Traffic speed estimation based on normal location updates and call arrivals from cellular networks
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.
speed estimation cellular network intelligent transportation system traffic density estimation