An Analysis Method of Ship Traffic Section Flow Based on Big Data

Abstract

Traffic flow has important research value for traffic planning and traffic management. In waterway traffic, the cross-sectional flow of ships also has important application value in ship safety management, navigation rule making, bridge and wharf construction, and ship driver decision-making. In order to fully explore the characteristics of ship traffic flow in the big data environment, this paper studies the analysis method of ship cross-section flow based on big data. First of all, in order to ensure the accuracy of calculation and reduce the calculation time to improve calculation efficiency, based on AIS big data optimization data processing method, complete data storage strategy and construction of data management mechanism. Then, the ship section flow analysis algorithm is proposed and implemented. Finally, based on the ship section flow analysis algorithm, a ship section flow analysis and statistics system is constructed to complete the flow calculation and information statistics. The research results of this paper make the relevant analysis of ship traffic flow more convenient and faster, and have greater application value for waterway traffic planning and management.