Active Control for Traffic Lights in Regions and Corridors: An Approach based on Evolutionary Computation

The growth of vehicles’ fleet circulating on urban streets constitutes a very strong tendency in recent years. The main consequence of this phenomenon refers to the increase of urban congestions, of average delays caused by vehicles waiting on traffic lights and of number of stops. Finding strategies to achieve efficient active traffic control in urban centers is a challenge for engineers and analysts. Recently, important research on dynamic networks and Intelligent Transportation Systems using computational intelligence modeling techniques has been done. This paper proposes a new scheme of active control, using optimization algorithms, to dynamically find traffic signal control plans that optimize traffic conditions in delimited networks and corridors. The proposed system includes a time delay predictive model, used in conjunction with evolutionary approaches like genetic algorithms and differential evolution techniques. Conceptual and applied computational representations necessary for the construction of models are presented. Data collected from a big city in Brazil were fed into the commercial microscopic simulator AIMSUN and were used for the practical experiments. Two main experiments were undertaken and statistically compared in order to decide which method is more efficient in optimizing the active traffic signal timing control for the region under study.

• Record URL:
  https://doi.org/10.1016/j.trpro.2017.05.140
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S2352146517304313
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2017 Samara Soares Leal et al. Published by Elsevier B.V.
• Authors:
  • Leal, Samara Soares
  • de Almeida, Paulo Eduardo
  • Chung, Edward
• Conference:
  • World Conference on Transport Research - WCTR 2016
  • Location: Shanghai , China
  • Date: 2016-7-10 to 2016-7-15
• Publication Date: 2017

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 1769-1780
• Serial:
  • Transportation Research Procedia
  • Volume: 25
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2352-1465
  • Serial URL: http://www.sciencedirect.com/science/journal/23521465/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Active safety systems; Algorithms; Data collection; Driving simulators; Intelligent transportation systems; Optimization; Traffic data; Traffic signal control systems
• Identifier Terms: AIMSUN (Computer model)
• Uncontrolled Terms: Evolutionary computation
• Geographic Terms: Brazil
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01642415
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 13 2017 3:03PM