Taxi trip time prediction using similar trips and road network data

Taxi trip time prediction using similar trips and road network data
Title:
Taxi trip time prediction using similar trips and road network data
Other Titles:
2015 IEEE International Conference on Big Data (Big Data)
Publication Date:
29 October 2015
Citation:
A. Deep Singh, W. Wu, S. Xiang and S. Krishnaswamy, "Taxi trip time prediction using similar trips and road network data," Big Data (Big Data), 2015 IEEE International Conference on, Santa Clara, CA, 2015, pp. 2892-2894.
Abstract:
Trip time prediction is an important problem. Taxi passengers often want to know when they will arrive at their destinations. We design a method of predicting taxi trip time by finding historical similar trips. Trips are clustered based on origin, destination, and start time. Then similar trips are mapped to road networks to find frequent sub-trajectories that are used to model travel time of the various parts of the routes. Experimental results show this method is effective.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
978-1-4799-9925-5
ISBN:
978-1-4799-9926-2
Files uploaded: