480
Views
10
CrossRef citations to date
0
Altmetric
ARTICLES

Bus travel time prediction: a log-normal auto-regressive (AR) modelling approach

, , &
Pages 807-839 | Received 10 Jun 2019, Accepted 29 Nov 2019, Published online: 11 Feb 2020

References

  • Abdelfattah, A. M., and A. M. Khan. 1998. “Models for Predicting Bus Delays.” Transportation Research Record, Journal of Transportation Research Board 1623: 8–15.
  • Anderson, T. 2003. An Introduction to Multivariate Statistical Analysis, Wiley Series in Probability and Statistics, Wiley. https://books.google.co.in/books?id=Cmm9QgAACAAJ.
  • Andres, M., and R. Nair. 2017. “A Predictive-control Framework to Address Bus Bunching.” Transportation Research Part B: Methodological 104: 123–148.
  • Angelo, M., H. A. Deek, and M. Wang. 1999. “Travel Time Prediction for Freeway Corridors.” In Proceedings of the 78th Annual Transportation Research Board Meeting. National Research Council, Washington, DC, USA.
  • Arem, B., M. Vlist, and M. Muste. 1997. “Travel Time Estimation in the GERDIEN Project.” International Journal of Forecasting 13: 73–85.
  • Baba, K., R. Shibata, and M. Sibuya. 2004. “Partial Correlation and Conditional Correlation As Measures of Conditional Independence.” Australian & New Zealand Journal of Statistics 46 (4): 657–664.
  • Bae, S. 1995. “Dynamic Estimation of Travel Time on Arterial Roads by Using Automatic Vehicle Location (AVL) Bus as a Vehicle Probe.” PhD thesis, Dept. Civil Eng., Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
  • Bhandari, R. R. 2005. “Bus Arrival Time Prediction Using Stochastic Time Series and Markov Chains.” PhD thesis, Dept. Civil Eng., New Jersey Institute of Technology, Newark, USA.
  • Bin, Y., Y. Zhinzhen, and Y. Baozhen. 2006. “Bus Arrival Time Prediction Using Support Vector Machines.” Journal of Intelligent Transportation Systems 10 (4): 151–158.
  • Boel, R., and L. Mihaylova. 2006. “A Compositional Stochastic Model for Real Time Freeway Traffic Simulation.” Transportation Research Part B 40: 319–334.
  • Box, G. E. P., and G. Jenkins. 1990. Time Series Analysis, Forecasting and Control. San Francisco, CA: Holden-Day, Incorporated.
  • Brakewood, C., S. Barbeau, and K. Watkins. 2014. “An Experiment Evaluating the Impacts of Real-time Transit Information on Bus Riders in Tampa, Florida.” Transportation Research Part A: Policy and Practice 69: 409–422.
  • Brockwell, P. J., and R. A. Davis. 2002. Introduction to Time Series and Forecasting. 2nd ed. New York: Springer.
  • Cats, O., and G. Loutus. 2015. “Real-time Bus Arrival Information System – An Empirical Evaluation.” Journal of Intelligent Transportation Systems 20 (2): 138–151.
  • Ceder, A. 2007. Public Transit Planning and Operation: Theory, Modeling and Practice. Butterworth-Heinemann: Boston.
  • Celana, M., and M. Lep. 2017. “Bus Arrival Time Prediction Based on Network Model.” Procedia Computer Science 113: 138–145.
  • Celikoglu, H. B. 2013. “Flow-based Freeway Travel-time Estimation: Dynamic Path Loading.” IEEE Transactions on Intelligent Transportation Systems 14 (2): 772–781.
  • Chamberlain, R. 2014. “Great Circle Distance Between Two Points.” http://www.movabletype.co.uk/scripts/gis-faq-5.1.html.
  • Chen, M., X. B. Liu, and J. X. Xia. 2004. “A Dynamic Bus Arrival Time Prediction Model Based on APC Data.” Computer Aided Civil and Infrastructure Engineering 19: 364–376.
  • Chen, H., and H. Rakha. 2014. “Real-time Travel Time Prediction Using Particle Filtering with a Non-explicit State-transition Model.” Transportation Research Part C: Emerging Technologies 43 (1): 112–126.
  • Chen, G., X. Yang, J. An, and D. Zhang. 2012. “Bus-arrival-time Prediction Models: Link-based and Section-based.” Jouranl of Transportation Engineering 138 (1): 60–66.
  • Chien, S. J., Y. Ding, and C. Wei. 2002. “Dynamic Bus Arrival Time Prediction with Artificial Neural Networks.” ASCE Journal of Transportation Engineering 128 (5): 429–438.
  • Chu, L. Y., J. Oh, and W. Recker. 2005. “Adaptive Kalman Filter Based Freeway Travel Time Estimation.” In 84th Annual Meeting of the Transportation Research Board, Washington, DC, USA: National Research Council.
