This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
In the middle of the 20th century in the United States, transportation and infrastructure development became a priority on the national agenda, instigating the development of mathematical models that would predict transportation network performance. Approximately 40 years later, transportation planning models again became a national priority, this time instigating the…
In the middle of the 20th century in the United States, transportation and infrastructure development became a priority on the national agenda, instigating the development of mathematical models that would predict transportation network performance. Approximately 40 years later, transportation planning models again became a national priority, this time instigating the development of highly disaggregate activity-based traffic models called microsimulations. These models predict the travel on a network at the level of the individual decision-maker, but do so with a large computational complexity and processing time requirement. The vast resources and steep learning curve required to integrate microsimulation models into the general transportation plan have deterred planning agencies from incorporating these tools. By researching the stochastic variability in the results of a microsimulation model with varying random number seeds, this paper evaluates the number of simulation trials necessary, and therefore the computational effort, for a planning agency to reach stable model outcomes. The microsimulation tool used to complete this research is the Transportation Analysis and Simulation System (TRANSIMS). The requirements for initiating a TRANSIMS simulation are described in the paper. Two analysis corridors are chosen in the Metropolitan Phoenix Area, and the roadway performance characteristics volume, vehicle-miles of travel, and vehicle-hours of travel are examined in each corridor under both congested and uncongested conditions. Both congested and uncongested simulations are completed in twenty trials, each with a unique random number seed. Performance measures are averaged for each trial, providing a distribution of average performance measures with which to test the stability of the system. The results of this research show that the variability in outcomes increases with increasing congestion. Although twenty trials are sufficient to achieve stable solutions for the uncongested state, convergence in the congested state is not achieved. These results indicate that a highly congested urban environment requires more than twenty simulation runs for each tested scenario before reaching a solution that can be assumed to be stable. The computational effort needed for this type of analysis is something that transportation planning agencies should take into consideration before beginning a traffic microsimulation program.
