Modeling Traffic Flows with Fluid Flow Model

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Paulus Setiawan Suryadjaja ◽  
◽  
Maclaurin Hutagalung ◽  
Herman Yoseph Sutarto ◽  
◽  
...  
Keyword(s):  
Fluid Flow ◽  
Traffic Flow ◽  
Flow Model ◽  
Intelligent Transportation System ◽  
Macroscopic Model ◽  
Chain Process ◽  
Data Traffic ◽  
Flow Data ◽  
Order Markov Chain ◽  
Parameter Values

This Research presents a macroscopic model of traffic flow as the basis for making Intelligent Transportation System (ITS). The data used for modeling is The number of passing vehicles per three minutes. The traffic flow model created in The form of Fluid Flow Model (FFM). The parameters in The model are obtained by mixture Gaussian distribution approach. The distribution consists of two Gaussian distributions, each representing the mode of traffic flow. In The distribution, intermode shifting process is illustrated by the first-order Markov chain process. The parameters values are estimated using The Expectation-maximization (EM) algorithm. After The required parameter values are obtained, traffic flow is estimated using the Observation and transition-basedmost likely estimates Tracking Particle Filter (OTPF). To Examine the accuracy of the model has been made, the model estimation results are compared with the actual traffic flow data. Traffic flow data is collected on Monday 20 September 2017 at 06.00 to 10.00 on DipatiukurRoad, Bandung. The proposed model has accuracy with MAPE value below 10%, or falls into highly accurate categories

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.

Macroscopic Model and Its Numerical Solution for Two-Flow Mixed Traffic with Different Speeds and Lengths

2003 ◽  
Vol 1852 (1) ◽  
pp. 209-219 ◽  
Author(s):  
Stéphane Chanut ◽  
Christine Buisson
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Macroscopic Model ◽  
Model Output ◽  
Mixed Traffic ◽  
Traffic Flow Model ◽  
Hyperbolic Conservation ◽  
Flux Function ◽  
First Order ◽  
Proposed Model

A new first-order traffic flow model is introduced that takes into account the fact that various types of vehicles use the roads simultaneously, particularly cars and trucks. The main improvement this model has to offer is that vehicles are differentiated not only by their lengths but also by their speeds in a free-flow regime. Indeed, trucks on European roads are characterized by a lower speed than that of cars. A system of hyperbolic conservation equations is defined. In this system the flux function giving the flow of heavy and light vehicles depends on total and partial densities. This problem is partly solved in the Riemann case in order to establish a Godunov discretization. Some model output is shown stressing that speed differences between the two types of vehicles and congestion propagation are sufficiently reproduced. The limits of the proposed model are highlighted, and potential avenues of research in this domain are suggested.

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.

scholarly journals EXISTENCE OF SOLUTIONS FOR THE AW–RASCLE TRAFFIC FLOW MODEL WITH VACUUM

2008 ◽  
Vol 05 (01) ◽  
pp. 45-63 ◽  
Author(s):  
MARTE GODVIK ◽  
HARALD HANCHE-OLSEN
Keyword(s):  
Traffic Flow ◽  
Hyperbolic Conservation Laws ◽  
Entropy Solution ◽  
Flow Model ◽  
Existence Of Solutions ◽  
Macroscopic Model ◽  
Hyperbolic Conservation ◽  
Hyperbolic Balance Laws ◽  
The Cauchy Problem ◽  
Weak Entropy Solution

In this paper, the macroscopic model for traffic flow proposed by Aw and Rascle in 2000 is considered. The model is a 2 × 2 system of hyperbolic conservation laws, or, when the model includes a relaxation term, a 2 × 2 system of hyperbolic balance laws. The main difficulty is the presence of vacuum, which makes control of the total variation of the conservative variables impossible. We allow vacuum to appear and prove the existence of a weak entropy solution to the Cauchy problem.

A Study of the Traffic Flow Predictive Model Based on Mathematical Statistics and Stochastic Process

2014 ◽  
Vol 548-549 ◽  
pp. 1862-1868
Author(s):  
Hui Zhang ◽  
Hong Yong Zhang ◽  
Man Xia Liu
Keyword(s):  
Stochastic Process ◽  
Traffic Flow ◽  
Intelligent Transportation System ◽  
Flow Data ◽  
Traffic Flow Prediction ◽  
Time Prediction ◽  
Real Time Traffic ◽  
Fluctuation Range ◽  
Improved Model ◽  
Short Time

Real-time traffic flow prediction is one of important issues of intelligent transportation system. Based on the theory of stochastic process of the traffic flow data, the prediction methods, such as grey expecting model and neural network, were applied in this paper. Then according to the actual traffic flow data, an improved model was proposed and the fluctuation range of predicted traffic flow was determined due to calculate an accurate result. Finally, the experiment shows that the designed prediction model can be able to achieve a short time prediction accurately for traffic flow.

scholarly journals Modified Traffic Flow Model with Connected Vehicle Microscopic Data for Proactive Variable Speed Limit Control

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Jie Fang ◽  
Huixuan Ye ◽  
Said M. Easa
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Simulation Software ◽  
Experimental Simulation ◽  
Speed Limit ◽  
Connected Vehicle ◽  
Flow Data ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Flow Model

Most previous prediction based Variable Speed Limit (VSL) control strategies focused on improving traffic mobility based on the macroscopic traffic data. Nowadays, the emerging technologies provide access to the microscopic traffic flow data, which better captures the details of traffic flow dynamics in the VSL controlled environment. Thus, in this paper, the microscopic traffic flow data were utilized as a supplement to predict the evolutions of traffic flow parameters. The proposed VSL control algorithm adopts the Model Predictive Control (MPC) framework, which employs a modified version of the classic traffic flow model METANET to take advantage of the microscopic data in traffic flow predictions. The microscopic traffic simulation software VISSIM was used to establish an experimental simulation platform and perform real time traffic responsive control based on field data. The proposed control strategy was evaluated against the no-VSL control and macroscopic-based VSL controlled scenario. The results show that utilizing the proposed modified METANET model reduced the error in speed prediction accuracy and improved system mobility performance.

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

Integration of an Aggregate Flow Model with a Traffic Flow Simulator

2008 ◽  
Author(s):  
Robert Hoffman ◽  
Jason Burke ◽  
Stephen Augustine ◽  
Dengfeng Sun ◽  
Alexander Bayen ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Flow Simulator
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