Dynamic Bus Arrival Time Prediction with Artificial Neural Networks
Publication: Journal of Transportation Engineering
Volume 128, Issue 5
Abstract
Transit operations are interrupted frequently by stochastic variations in traffic and ridership conditions that deteriorate schedule or headway adherence and thus lengthen passenger wait times. Providing passengers with accurate vehicle arrival information through advanced traveler information systems is vital to reducing wait time. Two artificial neural networks (ANNs), trained by link-based and stop-based data, are applied to predict transit arrival times. To improve prediction accuracy, both are integrated with an adaptive algorithm to adapt to the prediction error in real time. The bus arrival times predicted by the ANNs are assessed with the microscopic simulation model CORSIM, which has been calibrated and validated with real-world data collected from route number 39 of the New Jersey Transit Corporation. Results show that the enhanced ANNs outperform the ones without integration of the adaptive algorithm.
Get full access to this article
View all available purchase options and get full access to this article.
References
Abdelfattah, A. M., and Khan, A. M.(1998). “Models for predicting bus delays.” Transp. Res. Rec., 1623, 8–15.
Ben-Akiva, M., and Lerman, S. R. (1985). Discrete choice analysis, MIT Press, Cambridge, Mass.
Chang, G., and Su, C.(1995). “Predicting intersection queue with neural network models.” Transp. Res., 3C(3), 175–191.
Chien, S., and Ding, Y. (1999a). “Applications of artificial neural networks in prediction of transit arrival times.” Conf. Proc. (CD-ROM), ITS America.
Chien, S., and Ding, Y. (1999b). “A dynamic headway control strategy for transit operations.” Conf. Proc., 6th World Congress on ITS (CD-ROM), ITS Canada, Toronto.
Chin, S., Hwang, H., and Pei, T.(1994). “Using neural networks to synthesize origin-destination flows in a traffic circle.” Transp. Res. Rec., 1457, 134–142.
DeLurgio, S. A. (1998). Forecasting principles and applications, McGraw-Hill, New York.
Ding, Y., Chien, S., and Zayas, N.(2001). “Microscopic simulation of bus transit operations. Case study: Bus route #39 of New Jersey Transit.” Transp. Res. Rec., 1731, 104–111.
Dougherty, M. S., Kirby, H. R., and Boule, R. D.(1993). “The use of neural networks to recognize and predict traffic congestion.” Traffic Eng. Control, 34(6), 311–314.
Faghri, A., and Hua, J. (1992). “Evaluation of artificial neural networks applications in transportation engineering.” Proc., 71st Annual Meeting, Transportation Research Board, Washington, D.C.
Federal Highway Administration. (1996). “CORSIM user’s manual.” Rep. No. DTFH61-92-Z-00074, U.S. Department of Transportation, Washington, D.C.
Federal Transit Administration. (1998). “Advanced public transportation systems: The state of the art. Update ’98.” Rep., U.S. Department of Transportation, Washington, D.C.
Gelb, A., Kasper, J. F. Jr., Nash, R. A., Price, C. F. Jr., and Sutherland, A. A. Jr. (1977). Applied optimal estimation, MIT Press, Cambridge, Mass.
Hagan, M. T., Demuth, H. B., and Beale, M. (1996). Neural network design, PWS, Boston.
Hua, J., and Faghri, A.(1994). “Application of ANNs to IVHS.” Transp. Res. Rec., 1453, 83–90.
Kalaputapu, R., and Demetsky, M. J.(1995). “Application of artificial neural networks and automatic vehicle location data for bus transit schedule behavior modeling.” Transp. Res. Rec., 1497, 44–52.
Okutani, I., and Stephanedes, Y. J.(1984). “Dynamic prediction of traffic volume through Kalman filtering theory.” Transp. Res., 18B(1), 1–11.
Park, D., and Rilett, L. R.(1999). “Forecasting freeway link travel times with a multilayer feedforward neural network.” Computer-Aided Civil and Infrastructure Engineering, 14(5), 357–367.
Smith, B. L., and Demetsky, M. J.(1995). “Short-term traffic flow prediction: Neural network approach.” Transp. Res. Rec., 1453, 98–104.
Stephanedes, Y. J., Kwon, E., and Michalopoulos, P.(1990). “On-line diversion prediction for dynamic control and vehicle guidance in freeway corridors.” Transp. Res. Rec., 1287, 11–19.
Wei, C., and Wu, K.(1997). “Developing intelligent freeway ramp metering control systems.” Conf. Proc., National Science Council in Taiwan, 7C(3), 371–389.
Zhang, H., Ritchie, S. G., and Lo, Z.(1997). “Macroscopic modeling of freeway traffic using an artificial neural network.” Transp. Res. Rec., 1588, 110–119.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 128 • Issue 5 • September 2002
Pages: 429 - 438
Copyright
Copyright © 2002 American Society of Civil Engineers.
History
Received: Feb 20, 2001
Accepted: Nov 29, 2001
Published online: Aug 15, 2002
Published in print: Sep 2002
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.