Abstract
Nowadays, transportation companies look for smart solutions in order to improve quality of their services. Accordingly, an intercity bus company in Istanbul aims to improve their shuttle schedules. This paper proposes revising scheduling of the shuttles based on their estimated travel time in the given timeline. Since travel time varies depending on the date of travel, weather, distance, we present a prediction model using both travel history and additional information such as distance, holiday, and weather. The results showed that Random Forest algorithm outperformed other methods and adding additional features increased its accuracy rate.
Original language | English |
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Title of host publication | Distributed Computing and Artificial Intelligence |
Editors | F. Herrera, K. Matsui, S. Rodriguez-Gonzalez |
Place of Publication | Cham |
Publisher | Springer |
Pages | 44-51 |
Number of pages | 8 |
ISBN (Electronic) | 978-3-030-23887-2 |
ISBN (Print) | 978-3-030-23886-5 |
DOIs | |
Publication status | Published - 1 Jan 2020 |
Event | DCAI 2019: The 16th International Symposium on Distributed Computing and Artificial Intelligence - Avila , Spain Duration: 26 Jun 2019 → 28 Jun 2019 Conference number: 16th |
Publication series
Name | The Advances in Intelligent Systems and Computing book series |
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Publisher | Springer |
Volume | 1003 |
Conference
Conference | DCAI 2019 |
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Country/Territory | Spain |
City | Avila |
Period | 26/06/19 → 28/06/19 |
Keywords
- Smart cities
- Transportation
- Information Fusion
- Data Science