1969. Models of segregation. American Economic Review 59(2): 488–93.
Scott, D. M., D. C. Novak, L. Aultman-Hall, and F. Guo. 2006. Network robustness index: A new method for identifying critical links and evaluating the performance of transportation networks. Journal of Transport Geography 14(3): 215–227.
Sheffi, Y. 1985. Urban Transportation Networks. Englewood Cliffs, NJ: Prentice-Hall.
Smock, R. J. 1962. An iterative assignment approach to capacity restraint on arterial networks. Highway Research Board Bulletin 156: 1–13.
Strathman, J. G., K. J. Dueker, T. Sanchez, J. Zhang, and A. E. Riis. 2000. Analysis of induced travel in the 1995 NPTS. Portland, OR: Center for Urban Studies, Portland State University.
Von Neumann, J. 1966. Theory of Self Reproducing Automata, edited by A. W. Burks. Champaign, IL: University of Illinois Press.
Voorhees, A. M. 2013. A general theory of traffic movement. Transportation 40(6): 1105. (Republished from Institute of Transportation Engineers 1955).
Wardrop, J. G. 1952. Some theoretical aspects of road traffic research. Proceedings of the Institution of Civil Engineers, Part II 1(36): 325–62.
Weidner, T. 1996. Hubbing in US air transportation system: Economic approach. Transportation Research Record (1562): 28–37.
Wilson, A. G. 1969. The use of entropy maximizing models, in the theory of trip distribution, mode split and route split. Journal of Transport Economics and Policy 3: 108–126.
Wolfram, S. 1994 Cellular Automata and Complexity. Boston, MA: Addison-Wesley.
Wolfram, S. 2002. A New Kind of Science. Champaign, IL: Wolfram Media.
Xie, F., and D. Levinson. 2009. Modeling the growth of transportation networks: A comprehensive review. Networks and Spatial Economics 9(3): 291–307.
Yerra, B., and D. Levinson. 2005. The emergence of hierarchy in transportation networks. Annals of Regional Science 39(3): 541–553.
Yusufzyanova, D., and L. Zhang. 2011a. Multi-modal and multi-jurisdictional transportation investment decision-making: The case of Washington, DC-Baltimore Region. In Transportation Research Board 90th Annual Meeting (No. 11-4157).
Yusufzyanova, D., and L. Zhang, L. 2011b. Forecasting transportation network evolution and performance under existing and alternative transportation planning processes. In11th International Conference of Chinese Transportation Professionals, 4145–4156.
Zhang, L., and D. Levinson. 2005. An agent-based approach to travel demand forecasting: An exploratory analysis. Journal of the Transportation Research Board 1898: 28–36.
Zhang, L., and D. Levinson. 2006. Road pricing with autonomous links. Journal of the Transportation Research Board 1932: 147–155.
Zhang, L., and D. Levinson. 2008. Investing for reliability and security in transportation networks. Journal of the Transportation Research Board 2041: 1–10.
Zhang, L., and D. Levinson. 2009. Economics of network ownership. International Journal of Sustainable Transportation 3(5): 339–359.
Zhang, L., S. Zhu, and D. Levinson. 2008. Agent-based modeling of price competition, capacity choice, and product differentiation in congested networks. Journal of Transport Economics and Policy 42(3): 435–461.
Zhu, S., and D. Levinson. (2015). Do people use the shortest path? An empirical test of Wardrop’s first principle. PloS One, 10(8), e0134322.
Zia, A., and C. Koliba. 2015. The emergence of attractors under multi-level institutional designs: Agent-based modeling of intergovernmental decision making for funding transportation projects. AI and Society 30(3): 315–331.
How to Cite
Authors who publish with JTLU agree to the following terms: 1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution-Noncommercial License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. 2) 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. 3) 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.