Travel Time Forecasting Based on Fuzzy Patterns
| Autor: | Maciej Celiński, Agnieszka Gandzel, Adam Kiersztyn, Leopold Koczan |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Technology
fuzzy patterns Operations research Computer science Manufactures General Medicine Engineering (General). Civil engineering (General) Environmental technology. Sanitary engineering Fuzzy logic TS1-2301 Travel time transportation data travel time forecasting TJ1-1570 fuzzy clustering Mechanical engineering and machinery TA1-2040 TD1-1066 |
| Zdroj: | Advances in Science and Technology Research Journal, Vol 15, Iss 3, Pp 224-232 (2021) |
| ISSN: | 2299-8624 2080-4075 |
| DOI: | 10.12913/22998624/140540 |
| Popis: | Estimating travel time is one of the most important processes in logistics as well as in everyday life. In particular, when it comes to transportation services, efficient time management can be a competitive advantage, not to mention customer satisfaction, which can be easily translated into business success. Therefore, in this study we analyze various travel time estimation methods in combination with a well-known Fuzzy C-Means clustering algorithm. The proposed FCM-based solution has significant advantages, allowing for the determination of the optimal travel time. In an extensive numerical experiment, we present the application of the proposed method to estimate the time of a taxi trip around New York. Due to division of the city area into detailed areas and taking into account information about the travel time in the analysis, a model was obtained, that perfectly forecasts speed of taxi travel. In this study we consider various, competitive approaches to build such a model. |
| Databáze: | OpenAIRE |
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