Vehicle trajectory reconstruction of urban roads based on low-frequency data collection
Focused on low accuracy in vehicle trajectory matching and traffic flow data errors,when low-frequency collection approach was used during the survey of urban road traffic flow and traffic data collection of particularly at critical road network nodes.A vehicle trajectory reconstruction method was proposed based on the study of the hidden Markov theory and the minimum cost maximum flow model.Using multi-source data fusion technology and geographic information positioning matching technology,the missing traffic basic data of the non-detector road section were reasonably estimated to provide important data support for the research of vehicle trajectory reconstruction.Then,a high-frequency trajectory point dataset of taxi vehicles in a specific region of Chengdu City was employed to validate the effectiveness of this method.The results demonstrate that the complete coverage rate of trajectory reconstruction using low-frequency vehicle trajectory points reaches 89.4％,confirming the method's efficacy and practicality.
vehicle low-frequency trajectory datasetminimum cost maximum flowmulti-source data fusiontrajectory reconstruction
万方数据
维普
