1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China; 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China 在期刊界中查找 在百度中查找 在本站中查找
1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China; 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China 在期刊界中查找 在百度中查找 在本站中查找
1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China; 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China 在期刊界中查找 在百度中查找 在本站中查找
1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China; 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China 在期刊界中查找 在百度中查找 在本站中查找
Highway OD data is a kind of important data for highway operation management and condition analysis. How to use massive toll data to quickly generate and effectively manage highway OD data is an important problem in the current highway intelligent construction. Aiming at the problems of various types and long periods of highway OD data, a storage model of highway OD matrix based on Hadoop and corresponding calculation method are proposed. Two kinds of OD matrices are established as storage models, i.e. statistics of highway vehicle travel time and statistics of highway traffic flow. The comparison between the experiment based on massive real highway toll data and the traditional storage of highway toll data shows that the storage method proposed has better storage efficiency and saves storage space compared with the traditional relational data storage.