Date of Award
Master of Science (MS)
Dr. Wayne A. Sarasua, Committee Chair
Dr. Mashrur Chowdhury
Dr. Jennifer H. Ogle
Many communities host planned special events that generate several times the communties' AADT around the event period (e.g. pro and college football games). Larger metropolises benefit from ITS to collect data from, model, plan for, and analyze potential solutions to event-caused congestion. The smaller communities, which do not have the resources for traffic management centers, could benefit from more cost-appropriate methodologies. This thesis presents a cost-effective methodology for traffic data collection before and after these events. Modelers can then use this data in a microsimulation package, such as VISSIM, to model how the transportation network performs during this period, to model treatments, and to obtain MOEs useful for making planning decisions. Furthermore, because these events cause networks to be severely over-saturated, collected data can underestimate the level of demand, as it is restricted by capacity. This thesis also presents a methodology to account for this as well. Researchers collected traffic data with these methods from games in 2014-16, developed models for base and treatment scenarios, and proposed changes to the traffic plan starting in 2015. In addition to the methodology, travel-time results from these models are provided as measures of effectiveness. The author's uses his experience with this project to demonstrate that these methods can be used to microsimulate a severely-oversaturated network and predict treatment effectiveness.
Fry, Stephen Daniel, "Modeling Clemson Football Traffic: New Techniques for Small Communities" (2017). All Theses. 2713.