CAREER: The Evolution of Transportation Networks: Empirical Research and Agent-Based Models

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

Abstract Abstract - CAREER: The Evolution of Transportation Networks: Empirical Research and Agent-Based Models 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. 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? It is hypothesized that simple, measurable factors (such as traffic growth rates, volume to capacity ratios, and comparison with adjacent upstream and downstream links) explain many of the resulting decisions. This investigation will examine a time series of capital improvement projects and decisions for the Twin Cities of Minneapolis and St. Paul, relating them to network structure characteristics. These empirical models will be embedded in agent based models to replicate the process of network growth. This research specifies and estimates component models explaining travel behavior, network costs and revenue, and investment decisions. 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. Incorporating explicit measures of network externalities in decision making will lead to better plans, network routing decisions, and implementation strategies. Understanding and illustrating how decisions in one point of time affect future choices should help guide planners and decision-makers desiring to shape the future. The long-term consequences of incremental changes will be assessed. This will help decision-makers assess the effects of expanding existing facilities or routes, or building in new rights-of-way or offering new services. This improved understanding of long term network dynamics would lead to better planning and design of road networks to exploit network externalities and maximize future choice for decision makers. The knowledge of how current decisions foreclose or create future opportunities should improve decision-making. The primary educational objectives of the research are to 1) integrate transportation network evolution into courses on Urban Transportation Planning, Transportation Economics, and Transportation and Land Use, 2) develop a Freshman Seminar on Transportation Policy to involve University of Minnesota undergraduates through the Undergraduate Research Opportunities Program, and 3) involve Native American High School Students from the Fond du Lac tribe in Transportation. Use of the simulation model in the courses will provide the students a unique tool for understanding the implications of policy decisions on network evolution.