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Combining Machine Learning and Multi-agent Approach for Controlling Traffic at Intersections

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Computational Collective Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9329))

Abstract

Increasing volume of traffic in urban areas causes great costs and has negative effect on citizens’ life and health. The main cause of decreasing traffic fluency is intersections. Many methods for increasing bandwidth of junctions exist, but they are still insufficient. At the same time intelligent, autonomous cars are being created, what opens up new possibilities for controlling traffic at intersections. In this article a new approach for crossing an isolated junction is proposed - cars are given total autonomy and to avoid collisions they have to change speed. Several methods for adjusting speed based on machine learning (ML) are described, including new methods combining different ML algorithms (hybrid methods). The approach and methods were tested using a specially designed platform MABICS. Conducted experiments revealed some deficiencies of the methods - ideas for addressing them are proposed. Results of experiments made it possible to verify the proposed idea as promising.

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Author information

Authors and Affiliations

  1. Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, Poland

    Mateusz Krzysztoń

  2. AGH University of Science and Technology, Krakow, Poland

    Bartłomiej Śnieżyński

Authors
  1. Mateusz Krzysztoń
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  2. Bartłomiej Śnieżyński
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Corresponding author

Correspondence to Mateusz Krzysztoń .

Editor information

Editors and Affiliations

  1. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Núñez

  2. Wrocław University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. Computer Science Department, Universidad Autónoma De Madrid, Madrid, Spain

    David Camacho

  4. Wrocław University of Technology, Wroclaw, Poland

    Bogdan Trawiński

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Krzysztoń, M., Śnieżyński, B. (2015). Combining Machine Learning and Multi-agent Approach for Controlling Traffic at Intersections. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9329. Springer, Cham. https://doi.org/10.1007/978-3-319-24069-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-24069-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24068-8

  • Online ISBN: 978-3-319-24069-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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