Study on the evolution and prediction of the temporal and spatial characteristics of freeway traffic load
Because of the spatiotemporal evolution of expressway traffic flow,it is necessary to study its spatiotemporal characteristics to establish a more accurate and reasonable traffic flow load model.Pearson correlation theory and singular spectrum analysis are used to study the dynamic weighing system data of several regions.According to the 40m dividing point of the average vehicle spacing of the expressway traffic flow,two different space-time models are divided;The time-average vehicle weight of vehicle flow is de-fined,and the time-space correlation and evolution characteristics between the average vehicle weight of ve-hicle flow system and parameters such as vehicle speed and vehicle spacing are analyzed.The combined SSA-LSTM model is further used to decompose,reconstruct and predict the time-average vehicle weight of the vehicle flow system.The results show that the traffic flow load has the periodic characteristic of 24 hours.Compared with the single LSTM model,the average absolute error and root mean square error of the combined SSA-LSTM model are reduced by 57.1％and 54.7％respectively,and the prediction accuracy is greatly improved,which can effectively predict the overall load change of the traffic flow system,thus pro-viding a basis for evaluating the long-term effect of the traffic flow load.
expresswaytraffic loadspace time characteristicsrelevancesingular spectrumLSTM
NETL
NSTL
万方数据
