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T-Finder: A Recommender System for Finding Passengers and Vacant Taxis
Oct. 2013 (vol. 25 no. 10)
pp. 2390-2403
Nicholas Jing Yuan, Microsoft Research Asia, Beijing
Yu Zheng, Microsoft Research Asia, Beijing
Liuhang Zhang, Chinese Academy Of Sciences, Hefei
Xing Xie, Microsoft Research Asia, Beijing
This paper presents a recommender system for both taxi drivers and people expecting to take a taxi, using the knowledge of 1) passengers' mobility patterns and 2) taxi drivers' picking-up/dropping-off behaviors learned from the GPS trajectories of taxicabs. First, this recommender system provides taxi drivers with some locations and the routes to these locations, toward which they are more likely to pick up passengers quickly (during the routes or in these locations) and maximize the profit of the next trip. Second, it recommends people with some locations (within a walking distance) where they can easily find vacant taxis. In our method, we learn the above-mentioned knowledge (represented by probabilities) from GPS trajectories of taxis. Then, we feed the knowledge into a probabilistic model that estimates the profit of the candidate locations for a particular driver based on where and when the driver requests the recommendation. We build our system using historical trajectories generated by over 12,000 taxis during 110 days and validate the system with extensive evaluations including in-the-field user studies.
Index Terms:
Vehicles,Roads,Trajectory,Global Positioning System,Recommender systems,Probability,Silicon,taxicabs,Vehicles,Roads,Trajectory,Global Positioning System,Recommender systems,Probability,Silicon,parking place detection,Location-based services,urban computing,recommender systems,trajectories
Nicholas Jing Yuan, Yu Zheng, Liuhang Zhang, Xing Xie, "T-Finder: A Recommender System for Finding Passengers and Vacant Taxis," IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 10, pp. 2390-2403, Oct. 2013, doi:10.1109/TKDE.2012.153
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