Network Aggregation Method using Vehicle Trajectory Data

Abstract

Managing and utilizing traffic data on a large-scale transportation network generally involves a great deal of effort. A network aggregation techniques that simplifies complicated network structures have been developed for efficient analysis of large-scale networks. However, the development of more efficient methodologies is required due to the complexity of processing based only on the patterns of the connection structure of existing methodologies and the enormous computation associated with the setting of link attributes. In recent years, vehicle trajectory data that allows comprehensive observation of network traffic state has been accumulated from GPS equipment. In this study, we propose a methodology for network representation and network aggregation based on actual vehicle flow using longterm vehicle trajectory data. As shown by numerical examples of Japan, the complexity of the structure of the aggregated network is not too simple to lose information under network-wide traffic conditions and not too complex to incur a huge calculating cost.