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All Journal Civil Engineering Journal
Khurram S. Khattak
Department of Computer System Engineering, University of Engineering and Technology, Peshawar,
Civil Engineering, Building, Construction & Architecture

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Macroscopic Traffic Flow Characterization for Stimuli Based on Driver Reaction Waheed Imran; Zawar H. Khan; T. A. Gulliver; Khurram S. Khattak; Salman Saeed; M. Sagheer Aslam
Civil Engineering Journal Vol 7, No 1 (2021): January
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2021-03091632

Abstract

The design and management of infrastructure is a significant challenge for traffic engineers and planners. Accurate traffic characterization is necessary for effective infrastructure utilization. Thus, models are required that can characterize a variety of conditions and can be employed for homogeneous, heterogeneous, equilibrium and non-equilibrium traffic. The Lighthill-Whitham-Richards (LWR) model is widely used because of its simplicity. This model characterizes traffic behavior with small changes over a long idealized road and so is inadequate for typical traffic conditions. The extended LWR model considers driver types based on velocity to characterize traffic behavior in non lane discipline traffic but it ignores the stimuli for changes in velocity. In this paper, an improved model is presented which is based on driver reaction to forward traffic stimuli. This reaction occurs over the forward distance headway during which traffic aligns to the current conditions. The performance of the proposed, LWR and extended LWR models is evaluated using the first order upwind scheme (FOUS). The numerical stability of this scheme is guaranteed by employing the Courant, Friedrich and Lewy (CFL) condition. Results are presented which show that the proposed model can characterize both small and large changes in traffic more realistically. Doi: 10.28991/cej-2021-03091632 Full Text: PDF
Modeling Sustainable Traffic Behavior: Avoiding Congestion at a Stationary Bottleneck Imran Badshah; Zawar H. Khan; T. Aaron Gulliver; Khurram S. Khattak; Syed Saad
Civil Engineering Journal Vol 8, No 11 (2022): November
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-11-02

Abstract

Sustainable traffic behaviour is increasing in importance as traffic volume rises due to population growth. In this paper, a model for traffic flow at a stationary bottleneck is developed to determine the parameters that cause congestion. Towards this goal, traffic density, speed, and delay were acquired during peak and off-peak periods in the morning and afternoon at a stationary bottleneck in Peshawar, KPK, Pakistan. The morning and afternoon peak periods have high densities, low speeds, and considerable delays. Regression models are developed using this data. These results indicate that there is a linear relationship between density and time at the stationary bottleneck and a negative linear relationship between density and speed. Thus, an increase in density increases the time delay and reduces the speed. I comprehensive traffic delay model is characterized by a stationary bottleneck. The Kolmogorov-Smirnov (KS) test and P-values were used to identify the best-fit distribution for speed and density. The binomial and generalized extreme values are considered the best fits for density and speed. The results presented can be used to develop accurate simulation models for stationary bottlenecks to reduce congestion. Doi: 10.28991/CEJ-2022-08-11-02 Full Text: PDF
A Novel Macroscopic Traffic Model based on Distance Headway Zawar H. Khan; T. Aaron Gulliver; Khurram S. Khattak
Civil Engineering Journal Vol 7 (2021): Special Issue "Innovative Strategies in Civil Engineering Grand Challenges"
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-SP2021-07-03

Abstract

A new model is proposed to characterize changes in traffic at transitions. These changes are affected by driver response. The distance headway between vehicles is considered as it affects driver behavior. Driver response is quick with a small distance headway and slow when the distance headway is large. The variations in traffic are greater with a slow driver while traffic is smooth with a quick driver. A model is developed which characterizes traffic based on driver response and distance headway. This model is compared with the well-known and widely employed Zhang and PW models. The Zhang model characterizes driver response at transitions using an equilibrium velocity distribution and ignores distance headway and driver response. Traffic flow in the PW model is characterized using only a velocity constant. Roe decomposition is employed to evaluate the Zhang, PW, and proposed models over a 270 m circular (ring) road. Results are presented which show that Zhang model provides unrealistic results. The corresponding behavior with the proposed model has large variations in flow with a slow driver but is smooth with a quick driver. The PW model provides smooth changes in flow according to the velocity constant, but the behavior is unrealistic because it is not based on traffic physics. Doi: 10.28991/CEJ-SP2021-07-03 Full Text: PDF
Co-Authors Imran Badshah M. Sagheer Aslam Salman Saeed Syed Saad T. A. Gulliver T. Aaron Gulliver Waheed Imran Zawar H. Khan