  • Dhivyabharathi, B., E. S. Hima, and L. Vanajakshi. 2018. “Stream Travel Time Prediction Using Particle Filtering Approach.” Transportation Letters: The International Journal of Transportation Research 10 (2): 75–82.
  • Dixon, W. J. 1960. “Simplified Estimation From Censored Normal Samples.” The Annals of Mathematical Statistics 31 (2): 385–391.
  • Fei, X., C. C. Lu, and K. Liu. 2011. “A Bayesian Dynamic Linear Model Approach for Real-time Short-term Freeway Travel Time Prediction.” Transportation Research Part C, Emerging Technologies 19 (6): 1306–1318. http://dx.doi.org/10.1016/j.trc.2010.10.005.
  • Gentili, M., and P. B. Mirchandani. 2018. “Review of Optimal Sensor Location Models for Travel Time Estimation.” Transportation Research Part C: Emerging Technologies 90: 74–96.
  • Guin, A. 2006. “Travel Time Prediction Using a Seasonal Autoregressive Integrated Moving Average Time Series Model.” In Proceedings of the IEEE Intelligent Transportation Systems Conference, Toronto, ON, Canada, 493–498.
  • Hage, R., B. David, F. Peyret, and D. Meizel. 2012. “Unscented Kalman Filter for Urban Network Travel Time Estimation.” In Proceedings of EWGT2012 – 15th Meeting of the EURO Working Group on Transportation, Paris, France.
  • Hamner, B. 2010. “Predicting Travel Times with Context-Dependent Random Forests by Modeling Local and Aggregate Traffic Flow.” In Proceedings of the ICDMW. Sydney, Australia.
  • Haworth, J., J. Shawetaylor, T. Cheng, and J. Wang. 2014. “Local Online Kernel Ridge Regression for Forecasting of Urban Travel Times..” Transportation Research Part C: Emerging Technologies 46: 151–178.
  • Jairam, R., B. A. Kumar, S. S. Arkatkar, and L. Vanajakshi. 2018. “Performance Comparison of Bus Travel Time Prediction Models Across Indian Cities.” Transportation Research Record: Journal of the Transportation Research Board 2672 (31): 87–98.
  • Julio, N., R. Giesen, and P. Lizana. 2016. “Real-time Prediction of Bus Travel Speeds Using Traffic Shockwaves and Machine Learning Algorithms.” Research in Transportation Economics 59: 250–257.
  • Kay, S. M. 1993. Fundamentals of Statistical Signal Processing: Estimation Theory. Upper Saddle River: Prentice-Hall
  • Kendall, M., and A. Stuart. 1977. The Advanced Theory of Statistics, Vol. 2: Inference and Relationship. 4th ed. London: Charles Griffin.
  • Kuchipudi, C., and S. I. Chien. 2003. “Development of a Hybrid Model for Dynamic Travel-time Prediction.” Transportion Research Record, Journal of Transportation Reseach Board 1885 (1): 22–31.
  • Kumar, V., B. A. Kumar, L. Vanajakshi, and S. Subramanian. 2014. “Comparison of Model Based and Machine Learning Approaches for Bus Arrival Time Prediction.” In Proceedings of the 93rd Annual Transportation Research Board Meeting. Washington DC, USA: National Research Council, Transportation Research Board.
  • Kumar, S. V., and L. Vanajakshi. 2012. “Pattern Identification Based Bus Arrival Time Prediction.” Proceedings of the Institution of Civil Engineers-Transport 167 (3): 194–203.
  • Kumar, B. A., L. Vanajakshi, and S. C. Subramanian. 2017a. “Bus Travel Time Prediction Using a Time-Space Discretization Approach.” Transportation Research Part C 79: 308–332.
  • Kumar, B. A., L. Vanajakshi, and S. C. Subramanian. 2017b. “Pattern-based Time-discretized Method for Bus Travel Time Prediction.” Journal of Transportation Engineering, Part A: Systems 143 (6): 04017012.
  • Kumar, B. A., L. Vanajakshi, and S. C. Subramanian. 2018. “A Hybrid Model Based Method for Bus Travel Time Estimation.” Journal of Intelligent Transportation Systems: Technology, Planning, and Operations 22 (5): 390–406.
  • Kwon, J., B. Coifman, and P. Bickel. 2000. “Day-to-day Travel-time Trends and Travel-time Prediction From Loop-detector Data.” Transportation Research Record: Journal of the Transportation Research Board 1717 (15): 120–129.
  • Kwon, J., and K. Petty. 2005. ”A Travel Time Prediction Algorithm Scalable to Freeway Networks with Many Nodes with Arbitrary Travel Routes.” In Proceedings of the 84th Annual Transportation Research Board Meeting. Washington, DC, USA: National Research Council.
