Traffic Characterization Based on Driver Reaction

Zawar Hussain Khan (), Khurram S. Khattak, Ahmed B. Altamimi, Thomas Aaron Gulliver, Alaa Chabir and Shah Hussain
Additional contact information
Zawar Hussain Khan: Department of Computer Engineering, College of Computer Science and Engineering, University of Háil, Háil 55476, Saudi Arabia
Khurram S. Khattak: Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan
Ahmed B. Altamimi: Department of Computer Engineering, College of Computer Science and Engineering, University of Háil, Háil 55476, Saudi Arabia
Thomas Aaron Gulliver: Department of Electrical and Computer Engineering, University of Victoria, P.O. Box 1700, STN CSC, Victoria, BC V8W 2Y2, Canada
Alaa Chabir: Department of Computer Engineering, College of Computer Science and Engineering, University of Háil, Háil 55476, Saudi Arabia
Shah Hussain: Department of Mathematics, College of Science, University of Háil, Háil 55476, Saudi Arabia

Mathematics, 2025, vol. 13, issue 16, 1-22

Abstract: A macroscopic model for nonhomogeneous traffic is introduced that incorporates relaxation time and lateral time headway, and accounts for driver reaction time. Driver reaction is based on models of real-world nonhomogeneous traffic flow in Pakistan and Iran. A lateral time headway model is obtained using lane change data to characterize traffic during lane changes. The performance of the proposed model is compared with the well-known Payne–Whitham (PW) model on a 3000 m circular road using the FORCE numerical scheme. The results show that the initial multi-cluster density distribution evolves more realistically and accurately with the proposed model. Thus, it can be used to aid in traffic congestion mitigation for on-ramps and off-ramps.

Keywords: macroscopic model; relaxation time; lateral time headway; regression; FORCE scheme; multi-cluster density distribution; nonhomogeneous traffic (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/16/2616/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/16/2616/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:16:p:2616-:d:1725044

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().