Paper Info
Title
How Long a Passenger Waits for a Vacant Taxi -- Large-Scale Taxi Trace Mining for Smart Cities
Abstract
To achieve smart cities, real-world trace data sensed from the GPS-enabled taxi system, which conveys underlying dynamics of people movements, could be used to make urban transportation services smarter. As an example, it will be very helpful for passengers to know how long it will take to find a taxi at a spot, since they can plan their schedule and choose the best spot to wait. In this paper, we present a method to predict the waiting time for a passenger at a given time and spot from historical taxi trajectories. The arrival model of passengers and that of vacant taxis are built from the events that taxis arrive at and leave a spot. With the models, we could simulate the passenger waiting queue for a spot and infer the waiting time. The experiment with a large-scale real taxi GPS trace dataset is carried out to verify the proposed method.
Year
DOI
Venue
2013
10.1109/GreenCom-iThings-CPSCom.2013.175
GreenCom/iThings/CPScom
Keywords
Field
DocType
arriving model,global positioning system,trace mining,passenger waits,large-scale taxi trace mining,arrival model,best spot,smart city,passenger waiting time,trace dataset,passenger waiting queue,large-scale real taxi gps,smart cities,traffic engineering computing,historical taxi trajectory,taxi trace data,urban transportation services,vacant taxi,people movement,large-scale taxi,data mining,real-world trace data,large-scale real taxi gps trace dataset,passenger's waiting time,gps-enabled taxi system
Know-how,Simulation,Computer science,Taxis,Transport engineering,Queue,Urban transportation,Smart city,Global Positioning System
Conference
Citations 
PageRank 
References 
12
0.79
14
Authors
7
Name
Order
Citations
PageRank
Guande Qi141819.45
Gang Pan21501123.57
Shijian Li3115569.34
Zhaohui Wu43121246.32
Daqing Zhang53619217.31
Lin Sun61459.46
Laurence T. Yang76870682.61