A Microscopic Traffic Model Incorporating Vehicle Vibrations Due to Pavement Condition

Faryal Ali (), Zawar Hussain Khan, Khurram Shehzad Khattak, Thomas Aaron Gulliver and Ahmed B. Altamimi
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Faryal Ali: Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
Zawar Hussain Khan: Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
Khurram Shehzad Khattak: Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan
Thomas Aaron Gulliver: Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
Ahmed B. Altamimi: College of Computer Science and Engineering, University of Ha’il, Ha’il 55476, Saudi Arabia

Mathematics, 2023, vol. 11, issue 24, 1-24

Abstract: A microscopic traffic flow model is developed that incorporates vehicle vibrations due to pavement condition. The Intelligent Driver (ID) model employs a fixed exponent so traffic behavior is the same regardless of the road condition. Thus, it ignores the underlying physics. To address this limitation, the proposed model employs the Pavement Condition Index (PCI) in describing traffic behavior. The performance of both models is evaluated on a 3000 m circular road using the Euler numerical discretization technique. The results show that the performance of the proposed model varies with the pavement condition (PCI), as expected. Furthermore, the traffic flow increases with vehicle speed. The oscillations in speed and density with the proposed model decrease as the PCI increases, and are larger when the speed is higher. Consequently, the results with the proposed model align more closely with reality as they are based on the PCI, and so are a more accurate representation of traffic behavior.

Keywords: traffic exponent; Intelligent Driver model; microscopic traffic flow; Pavement Condition Index; vehicle vibration (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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