scholarly journals Macroscopic Traffic Flow Characterization at Bottlenecks

2020 ◽  
Vol 6 (7) ◽  
pp. 1227-1242
Author(s):  
Amir Iftikhar ◽  
Zawar H. Khan ◽  
T. Aaron Gulliver ◽  
Khurram S. Khattak ◽  
Mushtaq A. Khan ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Driver Behavior ◽  
Flow Models ◽  
Driver Response ◽  
Lwr Model ◽  
Upwind Difference Scheme ◽  
Flow Characterization ◽  
Traffic Flow Models

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.

Gas-Kinetic Traffic Flow Modeling Including Continuous Driver Behavior Models

2003 ◽  
Vol 1852 (1) ◽  
pp. 231-238 ◽  
Author(s):  
C. M. J. Tampère ◽  
B. van Arem ◽  
S. P. Hoogendoorn
Keyword(s):  
Traffic Flow ◽  
Driver Behavior ◽  
Discrete Event ◽  
Traffic Density ◽  
Flow Density ◽  
Flow Equations ◽  
Flow Models ◽  
Explanatory Factors ◽  
Traffic Flow Models ◽  
Car Following Model

A modeling technique is presented that analytically bridges the gap between microscopic behavior of individual drivers and the macroscopic dynamics of traffic flow. The basis of this approach is the (gas-) kinetic or mesoscopic modeling principle that considers the dynamics of traffic density and generalizations thereof as a probability density function of vehicles in different driving states. In contrast to traditional kinetic models, deceleration of individual vehicles due to slower traffic is treated as a continuous adaptive process rather than a discrete event. An analytic procedure is proposed to aggregate arbitrarily refined individual driver behavior to a macroscopic expected acceleration or deceleration of flow as a whole that can be used in macroscopic differential equations for traffic flow. The procedure implicitly accounts for the anisotropy of information flow in traffic, for anticipation behavior of drivers, and for the finite space requirement of vehicles, as long as these properties have been specified at the level of individual driver behavior. The procedure is illustrated for a simple car-following model with overtaking opportunity. The results show that the procedure yields micro-based aggregate traffic flow models that capture the essential properties of traffic dynamics. The techniques presented can contribute to the development of traffic flow models with driver behavior and driver psychology as important explanatory factors of congestion formation and propagation. Moreover, the approach allows building macroscopic traffic flow equations from future traffic flows for which no empirical speed–flow–density relations are available yet.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

Stochastic Traffic Flow Models of the National Airspace System

2008 ◽  
Author(s):  
Monish Tandale ◽  
Jinwhan Kim ◽  
Karthik Palaniappan ◽  
P. K. Menon ◽  
Jay Rosenberger ◽  
...  
Keyword(s):  
Traffic Flow ◽  
National Airspace System ◽  
Flow Models ◽  
Traffic Flow Models

Study of the Response of PW Traffic Flow Model to a Bottleneck on a Circular Road and its Suitability for Heterogeneous Traffic Conditions

2021 ◽  
Vol 9 (4) ◽  
pp. 460-463
Keyword(s):  
Fluid Flow ◽  
Traffic Flow ◽  
Flow Model ◽  
Equation Model ◽  
Heterogeneous Traffic ◽  
Flow Conditions ◽  
Flow Models ◽  
Traffic Conditions ◽  
Model Response ◽  
Traffic Flow Models

The traffic flow conditions in developing countries are predominantly heterogeneous. The early developed traffic flow models have been derived from fluid flow to capture the behavior of the traffic. The very first two-equation model derived from fluid flow is known as the Payne-Whitham or PW Model. Along with the traffic flow, this model also captures the traffic acceleration. However, the PW model adopts a constant driver behavior which cannot be ignored, especially in the situation of heterogeneous traffic.This research focuses on testing the PW model and its suitability for heterogeneous traffic conditions by observing the model response to a bottleneck on a circular road. The PW model is mathematically approximated using the Roe Decomposition and then the performance of the model is observed using simulations.

Dual EKF State and Parameter Estimation in Multi-Class First-Order Traffic Flow Models

2008 ◽  
Vol 41 (2) ◽  
pp. 14078-14083 ◽  
Author(s):  
J.W.C. Van Lint ◽  
Serge P. Hoogendoorn ◽  
A. Hegyi
Keyword(s):  
Parameter Estimation ◽  
Traffic Flow ◽  
Flow Models ◽  
First Order ◽  
Traffic Flow Models

scholarly journals THEORETICAL ANALYSIS AND COMPUTER EXPERIMENTS FOR 1D RANDOM TRAFFIC FLOW MODELS

1998 ◽  
Vol 47 (11) ◽  
pp. 1761
Author(s):  
LV XIAO-YANG ◽  
LIU MU-REN ◽  
KONG LING-JING
Keyword(s):  
Theoretical Analysis ◽  
Traffic Flow ◽  
Computer Experiments ◽  
Flow Models ◽  
Traffic Flow Models
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