Citation

Kalaputapu R, Demetsky MJ. Transp. Res. Rec. 1995; 1497: 44-52.

Copyright

(Copyright © 1995, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

unavailable

PMID

unavailable

Abstract

The establishment of the Advanced Public Transportation Systems program has encouraged bus transit operators to experiment with implementing automatic vehicle-location systems for real-time monitoring and supervision of operations. While the focus has primarily been on the implementation of technologies, such as automatic vehicle-location systems, it is necessary to experiment and develop advanced performance analysis and evaluation procedures that can assist in schedule planning and real-time service-control tasks. One potentially useful and effective approach to these tasks is system behavior modeling. In this study this method is used to model schedule behavior of buses on a route using schedule-deviation information. The primary objective of this study is to investigate the application of artificial neural networks, which have been shown to hold promise then applied to nonlinear dynamic system-modeling problems, for developing schedule behavior models. Models are developed using the schedule-deviation information obtained from Tidewater Regional Transit's automatic vehicle-location system. The time-series analysis approach is adopted for the development of schedule behavior models at the route level. The results of a case study are encouraging and demonstrate the usefulness of artificial neural network techniques, especially the Jordan networks and the Elman networks, for modeling schedule deviations of buses on a route.

Language: en

Keywords

Buses; Time series analysis; Neural networks; Scheduling; Performance; Computer simulation; Transportation routes; Bus transportation; Vehicle locating systems