A Microscopic Heterogeneous Traffic Flow Model Considering Distance Headway

Faryal Ali (), Zawar Hussain Khan, Khurram Shehzad Khattak, Thomas Aaron Gulliver and Akhtar Nawaz Khan
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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 Engineering, Jalozai Campus, University of Engineering and Technology Peshawar, Jalozai 24240, Pakistan
Khurram Shehzad Khattak: Department of Computer System 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
Akhtar Nawaz Khan: Department of Electrical Engineering, Jalozai Campus, University of Engineering and Technology Peshawar, Jalozai 24240, Pakistan

Mathematics, 2022, vol. 11, issue 1, 1-20

Abstract: The intelligent driver (ID) model characterizes traffic behavior with a constant acceleration exponent and does not follow traffic physics. This results in unrealistic traffic behavior. In this paper, a new microscopic heterogeneous traffic flow model is proposed which improves the performance of the ID model. The forward and lateral distance headways are used to characterize traffic behavior. The stability of the ID and proposed models is examined over a 1000 m circular road with a traffic disturbance after 30 s. The results obtained show that the proposed model is more stable than the ID model. The performance of the proposed and ID models is evaluated over an 1800 m circular road for 150 s with a platoon of 51 vehicles. Results are presented which indicate that traffic evolves realistically with the proposed model. This is because it is based on the lateral distance headway.

Keywords: intelligent driver model; acceleration exponent; heterogeneous flow; forward and lateral distance headway (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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