  • Lee, S., and D. B. Fambro. 1999. “Application of Subset Autoregressive Moving Average Model for Short-term Freeway Traffic Volume Forecasting.” Transportation Research Record: Journal of the Transportation Research Board 1678: 179–188.
  • Lin, W. H., and J. Zeng. 1999. “Experimental Study on Real-time Bus Arrival Time Prediction with GPS Data.” Transportation Research Record: Journal of the Transportation Research Board 1666: 101–109.
  • Liu, H., H. VanLint, H. VanZuylen, and K. Zhang. 2006. Two Distinct Ways of Using Kalman Filters to Predict Urban Arterial Travel Time.” In IEEE Intelligent Transportation Systems Conference. Toronto, Canada.
  • Logendran, R., and L. Wang. 2008. Dynamic Travel Time Estimation Using Regression Trees. In Technical Report FHWA-OR-RD-09-09. Salem, Oregon, USA: Oregon Department of Transportation.
  • Long, J., G. Ziyou, and W. Y. Szeto. 2011. “Discretised Link Travel Time Models Based on Cumulative Flows: Formulations and Properties.” Transportation Research Part-B 45 (1): 232–254.
  • Mihaylova, L., and R. Boel. 2004. “A Particle Filter for Freeway Traffic Estimation.” In 43rd IEEE Conference on Decision and Control. IEEE.
  • Miska, M. P., T. H. J. Muller, and H. J. van Zuylen. 2005. “Online Travel Time Prediction with Real-Time Microscopic Simulation.” In 84th Annual meeting of the Transportation Research Board, Washington, DC, USA.
  • Nam, D. H., and D. R. Drew. 1996. “Traffic Dynamics: Methods for Estimating Freeway Travel Times in Real-time From Flow Measurements.” Journal of Transportation Engineering 122 (3): 185–191.
  • Nanthawichit, C., T. Nakatsuji, and H. Suzuki. 2003. “Application of Probe-vehicle Data for Real-time Traffic-state Estimation and Short-term Travel-time Prediction on a Freeway.” Transportation Research Record: Journal of the Transportation Research Board 1855: 49–59. doi:10.3141/1855-06.
  • Oda, T. 1990. “An Algorithm for Prediction of Travel Time Using Vehicle Sensor Data.” In 3rd International Conference on Road Traffic Control, London, UK, 40–44.
  • Padmanaban, R. P. S., L. Vanajakshi, and S. C. Subramanian. 2009. “Estimation of Bus Travel Time Incorporating Dwell Time for APTS Applications.” Intelligent Vehicles Symposium 1931–0587: 955–959.
  • Park, S. 1981. “Collinearity and Optimal Restrictions on Regression Parameters for Estimating Responses.” Technometrics 23 (3): 289–295.
  • Patnaik, J., S. Chein, and A. Bladihas. 2004. “Estimation of Bus Arrival Times Using APC Data.” Journal of Public Transportation 7 (1): 1–20.
  • Rahman, M., S. Wirasinghe, and L. Kattan. 2018. “Analysis of Bus Travel Time Distributions for Varying Horizons and Real-time Applications.” Transportation Research Part C: Emerging Technologies 86: 453–466.
  • Ramakrishna, Y., P. Ramakrishna, and R. Sivanandan. 2006. “Bus Travel Time Prediction Using GPS Data.” In Proceedings Map India, New Delhi, India.
  • Ranjitkar, P., L. S. Tey, E. Chakravorty, and K. L. Hurley. 2019. “Bus Arrival Time Modeling Based on Auckland Data.” Transportation Research Record 2673 (6): 1–9.
  • Rashidi, S., and P. Ranjitkar. 2015. “Estimation of Bus Dwell Time Using Univariate Time Series Models.” Journal of Advanced Transportation 49 (1): 139–152.
  • Reifman, A., and K. Keyton. 2010. Winsorize. Thousand Oaks: Sage.
  • Rohatgi, V. K., and A. K. M. E. Saleh. 2015. Random Variables and Their Probability Distributions. Hoboken, NJ: John Wiley & Sons doi:10.1002/9781118799635.ch2.
  • Schrader, C., A. Kornhauser, and L. Friese. 2004. “Using Historical Information in Forecasting Travel Times.” In Proceedings of the 83rd Annual Transportation Research Board Meeting. Washington, DC, USA: National Research Council.
  • Shalaby, A., and A. Farhan. 2004. Bus Travel Time Prediction for Dynamic Operations Control and Passenger Information Systems.” In 83rd Annual Meeting of the Transportation Research Board. Washington, DC, USA: National Research Council.
  • Shumway, R. H., and D. S. Stoffer. 2005. Time Series Analysis and Its Applications (Springer Texts in Statistics). Berlin: Springer-Verlag.
