A macro traffic flow model accounting for real-time traffic state

2015 ◽  
Vol 437 ◽  
pp. 55-67 ◽  
Author(s):  
Tie-Qiao Tang ◽  
Liang Chen ◽  
Yong-Hong Wu ◽  
Lou Caccetta
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Flow Model ◽  
Traffic Flow Model ◽  
Traffic State ◽  
Real Time Traffic

State-Space Model for Traffic State Estimation of a Two-Dimensional Network

2018 ◽  
Vol 13 (2) ◽  
pp. 326-337
Author(s):  
Yosuke Kawasaki ◽  
Yusuke Hara ◽  
Masao Kuwahara ◽  
◽  
◽  
...  
Keyword(s):  
State Space ◽  
Real Time ◽  
Traffic Flow ◽  
Flow Model ◽  
State Space Model ◽  
Two Dimensional ◽  
Traffic Flow Model ◽  
Space Model ◽  
Traffic State ◽  
2D Network

This study proposes a real-time monitoring method for two-dimensional (2D) networks via the fusion of probe data and a traffic flow model. In the Great East Japan Earthquake occurring on March 11, 2011, there was major traffic congestion as evacuees concentrated in cities on the Sanriku Coast. A tragedy occurred when a tsunami overtook the stuck vehicles. To evacuate safely and efficiently, the state of traffic must be monitored in real time on a 2D network, where all networks are linked. Generally, the traffic state is monitored only at observation points. However, observation data presents the risk of errors. Additionally, in the estimated traffic state of the 2D network, unlike non-intersecting road sections (i.e., one-dimensional), it is necessary to model user route choice behavior and origin/destination (OD) demand to input in the model. Therefore, in this study, we develop a state-space model that assimilates vehicle density and divergence ratio data obtained from probe vehicles in a traffic flow model that considers route choice. Our state-space model considers observational errors in the probe data and can simultaneously estimate traffic state and destination component ratio of OD demand. The result of simulated traffic model verification shows that the proposed model has good congestion estimation precision in a small-scale test network.

Wave dynamics in an extended macroscopic traffic flow model with periodic boundaries

2018 ◽  
Vol 32 (16) ◽  
pp. 1850168 ◽  
Author(s):  
Yu-Qing Wang ◽  
Xing-Jian Chu ◽  
Chao-Fan Zhou ◽  
Bo-Wen Yan ◽  
Bin Jia ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Periodic Boundary ◽  
Flow Model ◽  
Traffic Flow Model ◽  
The Real ◽  
Wave Dynamics ◽  
Traffic State ◽  
Real Time Traffic ◽  
Macroscopic Traffic Flow ◽  
Car Following Model

Motivated by the previous traffic flow model considering the real-time traffic state, a modified macroscopic traffic flow model is established. The periodic boundary condition is applied to the car-following model. Besides, the traffic state factor R is defined in order to correct the real traffic conditions in a more reasonable way. It is a key step that we introduce the relaxation time as a density-dependent function and provide corresponding evolvement of traffic flow. Three different typical initial densities, namely the high density, the medium one and the low one, are intensively investigated. It can be found that the hysteresis loop exists in the proposed periodic-boundary system. Furthermore, the linear and nonlinear stability analyses are performed in order to test the robustness of the system.

The Analysis of Traffic Flow Model

2013 ◽  
Vol 380-384 ◽  
pp. 237-240
Author(s):  
Xiao Wei Wei
Keyword(s):  
Traffic Flow ◽  
Traffic Control ◽  
Complex Analysis ◽  
Flow Model ◽  
Flow Simulation ◽  
Urban Traffic ◽  
Traffic Condition ◽  
Traffic Flow Model ◽  
Real Time Traffic ◽  
Dual Channel

With worsening traffic condition in large and medium-sized cities, it has become one of the most important steps for the urban traffic strategy to solve the traffic problems. Since the urban traffic is a complex system in various factors and huge scale, to establish related mathematical model through computer numerical simulation is a significant solution to the comprehensive problems of complex analysis, decision and planning. At present researches on the problems have been achieved in many foreign countries, but domestic research is not enough, especially in the practical application. The macroscopic traffic flow model and microscopic traffic flow model are described and cellular automaton model, dual channel decision model and car-following model are analyzed in this paper, prediction of the ideal traffic flow and trip distribution is consequently concluded, which deepen the understanding to the traffic flow of various phenomenon intrinsic mechanism and predict most closely to the actual situation of traffic flow, which can make fundamental work for traffic flow simulation and for real-time traffic control[1-3].

The Traffic Flow Model of Intelligent Transportation System

2015 ◽  
Vol 713-715 ◽  
pp. 2000-2003 ◽  
Author(s):  
Hong Ying Jiao ◽  
Fang Chi Liang ◽  
Yi Rao
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
The Other ◽  
Traffic Flow Model ◽  
Traffic State ◽  
Two Systems

In this paper, we develop models to analyze traffic flow of intelligent transportation system (ITS).The investigation into ITS is carried out in two aspects: one is the partly ITS, the other is the completely ITS. Comparisons between two systems show: with the increasing of intelligence degree, the superiority of each rule becomes more and more obvious. As is mentioned above, each rule is the most ideal for certain traffic state. While the detailed forms of different rules are not the same, the purpose of all rules is to promote the traffic flow. The phenomenon reveals the consistency of the ITS. In another word, the higher the intelligence degree of a system is, the larger its contributions to the traffic flow are.

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.

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