Nonequilibrium Continuum Traffic Flow Model with Frozen Sound Wave Speed

2003 ◽  
Vol 1852 (1) ◽  
pp. 183-192
Author(s):  
W. L. Jin ◽  
H. M. Zhang
Keyword(s):  
Traffic Flow ◽  
Sound Speed ◽  
Flow Model ◽  
Wave Model ◽  
Homogeneous System ◽  
Traffic Flow Model ◽  
Traffic Conditions ◽  
Numerical Solution Methods ◽  
Stable Conditions ◽  
Solution Methods

Results are presented from a recent study on a variation of a new non-equilibrium continuum traffic flow model in which traffic sound speed is constant. Hence this model is called the frozen-wave model. This model resembles the Payne–Whitham model but avoids the “back-traveling” of the latter. For this frozen-wave model, the Riemann problem is analyzed for its homogeneous system, two numerical solution methods are developed to solve it, and numerical simulations are carried out under both stable and unstable traffic conditions. These results show that under stable conditions, the model behaves similarly to the Payne–Whitham model. However, under unstable traffic conditions, it has nonphysical solutions or no solutions when a vacuum problem occurs. This study, on the one hand, provides a more complete picture of the properties of this frozen-wave model and reduces the risk of improper applications of it. On the other hand, it also highlights the need to adopt a density-dependent sound speed.

scholarly journals Evaluating Impacts of Overloaded Heavy Vehicles on Freeway Traffic Condition by a Novel Multi-Class Traffic Flow Model

2018 ◽  
Vol 10 (12) ◽  
pp. 4694 ◽  
Author(s):  
Xiang Wang ◽  
Po Zhao ◽  
Yanyun Tao
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Management Strategies ◽  
Maximum Speed ◽  
Heavy Vehicles ◽  
Fundamental Diagram ◽  
Traffic Condition ◽  
Traffic Flow Model ◽  
Traffic Conditions ◽  
The Impact

Overloaded heavy vehicles (HVs) have significant negative impacts on traffic conditions due to their inferior driving performance. Highway authorities need to understand the impact of overloaded HVs to assess traffic conditions and set management strategies. We propose a multi-class traffic flow model based on Smulders fundamental diagram to analyze the influence of overloaded HVs on traffic conditions. The relationship between the overloading ratio and maximum speed is established by freeway toll collection data for different types of HVs. Dynamic passenger car equivalent factors are introduced to represent the various impacts of overloaded HVs in different traffic flow patterns. The model is solved analytically and discussed in detail in the appendices. The model validation results show that the proposed model can represent traffic conditions more accurately with consideration for overloaded HVs. The scenario tests indicate that the increase of overloaded HVs leads to both a higher congestion level and longer duration.

Traffic Status Prediction and Analysis Based on Mining Frequent Subgraph Patterns

2012 ◽  
Vol 605-607 ◽  
pp. 2543-2548
Author(s):  
Gang Xu ◽  
Hai He Jin ◽  
Jing Liu
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Flow Model ◽  
Graph Model ◽  
Good Choice ◽  
Frequent Subgraph Mining ◽  
Traffic Flow Model ◽  
Traffic Conditions ◽  
Mining Algorithm ◽  
Frequent Subgraph

With the development of the city, the traffic congestion and traffic accidents on the urban road increase frequently. Using traffic modeling and analysis to improve the traffic conditions become more important. Now, using the traffic flow model to study the traffic problems has made many achievements. However, traffic flow model cannot be a good choice for describing the relations of the traffic element at a specific moment, but these relations are indeed significant for forecasting traffic status from that moment on. In this paper, a graph model for the static traffic was studied, and then analyzed the feature of a graph substructure for traffic congestion at one moment. We propose an effective frequent subgraph mining algorithm to find the frequent substructure that represent traffic congestion status in a graph. Our mining algorithm can enhance the efficiency of finding the congestion subgraph. Analyzing the proportion of the congestion subgraph in a graph for traffic to forecast the traffic status at that moment later, thus to find ways to improve traffic conditions.

Study on Discrete Autonomous Traffic Flow Model with Zero-Order Hold

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Lidong Zhang ◽  
Wenxing Zhu ◽  
Mengmeng Zhang ◽  
Cuijiao Chen
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Zero Order ◽  
Traffic Flow Model

scholarly journals Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3425
Author(s):  
Huanping Li ◽  
Jian Wang ◽  
Guopeng Bai ◽  
Xiaowei Hu
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Flow Model ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Transformation Model ◽  
Hydrodynamic Theory ◽  
Traffic Flow Model ◽  
Traffic System ◽  
The Stability

In order to explore the changes that autonomous vehicles would bring to the current traffic system, we analyze the car-following behavior of different traffic scenarios based on an anti-collision theory and establish a traffic flow model with an arbitrary proportion (p) of autonomous vehicles. Using calculus and difference methods, a speed transformation model is established which could make the autonomous/human-driven vehicles maintain synchronized speed changes. Based on multi-hydrodynamic theory, a mixed traffic flow model capable of numerical calculation is established to predict the changes in traffic flow under different proportions of autonomous vehicles, then obtain the redistribution characteristics of traffic flow. Results show that the reaction time of autonomous vehicles has a decisive influence on traffic capacity; the q-k curve for mixed human/autonomous traffic remains in the region between the q-k curves for 100% human and 100% autonomous traffic; the participation of autonomous vehicles won’t bring essential changes to road traffic parameters; the speed-following transformation model minimizes the safety distance and provides a reference for the bottom program design of autonomous vehicles. In general, the research could not only optimize the stability of transportation system operation but also save road resources.

Bifurcation analysis of a heterogeneous continuum traffic flow model

2021 ◽  
Vol 94 ◽  
pp. 369-387
Author(s):  
Weilin Ren ◽  
Rongjun Cheng ◽  
Hongxia Ge
Keyword(s):  
Traffic Flow ◽  
Bifurcation Analysis ◽  
Flow Model ◽  
Traffic Flow Model

scholarly journals A Cellular Automaton Traffic Flow Model with Advanced Decelerations

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Yingdong Liu
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Flow Model ◽  
Stable State ◽  
Practical Significance ◽  
Fundamental Diagram ◽  
Traffic Flow Model ◽  
Short Time ◽  
Vehicle Deceleration ◽  
Real Traffic

A one-dimensional cellular automaton traffic flow model, which considers the deceleration in advance, is addressed in this paper. The model reflects the situation in the real traffic that drivers usually adjust the current velocity by forecasting its velocities in a short time of future, in order to avoid the sharp deceleration. The fundamental diagram obtained by simulation shows the ability of this model to capture the essential features of traffic flow, for example, synchronized flow, meta-stable state, and phase separation at the high density. Contrasting with the simulation results of the VE model, this model shows a higher maximum flux closer to the measured data, more stability, more efficient dissolving blockage, lower vehicle deceleration, and more reasonable distribution of vehicles. The results indicate that advanced deceleration has an important impact on traffic flow, and this model has some practical significance as the result matching to the actual situation.

Analytical and grid-free solutions to the Lighthill–Whitham–Richards traffic flow model

2011 ◽  
Vol 45 (10) ◽  
pp. 1727-1748 ◽  
Author(s):  
Pierre-Emmanuel Mazaré ◽  
Ahmad H. Dehwah ◽  
Christian G. Claudel ◽  
Alexandre M. Bayen
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Traffic Flow Model
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