Macroscopic Traffic Flow Characterization at Bottlenecks

Amir Iftikhar,Zawar H Khan,Nasru Minallahe,T Aaron Gulliver,Mushtaq A Khan,Murtaza Ali,Khurram S Khattak

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.

Highlights

Traffic congestion is a critical issue in urban areas around the world [1] and it is getting worse
The performance of the proposed and LWR models is evaluated for a traffic bottleneck
A new model was proposed to characterize traffic flow behavior at the ingress to or egress from bottlenecks. This model is based on driver reaction and traffic stimuli

Summary

Introduction

Traffic congestion is a critical issue in urban areas around the world [1] and it is getting worse. A traffic model based on driver response is required which characterizes traffic behavior during transitions This can be employed to mitigate congestion and decrease travel time [6]. Newell improved the LWR model by incorporating stop and go traffic behavior While this model includes changes in density, it does not consider the distances between vehicles for alignment [7, 41]. A new model is proposed to characterize traffic changes at transitions due to bottlenecks This model considers changes in velocity based on driver reaction and traffic stimuli. Driver reaction is introduced as a function of time headway to characterize sluggish, typical and quick driver behavior These reactions are due to traffic stimuli, i.e. a decrease in velocity as vehicles move towards a bottleneck or an increase at the egress from a bottleneck.

Traffic Flow Models

Model Evaluation

Stability Analysis

Performance Results

Traffic Flow Comparison

Conclusion