Research On Real-time Traffic Flow Acquisition Method Based On Wi-Fi Channel State Information

The number of private vehicles in our country is increasing year by year with the rapid development of economy and technology.However,the capacity of urban roads tends to be saturated.The consequent traffic congestion problem has become an urgent problem to be solved for urban traffic and people’s livelihood.The intelligent transportation system integrating many advanced technologies will be an effective way to solve the problem of traffic congestion.As a vital part of the intelligent transportation system,traffic flow information collection provides the intelligent transportation system with real-time,accurate and fast mass data,and helps the traffic participants acquire the traffic conditions in real time and accurately.With the rapid development of intelligent transportation and the gradual maturity of the Internet of Vehicles technology,more and more wireless infrastructure has appeared on roads and vehicles.These wireless communication devices provide convenient wireless connections between cars and between cars and the surrounding environment.Multiinput Multioutput(MIMO)antenna technology and orthogonal frequency division multiplexing(OFDM)technology introduced by the new type of Internet of Vehicles not only improve the communication performance of wireless network devices,but also enable them to have environmental awareness ability.Based on communication and perception fusion technology,this paper presents a real-time traffic flow acquisition method using channel state information.The specific research contents of this paper include:First,the channel state information(CSI)is collected through the wireless communication equipment placed on both sides of the road;Secondly,the collected original data is preprocessed to eliminate the phase anomaly.The preprocessing is divided into two parts.In the first part,the phase purification is achieved through linear fitting method.The processed CSI data can be directly applied to the Multiple Signal Classification(MUSIC)algorithm,so that the phase and amplitude information can be obtained.The traffic density can be detected by analyzing the phase and amplitude.Then,the vehicle velocity estimation model based on the arrival Angle of incident signal is established,and the velocity estimation problem is transformed into the Angle estimation problem.The Angle measurement can be realized by the MUSIC algorithm,so as to achieve the purpose of vehicle speed detection.Finally,the amplitude spectrum is obtained by performing Fourier transform on the CSI data,and continuous monitoring of the spectrum can realize the detection of traffic flow.In order to evaluate the performance and effectiveness of the proposed traffic flow real-time acquisition method,this paper builds an experimental platform based on a PC installed with Intel 5300 Wi-Fi network card and CSI Tool firmware.We verifies the effectiveness of the fast phase correction algorithm,vehicle speed estimation model and flow detection method,discussed and analyzed the factors that affect the accuracy of the experiment,and compared with the existing method in the same environment to verify the advantages of this method.