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Intelligent Urban Transportation System to Control Road Traffic with Air Pollution Orientation

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Future Data and Security Engineering (FDSE 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13076))

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Abstract

Enhancing transportation services and reducing vehicle emissions at intersections are main challenges for megacities. In this paper, an Intelligent Urban Transportation System is proposed as smart green traffic lights. In this context, vehicles are detected, and categorised. Furthermore, emission factors of each vehicle category are specified and used as an additional factor to optimize the traffic light cycle. IUTAR dashboard has also been developed and presented in this paper.

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Author information

Authors and Affiliations

  1. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

    Binh Thanh Nguyen

  2. Duy Tan University, Da Nang, Vietnam

    Pham Lu Quang Minh, Huynh Vu Minh Nguyet, Do Huu Phuoc, Pham Dinh Tai & Huy Truong Dinh

Authors
  1. Binh Thanh Nguyen
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  2. Pham Lu Quang Minh
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  3. Huynh Vu Minh Nguyet
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  4. Do Huu Phuoc
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  5. Pham Dinh Tai
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  6. Huy Truong Dinh
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Corresponding author

Correspondence to Binh Thanh Nguyen .

Editor information

Editors and Affiliations

  1. HCMC University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University of Linz, Linz, Austria

    Josef Küng

  3. Sungkyunkwan University, Suwon, Korea (Republic of)

    Tai M. Chung

  4. Hosei University, Koganei-shi, Tokyo, Japan

    Makoto Takizawa

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Nguyen, B.T., Minh, P.L.Q., Nguyet, H.V.M., Phuoc, D.H., Tai, P.D., Dinh, H.T. (2021). Intelligent Urban Transportation System to Control Road Traffic with Air Pollution Orientation. In: Dang, T.K., Küng, J., Chung, T.M., Takizawa, M. (eds) Future Data and Security Engineering. FDSE 2021. Lecture Notes in Computer Science(), vol 13076. Springer, Cham. https://doi.org/10.1007/978-3-030-91387-8_14

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  • DOI: https://doi.org/10.1007/978-3-030-91387-8_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91386-1

  • Online ISBN: 978-3-030-91387-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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