TY - JOUR
T1 - Traffic speed estimation based on normal location updates and call arrivals from cellular networks
AU - Chen, Chi Hua
AU - Chang, Hsu Chia
AU - Su, Chun Yun
AU - Lo, Chi Chun
AU - Lin, Hui Fei
N1 - Funding Information:
The research is supported by the National Science Council of Taiwan under the Grant Nos. NSC 100-2811-H-009-011, NSC 100-2622-H-009-001-CC3, NSC100-2410-H009-039-SS2, and NSC 101-2420-H-009-004-DR.
PY - 2013
Y1 - 2013
N2 - Information and communication technologies have improved the quality of Intelligent Transportation Systems (ITS). By estimating from Cellular Floating Vehicle Data (CFVD) is more cost-effective, and easier to acquire than traditional ways. In this paper, this study proposes a novel approach to evaluate the relation of normal location update, call arrivals, traffic flow, and traffic density. Moreover, the traffic speed is estimated by the proposed approach according to CFVD. In the simulation, this study compares the real traffic information with the estimated traffic information by Vehicle Detector (VD). The experiment results show that the accuracy of traffic speed estimation is 92.92%. Therefore, the proposed approach can be used to estimate traffic speed from CFVD for ITS.
AB - Information and communication technologies have improved the quality of Intelligent Transportation Systems (ITS). By estimating from Cellular Floating Vehicle Data (CFVD) is more cost-effective, and easier to acquire than traditional ways. In this paper, this study proposes a novel approach to evaluate the relation of normal location update, call arrivals, traffic flow, and traffic density. Moreover, the traffic speed is estimated by the proposed approach according to CFVD. In the simulation, this study compares the real traffic information with the estimated traffic information by Vehicle Detector (VD). The experiment results show that the accuracy of traffic speed estimation is 92.92%. Therefore, the proposed approach can be used to estimate traffic speed from CFVD for ITS.
KW - Cellular network
KW - Intelligent transportation system
KW - Speed estimation
KW - Traffic density estimation
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U2 - 10.1016/j.simpat.2013.02.005
DO - 10.1016/j.simpat.2013.02.005
M3 - Article
AN - SCOPUS:84876468134
SN - 1569-190X
VL - 35
SP - 26
EP - 33
JO - Simulation Modelling Practice and Theory
JF - Simulation Modelling Practice and Theory
ER -