Prediction Model of Bus Arrival Time at Signalized Intersection Using GPS Data
Publication: Journal of Transportation Engineering
Volume 138, Issue 1
Abstract
Accurate prediction of bus arrival time at the stop line is a vital element to the bus signal priority system, but most previous approaches focused on predicting bus arrival times at next bus stops only. This paper develops a travel time prediction model to predict bus arrival time on the basis of global positioning system (GPS) data. Bus travel time from the detected location to stop line is divided into three parts: travel time from present point to the end of anterior queue, waiting time for the green light, and time for discharging anterior queue vehicles. Case studies were conducted in real-life signalized intersections to evaluate the performance of the model. Results showed that the presented model provided acceptable prediction accuracy. In addition, by considering the log interval of GPS data and prediction error, a determination method of the optimal decision-making zone when using sequential GPS data was developed.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This study is supported by Key Projects in the National Science & Technology Pillar Program during the Eleventh Five-Year Plan Period of China (UNSPECIFIEDGrant No. 2009BAG17B02) and National Natural Science Foundation of China (Grant No. NSFC50908100). The authors are grateful to Hongchao Liu, Alexander Skabardonis, Weibin Zhang, and Meng Li. This research is the extension of their previous work.
References
Chien, S., Ding, Y., and Wei, C. (2002). “Dynamic bus arrival time prediction with artificial neural networks.” J. Transp. Eng., 128(5), 429–438.
Chien, S., and Kuchipudi, C. (2003). “Dynamic travel time prediction with real-time and historic data.” J. Transp. Eng., 129(6), 608–616.
Frechette, L., and Khan, A. (1998). “Bayesian regression-based urban traffic models.” Transportation Research Record 1644, Transportation Research Board, Washington, DC, 157–165.
Jeong, R., and Rilett, L. (2004). “The prediction of bus arrival time using AVL data.” Transportation Research Board 83rd Annual Meeting (CD-ROM), Washington, DC.
Liu, H., Skabardonis, A., Zhang, W. et al. (2004). “Optimal detector location for bus signal priority.” Transportation Research Record 1867, Transportation Research Board, Washington, DC, 144–150.
Patnaik, J., Chien, S., Bladikas, A. et al. (2004). “Estimation of bus arrival times using APC data.” J. Public Transp., 7(1), 1–20.
Shalaby, A., and Farhan, A. (2003). “Bus travel time prediction model for dynamic operations control and passenger information systems.” Transportation Research Board 82nd Annual Meeting (CD-ROM), Washington, DC.
Sun, D., Luo, H., Fu, L. et al. (2008). “Predicting bus arrival time on the basis of global positioning system data.” Transportation Research Record 2034, Transportation Research Board, Washington, DC, 62–72.
Tan, C. W., et al. (2006). “Prediction of transit vehicle arrival times at signalized intersections for signal priority control.” Proc., IEEE Intelligent Transportation Systems Conf., Toronto, 1477–1482.
Information & Authors
Information
Published In
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Jul 8, 2009
Accepted: Jun 7, 2011
Published online: Jun 10, 2011
Published in print: Jan 1, 2012
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.