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Hemorheology Based Traffic Congestion and Forecasting Model in the Internet of Vehicles

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Modeling, Design and Simulation of Systems (AsiaSim 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 751))

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Abstract

Traffic congestion causes increased vehicular queuing, slower speeds and delay in travel time, continuously claiming many social, economic and environmental problems. While Internet of Vehicles (IoV) advances in equipping vehicles with sensors and actuators that ‘communicates’, classifying and forecasting traffic congestion in real-time and in fast mobility is a sizzling yet challenging research interest. In hemorheology, hypertension can be classified in stages to indicate severity levels, thus a similar analogy need to be tested in traffic to classify congestion levels. This paper attempts to develop a traffic congestion and forecasting model based on hypertension in hemorheology. Traffic congestion was simulated in the city of Shah Alam’s urban area using SUMO urban vehicular mobility simulator. Results show promising and rational adaptation of hemorheology in classifying the severity levels of traffic congestion.

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Author information

Authors and Affiliations

  1. University Teknologi MARA, Shah Alam, Selangor, Malaysia

    Nurshahrily Idura Ramli & Mohd Izani Mohamed Rawi

Authors
  1. Nurshahrily Idura Ramli
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  2. Mohd Izani Mohamed Rawi
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Corresponding author

Correspondence to Nurshahrily Idura Ramli .

Editor information

Editors and Affiliations

  1. Universiti Teknologi Malaysia, Skudai, Malaysia

    Mohamed Sultan Mohamed Ali

  2. Universiti Teknologi Malaysia, Skudai, Malaysia

    Herman Wahid

  3. Universiti Teknologi Malaysia, Skudai, Malaysia

    Nurul Adilla Mohd Subha

  4. Universiti Teknologi Malaysia, Skudai, Malaysia

    Shafishuhaza Sahlan

  5. Universiti Teknologi Malaysia, Skudai, Malaysia

    Mohd Amri Md. Yunus

  6. Universiti Teknologi Malaysia, Skudai, Malaysia

    Ahmad Ridhwan Wahap

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© 2017 Springer Nature Singapore Pte Ltd.

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Ramli, N.I., Mohamed Rawi, M.I. (2017). Hemorheology Based Traffic Congestion and Forecasting Model in the Internet of Vehicles. In: Mohamed Ali, M., Wahid, H., Mohd Subha, N., Sahlan, S., Md. Yunus, M., Wahap, A. (eds) Modeling, Design and Simulation of Systems. AsiaSim 2017. Communications in Computer and Information Science, vol 751. Springer, Singapore. https://doi.org/10.1007/978-981-10-6463-0_32

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  • DOI: https://doi.org/10.1007/978-981-10-6463-0_32

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6462-3

  • Online ISBN: 978-981-10-6463-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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