Prediction Model of Bus Arrival and Departure Times Using AVL and APC Data

Abstract

The emphasis of this research effort was on using AVL and APC dynamic data to develop a bus travel time model capable of providing real-time information on bus arrival and departure times to passengers (via traveler information services) and to transit controllers for the application of proactive control strategies. The developed model is comprised of two Kalman filter algorithms for the prediction of running times and dwell times alternately in an integrated framework. The AVL and APC data used were obtained for a specific bus route in Downtown Toronto. The perfor-mance of the developed prediction model was tested using " hold out " data and other data from a microsimulation model representing different scenarios of bus opera-tion along the investigated route using the VISSIM microsimulation software pack-age. The Kalman filter-based model outperformed other conventional models in terms of accuracy, demonstrating the dynamic ability to update itself based on new data that reflected the changing characteristics of the transit-operating environ-ment. A user-interactive system was developed to provide continuous information on the expected arrival and departure times of buses at downstream stops, hence the ex-pected deviations from schedule. The system enables the user to assess in real time