An integrated modeling system for dynamic operations control and real-time transit information

Abstract

This paper explains a dynamic control system, which predicts deviations in bus operation and enables a transit controller to apply corrective control strategy prior to the actual occurrence of the variation. Two separated Kalman filter algorithms were used in the prediction-modeling framework of this system. Empirical Automatic Vehicle Location (AVL) and Automatic Passenger Counters (APC) data were used to develop the prediction model. The performance of the model was compared with previously developed models using the VISSIM traffic microsimulation package considering different operation scenarios.