TY - GEN
T1 - How long a passenger waits for a vacant taxi? Large-scale taxi trace mining for smart cities
AU - Qi, Guande
AU - Pan, Gang
AU - Li, Shijian
AU - Wu, Zhaohui
AU - Zhang, Daqing
AU - Sun, Lin
AU - Yang, Laurence Tianruo
PY - 2013/12/1
Y1 - 2013/12/1
N2 - 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.
AB - 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.
KW - Arriving model
KW - Passenger's waiting time
KW - Smart city
KW - Taxi trace data
U2 - 10.1109/GreenCom-iThings-CPSCom.2013.175
DO - 10.1109/GreenCom-iThings-CPSCom.2013.175
M3 - Conference contribution
AN - SCOPUS:84893483673
SN - 9780769550466
T3 - Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013
SP - 1029
EP - 1036
BT - Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013
T2 - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013
Y2 - 20 August 2013 through 23 August 2013
ER -
