Intelligent IoT systems for traffic management: A practical application

The incorporation of Artificial Intelligence algorithms in Intelligent Transportation Systems gives rise to new opportunities for a more sustainable urban mobility. However, one of the main challenges is to decide when and where these techniques should be applied; several options appear, such as cloud computing, fog computing, edge computing, or even edge devices. In this paper, an Internet of Things-based solution for smart traffic management is presented. Using the lightweight Random Early Detection for Vehicles Dynamic mechanism as a basis, the authors optimize using evolutionary algorithms. Random Early Detection for Vehicles Dynamic can be applied in signaled intersections to proactively detect incipient congestion and set the best cycle and phases of traffic lights. Then, the authors demonstrate that once Random Early Detection for Vehicles Dynamic has been appropriately optimised offline, it can be later used in unknown traffic scenarios without the burden of applying Artificial Intelligence in constrained Internet of Things devices. The performance of this mechanism is widely tested with the SUMO simulation tool. Results show that this improved version, called iREDVD, notably reduces the vehicles’ waiting time, average trip time, fuel consumption, and emission of particles and gaseous pollutants compared with other proposals.

• Record URL:
  https://doi.org/10.1049/itr2.12021
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/1751956X
• Supplemental Notes:
  • © 2021 Antonio Guillen-Perez and Maria-Dolores Cano.
• Authors:
  • Guillen-Perez, Antonio
  • Cano, Maria-Dolores
• Publication Date: 2021-2

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 273-285
• Serial:
  • IET Intelligent Transport Systems
  • Volume: 15
  • Issue Number: 2
  • Publisher: Institution of Engineering and Technology (IET)
  • ISSN: 1751-956X
  • EISSN: 1751-9578
  • Serial URL: https://ietresearch.onlinelibrary.wiley.com/journal/17519578
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Advanced traffic management systems; Algorithms; Artificial intelligence; Intelligent transportation systems; Internet; Traffic control; Wireless communication systems
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01778259
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 29 2021 12:00PM