TRAVEL TIME ESTIMATION FOR TAXI TRIPS USING GPS SEQUENCE

Authors

  • Abhijeet Tikar Department of Computer Engineering NBN Sinhgad School of Engineering Pune, 411041.
  • Niranjan Joshi Department of Computer Engineering NBN Sinhgad School of Engineering Pune, 411041.
  • Manmat Hotalappa Department of Computer Engineering NBN Sinhgad School of Engineering Pune, 411041.
  • Kajal Gadade Department of Computer Engineering NBN Sinhgad School of Engineering Pune, 411041.

Abstract

With many companies providing taxi services on a click, request and dispatch of taxi has become easier and accessible to a wide range of people. Predicting travel time of a given taxi trip plays important role in many decision making problems that are important from both the service time and economics perspective of this business. In this problem, we aim at using machine learning techniques to predict trip travel times based on the characteristics of the trip. We use the taxi trip data provided by Kaggle to train and test the data. We discuss our approach based on KNN regression using GPS data available as part of trip trajectories.

References

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Kaggle, “Pkdd15 taxi trip time prediction,” 2015. [Online]. Available: https://www.kaggle.com/c/pkdd-15-taxi-trip-time-prediction-ii

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Additional Files

Published

15-05-2017

How to Cite

Abhijeet Tikar, Niranjan Joshi, Manmat Hotalappa, & Kajal Gadade. (2017). TRAVEL TIME ESTIMATION FOR TAXI TRIPS USING GPS SEQUENCE. International Education and Research Journal (IERJ), 3(5). Retrieved from https://ierj.in/journal/index.php/ierj/article/view/789