A case study of MapReduce-based expressway traffic data analysis and service system. (18th April 2020)

• Record Type: Journal Article
• Authors: Liu, Jia; Hong, Zhilong; Mo, Tong; Ding, Weilong; Zhang, Jian; Li, Weiping; Li, Haochen
• Is Part Of: International journal of internet manufacturing and services. Volume 7:Number 4(2020)
• Page Start: 278
• Page End: 289
• Publication Date: 2020-04-18
• Subjects: expressway traffic data analysis system -- ETDAS -- big data -- Hadoop -- MapReduce -- data visualisation; Computer integrated manufacturing systems -- Periodicals; Internet -- Periodicals; 670.2854678
• Languages: English
• ISSNs: 1751-6048

Abstract

The scale of expressway information networking is constantly expanding. Currently the existing analysis system is still built on the relational database. Traffic data produced by the system has reached a data volume of 3 million items monthly. The performance requirements, including high concurrency, massive throughput, visualisation and scalability, are difficult to be satisfied. The expressway traffic data analysis system (ETDAS) is designed to meet the needs of the collection, analysis and visualisation of increasing expressway traffic data by means of the distributed frameworks. The new system is expected to help regulate the road network traffic flow, reduce traffic congestion, and provide analytical support for the optimisation strategy of road network. ETDAS has been deployed online.