TY - GEN
T1 - A freeway travel time predicting method based on IoV
AU - Tian, Daxin
AU - Liu, Chao
AU - Wang, Yunpeng
AU - Zhang, Guohui
AU - Xia, Haiying
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - Real-time travel time is one of the important value for traffic management and traffic control. With the help of Internet of Vehicles (IOV), the dynamic traffic information can be collected and distributed more correctly. In this paper, we propose a method to predict the remaining travel time (RTT) for a vehicle on the freeway in the IOV environment. The Markov chains are adopted to predict a vehicle's remaining travel time in real-time. The experimental results prove that the mean absolute percent error (MAPE) is less than 10%.
AB - Real-time travel time is one of the important value for traffic management and traffic control. With the help of Internet of Vehicles (IOV), the dynamic traffic information can be collected and distributed more correctly. In this paper, we propose a method to predict the remaining travel time (RTT) for a vehicle on the freeway in the IOV environment. The Markov chains are adopted to predict a vehicle's remaining travel time in real-time. The experimental results prove that the mean absolute percent error (MAPE) is less than 10%.
KW - Internet of vehicles
KW - Markov chains
KW - Remaining travel time
KW - Travel time prediction
UR - https://www.scopus.com/pages/publications/84964412279
U2 - 10.1109/WF-IoT.2015.7389017
DO - 10.1109/WF-IoT.2015.7389017
M3 - 会议稿件
AN - SCOPUS:84964412279
T3 - IEEE World Forum on Internet of Things, WF-IoT 2015 - Proceedings
SP - 1
EP - 5
BT - IEEE World Forum on Internet of Things, WF-IoT 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE World Forum on Internet of Things, WF-IoT 2015
Y2 - 14 December 2015 through 16 December 2015
ER -