  • Stoica, P. 1980. “Prediction of Autoregressive Lognormal Processes.” IEEE Transactions on Automatic Control 25 (2): 292–293.
  • Tirachini, A. 2017. “Estimation of Travel Time and the Benefits of Upgrading the Fare Payment Technology in Urban Bus Services..” Transportation Research Part C: Emerging Technologies 30: 239–256.
  • van Hinsbergen, C. P. I. J., J. C. van Lint, and F. M. Sanders. 2007. Short Term Traffic Prediction Models.” In 14th World Congress on Intelligent Transport Systems (ITS), Beijing, China.
  • Van Lint, J. 2004. “Reliable Travel Time Prediction for Freeways.” PhD thesis, Delft University of Technology, Delft, The Netherlands.
  • Van Lint, J. 2006. “Incremental and Online Learning Through Extended Kalman Filtering with Constraint Weights for Freeway Travel Time Prediction.” In IEEE Intelligent Transport Systems Conference (ITSC), Madrid, Spain, 1041–1046.
  • Van Lint, H., S. P. Hoogendoorn, and H. J. V. Zuylenv. 2002. “State Space Neural Networks for Freeway Travel Time Prediction.” Artificial Neural Networks – ICANN 2002 Lecture Notes in Computer Science 2415: 1043–1048.
  • Vanajakshi, L., and L. Rilett. 2004. “A Comparison of the Performance of Artificial. Neural Networks and Support Vector Machines for the Prediction of Traffic Speed.” In IEEE Intelligent Vehicles Symposium, 2004. Institute of Electrical and Electronics Engineers (IEEE), Parma, Italy. doi:10.1109/IVS.2004.1336380.
  • Vanajakshi, L., S. C. Subramanian, and R. Sivanandan. 2009. “Travel Time Prediction Under Heterogeneous Traffic Conditions Using Global Positioning System Data From Buses.” IET Intelligent Transporation Systems 3 (1): 1–9.
  • Venables, W., and B. Ripley. 2002. Modern Applied Statistics. New York: Springer.
  • Wall, Z., and D. J. Dailey. 1999. An Algorithm for Predicting the Arrival Time of Mass Transit Vehicles Using Automatic Vehicle Location Data.” In 78th Annual Meeting of the Transportation Research Board. Washington, DC, USA: National Research Council.
  • Watkins, K. E., B. Ferris, A. Borning, G. S. Rutherford, and D. Layton. 2011. “Where Is My Bus? Impact of Mobile Real-time Information on the Perceived and Actual Wait Time of Transit Riders.” Transportation Research Part A: Policy and Practice 45 (8): 839–848.
  • Wolff, T. 2015. “Travel Time Prediction: A Comparison Study on a Common Data Set.” Master's thesis, Norwegian University of Science and Technology, Norway.
  • Wu, C., D. C. Su, J. Chang, C. C. Wei, J. M. Ho, K. J. Lin, and D. Lee. 2003. An Advanced Traveler Information System with Emerging Network Technologies.” In Proceedings of 6thAsia-Pacific Conference Intelligent Transportation Systems Forum, 230–231. Taipei, Chinese-Taipei.
  • Xinghao, S., T. Jing, C. Guojun, and S. Qichong. 2013. “Predicting Bus Real-time Travel Time Basing on Both GPS and RFID Data.” Procedia – Social and Behavioral Sciences 96: 2287–2299.
  • Yin, T., G. Zhong, J. Zhang, S. He, and B. Ran. 2017. “A Prediction Model of Bus Arrival Time At Stops with Multi-routes.” Transportation Research Procedia 25: 4623–4636.
  • Yu, B., W. H. K. Lam, and M. L. Tam. 2011. “Bus Arrival Time Prediction At Bus Stop with Multiple Routes.” Transportation Research Part – C 19 (6): 1157–1170.
  • Yu, B., B. Yu, J. Lu, and Z. Yang. 2010. “An Adaptive Bus Arrival Time Prediction Model.” Journal of the Eastern Asia Society for Transportation Studies 8: 1126–1136.
  • Yu, Z., J. Wood, and V. Gayah. 2017. “Using Survival Models to Estimate Bus Travel Times and Associated Uncertainties.” Transportation Research Part C: Emerging Technologies 74: 366–382.
  • Zhang, Z., Y. Wang, P. Chen, Z. He, and G. Yu. 2017. “Probe Data-driven Travel Time Forecasting for Urban Expressways by Matching Similar Spatiotemporal Traffic Patterns.” Transportation Research Part C: Emerging Technologies 85: 476–493.
  • Zhou, Y., L. Yao, Y. Chen, Y. Gong, and J. Lai. 2017. “Bus Arrival Time Calculation Model Based on Smart Card Data.” Transportation Research Part C: Emerging Technologies 74: 81–96.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.