Performance measurement and operations control in advanced public transit systems

This thesis presents a new approach for operations monitoring and control in public transit systems with real-time information. First, an integrated model that combines both headway-based and schedule-based services is presented. To measure the headway or schedule adherence, the model uses predicted arrival times of vehicles at downstream stops. This feature allows the operational managers to avoid major service interruptions by proactively taking necessary corrective actions. Transit agencies have used and continue to use real-time control strategies to improve quality of their services. These strategies are employed by inspectors at various points along a route to remedy the problems as they occur. Practice shows that it is difficult to apply such strategies effectively without real-time information. In the second part of this thesis, a mathematical model for holding control strategy with real-time information is described. The proposed model aims at minimization of the total passengers waiting time and considers both cases of overcrowded and underutilized services. Due to complexity of the holding problem, several metaheuristics are proposed and tested. Among all intelligent search algorithms, a new version of simulated annealing algorithm is proposed to solve the real-time holding control model. (Abstract shortened by UMI.)...