Title: A case study of MapReduce-based expressway traffic data analysis and service system

Authors: Jia Liu; Zhilong Hong; Tong Mo; Weilong Ding; Jian Zhang; Weiping Li; Haochen Li

Addresses: Henan Expressway Network Monitoring Charge Communication Service Co., Ltd., Henan, China ' School of Software and Microelectronics, Peking University, Beijing, China ' School of Software and Microelectronics, Peking University, Beijing, China ' Data Engineering Institute, North China University of Technology, Beijing, China ' School of Economics and Management, Beijing Information Science and Technology University, Beijing, China ' School of Software and Microelectronics, Peking University, Beijing, China ' College of Science, China Agricultural University, Beijing, China

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.

Keywords: expressway traffic data analysis system; ETDAS; big data; Hadoop; MapReduce; data visualisation.

DOI: 10.1504/IJIMS.2020.110233

International Journal of Internet Manufacturing and Services, 2020 Vol.7 No.4, pp.278 - 289

Received: 27 Jul 2018
Accepted: 13 Dec 2018
Published online: 12 Oct 2020 *

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