Title of Dissertation: Robust Optimization Model for Bus Priority under Arterial Progression

The purpose of this study is to design a real-time robust arterial signal control system that gives priority to buses while simultaneously maximizing progression bandwidths and optimizing signal timing plans at each intersection along the arterial. The system architecture is divided into three levels. At the progression control level bandwidths are maximized. Existing progression strategies do not use real-time traffic data or use simple mathematical models to estimate traffic evolution. The proposed model eliminates this drawback by using real-time data to develop a neural network model for predicting traffic flows. Rather than using pre-specified values, queue clearance and minimum green times are computed as functions of the predicted queues. To eliminate uncertainty in the prediction due to the long time horizon, robust discrete optimization technique is used to determine the progression bands. At the intersection control level, signal timing plans are optimized subject to bandwidth constraints to allow for uninterrupted arterial flow, and minimum green constraints for driver safety and to discharge average waiting queues. At the bus priority control level, whenever a bus is detected and is a candidat