A reference architecture for context-aware intelligent traffic management platforms

Zeenat Rehena, Marijn Janssen, Samiran Chattopadhya

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Smart cities have been heralded for improving traffic management by utilizing data for making better traffic management decisions. Multi-sided platforms collect data from sensors and citizen-generated data on one side and can provide input for decision-making using data analytics by governments and the public on the other side. However, there is no guidance for creating developing Intelligent Traffic Management Systems (ITMS) platforms. The involvement of various actors having different interest and heterogeneous datasets hampers development. In this article, the authors design a reference architecture (RA) to support intelligent traffic management systems for providing better a commute, and safety and security during travel based on real-time information. The main three layers of this RA are datasets, processes, and actors. The RA for ITMS provides guidance for designing and overcoming the challenges with: 1) heterogeneous datasets; 2) data gathering; 3) data processing; 4) data management; and 5) supporting various types of data users. The illustration and evaluation of the architecture shows possible solutions of the aforementioned challenges. The RA helps to integrate the activities performed by the various actors. In this way it can be used to reduce traffic queues, increase the efficient use of resources, smooth and safe commute of the citizens.

Original languageEnglish
Pages (from-to)65-79
Number of pages15
JournalInternational Journal of Electronic Government Research
Volume14
Issue number4
DOIs
Publication statusPublished - 2018

Keywords

  • Big data
  • Context-aware systems
  • E-government
  • Intelligent traffic management system
  • Multi-sided platform
  • Reference architecture
  • Smart city

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