(National Science Foundation, $400,000, 5 years, PI-David Levinson 2003 start)

This material is based upon work supported by the National Science Foundation under Grant No. 0236396. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Original Abstract:
This research endeavors to understand the evolutionary growth process of transportation networks at a theoretical and empirical level, recognizing the inter-dependence of supply and demand, and to develop agent-based models to replicate that process. Key questions to be examined include:

• Why do networks expand and contract?
• Do networks self-organize into hierarchies?
• Are roads (routes) an emergent property of networks?
• What investment rules predict the sequence and location of network improvements?
• When are already existing facilities expanded (more lanes on the same link) as opposed to new facilities being provided (a new link)?
• How can transportation planning be improved to take advantage of a new understanding of network evolution?

This proposal investigates new methods of modeling transport networks. First, the underlying theory regarding the growth of transportation networks will be considered. Second, the feasibility of abstractly modeling the growth of transportation networks to reveal some basic properties will be demonstrated. Third, the research that aims to transform that proof of concept into an accurate and realistic representation of actual transportation network growth is detailed. Component models explaining travel behavior, network costs and revenue, and investment decisions will be specified and estimated. Then the components will be integrated into the simulation model and tested.
Both the estimation of individual component models and their integration into a simulation of network growth (and decline) will increase our limited understanding of network evolution processes. This new understanding will have broader impacts on transportation planning practice, and ultimately on the shape of cities and regions. In particular, it will provide a tool to illustrate the implications of current decisions on the future shape of the network, a consideration that is lacking in most planning and engineering studies.

Final Report

Presentations and Publications

• Xie, Feng and David Levinson (2006) Title: The Weakest Link: A Model of the Decline of Surface Transportation Networks Abstract: This study explores the economic mechanisms behind the decline of a surface transportation network, based on the assumption that the decline phase is a spontaneous process driven by decentralized decisions of individual travelers and privatized links. A simulation model is developed with a degeneration process by which the weakest link is removed iteratively from the network. Experiments reveal how the economic efficiency of a network evolves during the degeneration process and suggest an “optimal” degenerated network could be derived during the decline phase in terms of maximizing total social welfare.
  
  Keywords: decline, transportation network, degeneration, welfare, accessibility 06-0760 presented at the 85th Annual Meeting of the Transportation Research Board in Washington, DC, January 22-26 2006. Transportation Research part E (accepted). [doi] [bib]
• Xie, Feng and David Levinson (2005) Title: Measuring the Structure of Road Networks Abstract: Spatial networks display both topologic and geometric variations in their structure. This study investigates the measurement of road network structure. Existing measures of heterogeneity, connectivity, accessibility, and interconnectivity are reviewed and three supplemental measures are proposed, including measures of entropy, connection patterns, and continuity. Proposed measures were applied to 16 test networks, which were derived from 4 idealized base networks: 90-degree, 45-degree, 30-degree, and completely connected. The results show that the differentiated structures of road networks can be evaluated by the measure of entropy; predefined connection patterns of arterial roads can be identified and quantified by the measures of ringness, webness, beltness, circuitness, and treeness. A measure of continuity evaluates the quality of a network from the perspective of travelers. Proposed measures could be used to describe the structural attributes of complicated road networks quantitatively, to compare different network structures, and to explore the structural evolution of networks in the spatial and temporal context. These measures can find their applications in urban planning and transportation practice.
  
  Keywords: Networks, Transportation, Structure, Entropy, Pattern, Continuity. Geographical Analysis (accepted) [bib]
• Levinson, David and Bhanu Yerra (2006) Title: Self Organization of Surface Transportation Networks Abstract: This research investigates the self-organization of surface transportation networks. Using a travel demand model coupled with revenue, cost, and investment models, experiments are run under a variety of parameters on a grid network. It is found that roads, contiguous sections of multiple links operating with similar characteristics, and hierarchies of roads emerge under a broad range of assumptions from networks with neither defined roads nor clearly organized hierarchies. The factors which drive this are the (dis)economies of scale, the presence of boundaries, and any initial asymmetry in the network. This research thus finds that roads and hierarchies, which are often thought to be the product of conscious design, can also arise without such intention.
  
  Keywords: Self-organization, network growth, network evolution, transportation planning Transportation Science Vol. 40 No. 2 May 2006 pp. 179-188 [doi] [bib]

Masters Theses

• Feng Xie (2005) The evolution of road networks : a simulation study based on network degeneration

Dissertations

• Lei Zhang (2005) Search, Information, Learning, and Knowledge in Travel Decision-Making: A Positive Approach for Travel Behavior and Demand Analysis