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Khattak, Khurram S.
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Civil Engineering, Building, Construction & Architecture

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Macroscopic Traffic Flow Characterization at Bottlenecks Iftikhar, Amir; Khan, Zawar H.; Gulliver, T. Aaron; Khattak, Khurram S.; Khan, Mushtaq A.; Ali, Murtaza; Minallahe, Nasru
Civil Engineering Journal Vol 6, No 7 (2020): July
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2020-03091543

Abstract

Traffic congestion is a significant issue in urban areas. Realistic traffic flow models are crucial for understanding and mitigating congestion. Congestion occurs at bottlenecks where large changes in density occur. In this paper, a traffic flow model is proposed which characterizes traffic at the egress and ingress to bottlenecks. This model is based on driver response which includes driver reaction and traffic stimuli. Driver reaction is based on time headway and driver behavior which can be classified as sluggish, typical or aggressive. Traffic stimuli are affected by the transition width and changes in the equilibrium velocity distribution. The explicit upwind difference scheme is used to evaluate the Lighthill, Whitham, and Richards (LWR) and proposed models with a continuous injection of traffic into the system. A stability analysis of these models is given and both are evaluated over a road of length 10 km which has a bottleneck. The results obtained show that the behavior with the proposed model is more realistic than with the LWR model. This is because the LWR model cannot adequately characterize driver behavior during changes in traffic flow.
Macroscopic Traffic Characterization Based on Distance Headway Iftikhar, Amir; Khan, Zawar H.; Aaron Gulliver, T.; Khattak, Khurram S.; Ahmed, Irfan
Civil Engineering Journal Vol 10, No 12 (2024): December
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-12-016

Abstract

Accurate traffic characterization is essential for congestion mitigation. In this paper, a traffic model is proposed that incorporates distance headway in the well-known Lighthill, Whitham, and Richards (LWR) model. Velocity is influenced by the headway distance between vehicles. When this distance is small, the velocity is low, and when it is large, the velocity is high. The proposed and LWR models are implemented in MATLAB, and the performance is evaluated for different values of distance headway. The results show that traffic with the proposed model evolves with smaller changes that are more accurate and realistic than with the LWR model. Doi: 10.28991/CEJ-2024-010-12-016 Full Text: PDF
Co-Authors Aaron Gulliver, T. Ahmed, Irfan Ali, Murtaza Iftikhar, Amir Khan, Mushtaq A. Khan, Zawar H. Minallahe, Nasru T. Aaron Gulliver