Taxi trip time prediction using similar trips and road network data

Taxi trip time prediction using similar trips and road network data

2015 IEEE International Conference on Big Data (Big Data)

10.1109/BigData.2015.7364113

http://dx.doi.org/10.1109/BigData.2015.7364113

Wei Wu, Shili Xiang, Shonali Krishnaswamy, Aakash Deep Singh

Computing Science

29 October 2015

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.

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.

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https://oar.a-star.edu.sg/communities-collections/articles/13123

978-1-4799-9925-5

978-1-4799-9926-2

Institute for Infocomm Research