Modeling and Assessment of State-Of-The-Art Traffic Control Subsystems

Traffic signals are one of the vital control elements of traffic management and control systems under purview of Departments of Transportation (DOTs) nationwide. They directly affect mobility, safety, and environmental parameters of the transportation networks. Traffic engineers in DOTs often face pressure for extracting additional benefits from existing signal control equipment, influenced by evident increase in demand and changing traffic patterns. However, they often face difficulties, usually from the maturity of the field equipment, lack of understanding of currently available equipment capabilities, and multitude of market available equipment. Besides issues in everyday operation, the need for improved decision-making process appears during selection and implementation of the future signal-control subsystems. This thesis is focusing on the issues related with the need for extracting additional benefits and improved planning of signal-control equipment deployment. Presented are several methodologies and techniques for modeling and assessing traffic signal controllers and supporting communication infrastructure. Techniques presented in this thesis include Petri Net modeling language, Software-in-the-loop simulation, and Geographical Information Systems. Specific capabilities of listed techniques are coordinated for maximizing their benefits in addressing specific issues. The intended positive effects reflect in enhanced comprehension, numerical representation, and analysis of state-of-the-art signal control subsystems in focus. Frameworks, methodologies, and example cases are presented for each of the specific issues in identified traffic signal subsystems, along with recommendations for further research.