Paper Info
Title
Drive Smartly as a Taxi Driver
Abstract
GPS-equipped taxis are mobile sensors probing the traffic flow on road surfaces, and taxi drivers are experienced drivers who can usually find out the fastest path to a destination based on their knowledge. In this demo, we provide a user with the practically fastest path to a destination at a given departure time in terms of taxi drivers' intelligence mined from historical GPS trajectories of taxis. We build our system, called T-Drive, by using a real trajectory dataset generated by over 33,000 taxis in a period of 3 months, and conduct both synthetic experiments and in-the-field evaluations. As a result, our method outperforms the real-time-traffic-based (RT) and the speed-constraint-based (SC) approaches in both efficiency and effectiveness.
Year
DOI
Venue
2010
10.1109/UIC-ATC.2010.19
UIC/ATC Workshops
Keywords
Field
DocType
landmark graph,global positioning system,mobile sensor,path finding,road surface,speed-constraint-based approach,gps-equipped taxis,mobile sensors,drive smartly,gps trajectory,traffic flow,synthetic experiment,real trajectory dataset,in-the-field evaluation,taxi driver,departure time,historical gps trajectory,driver information systems,t-drive,road traffic,sensors,fastest path,driving directions,gps-equipped taxi,mobile communication,trajectory,routing
Traffic flow,Simulation,Computer science,Taxis,Road traffic,Real-time computing,Global Positioning System,Gps trajectory,Mobile telephony,Trajectory
Conference
ISBN
Citations 
PageRank 
978-0-7695-4272-0
13
1.00
References 
Authors
10
5
Name
Order
Citations
PageRank
Yu Zheng18939432.87
Nicholas Jing Yuan22617128.44
Wenlei Xie348622.55
Xing Xie49105527.49
Guangzhong Sun5131279.74