Analysis Of Traffic Oscillation Evolution Characteristics And Car-following Model In Expressway Weaving Section

Traffic oscillation is a common phenomenon of spontaneous "stop-and-go" of vehicles in urban expressways,which will not only reduce driving comfort,increase driving delay,but also adversely affect traffic safety.Exploring the evolution characteristics of traffic oscillation and studying the following behavior of vehicles under traffic oscillation can enrich the theory of traffic flow and provide strong support for the formulation of scientific and effective traffic control measures.Based on the error analysis and Eliminate high-frequency noise in high-resolution trajectory data,this paper analyzes the evolution characteristics of traffic oscillation phenomenon in the interleaved area of expressway from the aspects of growth characteristics and propagation characteristics,and analyzes the driving style of drivers by selecting and reconstructing the characteristic parameters of driving style under traffic oscillation,and then constructs a car-following model considering driving style under traffic oscillation.The specific research content is divided into the following aspects.Firstly,based on the high-resolution trajectory data,the erroneous frame data in the original data is analyzed and corrected.By analyzing the error causes of the trajectory data,the trajectory data is processing by the five-point cubic smoothing method.On the basis of ensuring the quality of the data,the standard deviation of vehicle speed in different lanes of the main line is calculated to analyze the growth characteristics of traffic oscillation.Using the time-frequency analysis method of short-time Fourier transform,the time-varying information of the vehicle during the oscillation is expressed from the time domain and frequency domain at the same time,the oscillating head car is tracked by identifying the first vehicle with obvious frequency intensity change in the spectrogram at the time of identification,and the acceleration and deceleration change point during the oscillation is identified by the change of frequency intensity of each vehicle,and the change of duration,amplitude and intensity of the oscillation is statistically analyzed based on the propagation path formed by the acceleration and deceleration point,so as to study the propagation characteristics of traffic oscillation in different lanes.Secondly,taking the vehicle following data under traffic oscillation as the research object,12 statistics are selected as the characteristic parameters of driving style clustering,and the characteristic parameters are reconstructed by factor analysis method,and the Xmeans clustering algorithm is used to cluster driving style,and the driving style under traffic oscillation is divided into three categories.Based on the results of driving style clustering,four indicators of speed,acceleration,front time distance and front spacing were selected to statistically calculate the trajectory data of drivers of different styles,and deeply analyze the behavioral characteristics of drivers of three styles.Finally,on the basis of the comparative analysis model-driven car following model and the data-driven car-following model,the instantaneous space headway,speed difference and driving speed of the preceding vehicle in the process of following the driving process are taken as the model input,follow the data of different driving styles obtained based on clustering,the recurrent neural network is used to construct a carfollowing model considering driving style under traffic oscillation,which is modeled and tested for bicycles with different driving styles and fleets containing various driving styles,and the prediction results of other data-driven car-following models and traditional model-driven car-following models are compared and analyzed This verifies the effectiveness and superiority of the proposed model.