Driver heterogeneity impact on aggregated traffic behavior

Abstract A new traffic model is developed to evaluate the impact of driver heterogeneity, including driver behavior and braking distance. This is achieved by incorporating the effect of different drivers and changes in braking distance. Thus, real world traffic conditions are considered. It is shown that the proposed model is hyperbolic and stable, so it is well posed and admissible. The performance of this model is compared with the widely used Payne–Witham (PW) model over a 3000 m circular road in MATLAB using the FORCE scheme. This represents a worst-case traffic scenario. The results obtained indicate that the velocity and driver anticipation evolve realistically with the proposed model, so it can effectively characterize driver heterogeneity. Conversely, the PW model produces unreasonable results.

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Publication Details

Journal
Scientific Reports
Published
2026-09-28
DOI
https://doi.org/10.1038/s41598-026-73070-0
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
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article

Driver heterogeneity impact on aggregated traffic behavior

Ahmed B. Altamimi, Faryal Ali, Zawar Hussain Khan, T. Aaron Gulliver
Scientific Reports
Traffic control and management
article

Driver heterogeneity impact on aggregated traffic behavior

Ahmed B. Altamimi, Faryal Ali, Zawar Hussain Khan, T. Aaron Gulliver
article en

Abstract

Abstract A new traffic model is developed to evaluate the impact of driver heterogeneity, including driver behavior and braking distance. This is achieved by incorporating the effect of different drivers and changes in braking distance. Thus, real world traffic conditions are considered. It is shown that the proposed model is hyperbolic and stable, so it is well posed and admissible. The performance of this model is compared with the widely used Payne–Witham (PW) model over a 3000 m circular road in MATLAB using the FORCE scheme. This represents a worst-case traffic scenario. The results obtained indicate that the velocity and driver anticipation evolve realistically with the proposed model, so it can effectively characterize driver heterogeneity. Conversely, the PW model produces unreasonable results.

Scientific Reports
University of Victoria (CA), University of Ha'il (SA)
Openalex Percentile: Top 16%
Traffic control and management
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