Prediction of Travel Time Using Fuzzy Logic Paradigm
Predicting travel time is an important aspect of human life. It helps to effectively manage and successfully make the most of time. So much time is usually spent on the road when travelling from one place to another, particularly in developing countries and in a mega city like Lagos for example, a little time wasted is a lot of money lost, hence the need to envisage the likely time to reach destinations.
This research work explores the robustness of fuzzy logic to predict travel time on all major routes out of the town where the Engineering faculty of Lagos State University is situated. This paper takes into consideration important factors that can lead to delay in travel time; period of day, weather, car density, and construction, as the fuzzy inputs and based on experience, fuzzy rules are generated to give an estimated time of arrival.
To prove the validity of this work, data were collected from frequent road users and co-efficient of determination was calculated for all three routes. The co-efficient of determination ranked above 90% for all three routes, two of which are discussed.
(1) Lum, K.M., Fan, H. S.L., Lam, S.H. and Olszewski, P. (1998) Speed-Flow Modeling of Arterial Roads in Singapore, Journal of Transportation Engineering, Vol. 124, no. 6, Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 1433 - 1448, 2005 213-222.
(2) Karl, C.A., Charles, S. and Trayford, R. (1999) Delivery of Real-Time and Predictive Travel Time Information: Experiences from a Melbourne Trial. Proceedings of 6th World Congress on Intelligent Transport Systems, Toronto, Canada.
(3) Wu, C.-F. (2001) The Study of Vehicle Travel Time Estimation using GPS, Department of Transportation Technology & Management, (Master Thesis), National Chiao Tung University, Taipei.
(4) Chien, S.I-J. And Kuchipudi, C. M. (2003) Dynamic travel time prediction with real-time and historic data, Journal of Transportation Engineering, Vol. 129, No. 6,608-616.
(5) Francesc Soriguera Marti, (2016) Springer Tracts on Transportation and Traffic Volume 11, Highway Travel Time Estimation With Data Fusion, Technical University of Catalonia, Barcelona, Spain
(6) Fuzzy Logic in C, Viot G., Dr. Dobb's Journal, February 1993.
(7) Hong-En LIN, Rocco ZITO, Michael A P TAYLOR. A REVIEW OF TRAVEL TIME PREDICTION IN TRANSPORT AND LOGISTICS.
(8) Wei, C.-H., Lin, S.-C. And Li, Y. (2003) Empirical Validation of Freeway Bus Travel Time Forecasting, Transportation Planning Journal, Vol. 32, 651-679.
(9) Jiang, G. and Zhang, R. (2001) Travel Time Prediction for Urban Arterial Road: A Case on China. Proceedings of Intelligent Transport System, IEEE, 255-260.
(10) Merrrie Bergmann, (2008) An Introduction to Many-Valued and Fuzzy Logic: Semantics, Algebra, and Derivation Systems. Cambridge University Press/9780521881289
(11) Falola, T., & Olanrewaju, S.A. (Eds.). (1986). Transport systems in Nigeria. Syracuse, NY: Maxwell School of Citizenship and Public Affairs, Syracuse University.
(12) Kenworthy, J. R., & Newman, P. (1999). Sustainability and cities. Washington, DC: Island Press. ISBN: 1559636602.9781559636605.
(13) Van Grol, H.J.M., Danech-pajouh, M., Manfredi, S. and Whittaker, J. (1999) DACCORD: Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 1433 - 1448, 2005 1447 on-line travel time prediction, World Conference on Transport Research Society (WCTRS), Vol. 2, 455-467.
Copyright (c) 2019 Transactions on Networks and Communications
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors wishing to include figures, tables, or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s) for both the print and online format and to include evidence that such permission has been granted when submitting their papers. Any material received without such evidence will be assumed to originate from the authors.
All authors of manuscripts accepted for publication in the journal Transactions on Networks and Communications are required to license the Scholar Publishing to publish the manuscript. Each author should sign one of the following forms, as appropriate:
License to publish; to be used by most authors. This grants the publisher a license of copyright. Download forms (MS Word formats) - (doc)
Publication agreement — Crown copyright; to be used by authors who are public servants in a Commonwealth country, such as Canada, U.K., Australia. Download forms (Adobe or MS Word formats) - (doc)
License to publish — U.S. official; to be used by authors who are officials of the U.S. government. Download forms (Adobe or MS Word formats) – (doc)
The preferred method to submit a completed, signed copyright form is to upload it within the task assigned to you in the Manuscript submission system, after the submission of your manuscript. Alternatively, you can submit it by email email@example.com