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Discontinuous-Galerkin-Based Analysis of traffic flow Model Connected with Multi-Agent traffic Model

Computer Modeling in Engineering & Sciences 2021年第9期128卷 949-965页

作者： Rina Okuyama Naoto Mitsume Hideki Fujii Hideaki Uchida The University of Tokyo 7-3-1 HongoBunkyo-kuTokyo113-8656Japan University of Tsukuba 1-1-1 TennodaiTsukuba CityIbaraki305-8577Japan

As the number of automobiles continues to increase year after year,the associated problem of traffic congestion has become a serious societal issue.Initiatives to mitigate this problem have considered methods for optimizing traffic volumes in wide-area road networks,and traffic-flow simulation has become a focus of interest as a technique for advance characterization of such strategies.Classes of models commonly used for traffic-flow simulations include microscopic models based on discrete vehicle representations,macroscopic models that describe entire traffic-flow systems in terms of average vehicle densities and velocities,and mesoscopic models and hybrid(or multiscale)models incorporating both microscopic and macroscopic features.Because traffic-flow simulations are designed to model traffic systems under a variety of conditions,their underlyingmodelsmust be capable of rapidly capturing the consequences of minor variations in operating environments.In other words,the computation speed of macroscopic models and the precise representation of microscopic models are needed simultaneously.Thus,in this study we propose a multiscale model that combines a microscopic model—for detailed analysis of subregions containing traffic congestion bottlenecks or other localized phenomena of interest-with a macroscopic model enabling simulation of wide target areas at a modest computational cost.In addition,to ensure analytical stability with robustness in the presence of discontinuities,we discretize our macroscopic model using a discontinuous Galerkin finite element method(DGFEM),while to conjoin microscopic and macroscopic models,we use a generating/absorbing sponge layer,a technique widely used for numerical analysis of long-wavelength phenomena in shallow water,to enable traffic-flow simulations with stable input and output regions.

关键词： Discontinuous Galerkin finite element method multiscale modeling traffic flow

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A NOTE ON THE INTERACTIONS OF ELEMENTARY WAVES FOR THE AR traffic flow MODEL WITHOUT VACUUM

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Acta Mathematica Scientia 2011年第4期31卷 1503-1512页

作者：孙梅娜 Institute of Physics and Mathematics The Chinese Academy of Sciences School of Mathematical and Information Ludong University

In this note, we consider the interactions of elementary waves for the traffic flow model proposed by Aw and Rascle when the vacuum is not involved. The solutions are obtained constructively and globally when the initial data consist of three pieces of constant states. Furthermore, it can be found that the Riemann solutions are stable with respect to such small perturbations of the initial data in this particular situation by investigating the limits of the solutions as the perturbed parameter ε goes to zero.

关键词： interaction of elementary wave Aw-Rascle model Riemann problem traffic flow hyperbolic conservation laws

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Urban traffic flow Prediction Based on Spatio-Temporal Convolution Networks

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Journal of Computer and Communications 2023年第3期11卷 15-23页

作者： Peng Zheng Yuansong Li Maoyan Lin Youxin Hu School of Computer Science and Engineering Sichuan University of Science and Engineering Yibin China

Urban traffic flow prediction plays an important role in traffic flow control and urban safety risk prevention and control. Timely and accurate traffic flow prediction can provide guidance for traffic, relieve urban traffic travel pressure and reduce the frequency of accidents. Due to the randomness and fast changing speed of urban dynamic traffic data flow, most of the existing prediction methods lack the ability to model the dynamic temporal and spatial correlation of traffic data, so they cannot produce satisfactory prediction results. A spatio-temporal convolution network (ST-CNN) is proposed to solve the traffic flow prediction problem. The model consists of two parts: 1) a convolution block used to extract spatial features;2) a block of time used to characterize time. Data has been fully mined through two modules to output the prediction results of spatio-temporal characteristics, and at the same time, skip connection (direct connection) has been made between the two modules to avoid the problem of gradient explosion. The experimental results on two data sets show that ST-CNN is better than the baseline model.

关键词： traffic flow Deep Learning RNN CNN

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Effects of Adaptive Random Deceleration on traffic flow

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Journal of Applied Mathematics and Physics 2023年第3期11卷 618-628页

作者： Qi Wang Shu Zhu Liuhua Zhu School of computer Jiangsu University of Science and Technology Zhenjiang China School of Physics and Telecommunication Engineering Yulin Normal University Yulin China Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin China Optoelectronic Information Research Center Yulin Normal University Yulin China

Based on the Nagel-Schreckenberg model, an improved cellular automaton traffic flow model is proposed, in which the random deceleration probability of each vehicle is no longer fixed, but is adaptively adjusted according to the local traffic density in its vision and its current velocity. The numerical simulation results show that the maximum traffic capacity of the improved model under the same parameters is greater than that of the Nagel-Schreckenberg model, and is closer to the measured data. In addition, the traffic flow and vehicle velocity under different meteorological conditions are simulated by using the improved model, and the synchronized flow phenomenon consistent with the actual traffic is reproduced. Meanwhile, the results show that under the same parameters, when the traffic density is equal to 0.3, the traffic flow of the improved model increases by about 11% compared with the original model, and when the traffic density increases to 0.6, the traffic flow increases by about 27%. .

关键词： traffic flow Cellular Automaton Adaptive Random Deceleration Synchronized flow

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Missing Data Imputation for traffic flow Based on Improved Local Least Squares

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Tsinghua Science and Technology 2012年第3期17卷 304-309页

作者： Gang Chang Yi Zhang Danya Yao Tsinghua National Laboratory for Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China

Complete and reliable field traffic data is vital for the planning, design, and operation of urban traf- fic management systems. However, traffic data is often very incomplete in many traffic information systems, which hinders effective use of the data. Methods are needed for imputing missing traffic data to minimize the effect of incomplete data on the utilization. This paper presents an improved Local Least Squares （LLS） ap- proach to impute the incomplete data. The LLS is an improved version of the K Nearest Neighbor （KNN） method. First, the missing traffic data is replaced by a row average of the known values. Then, the vector angle and Euclidean distance are used to select the nearest neighbors. Finally, a regression step is used to get weights of the nearest neighbors and the imputation results. traffic flow volume collected in Beijing was analyzed to compare this approach with the Bayesian Principle Component Analysis （BPCA） imputation ap- proach. Tests show that this approach provides slightly better performance than BPCA imputation to impute missing traffic data.

关键词： Local Least Squares （LLS） vector angle missing value imputation traffic flow

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Microscopic car-following model for the traffic flow:the state of the art

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控制理论与应用（英文版） 2012年第2期10卷 133-143页

作者： Yongfu Li Dihua Sun College of Automation Chongqing University Chongqing 400044 China

Car following theory is an important research direction in the field of intelligent transportation systems （ITS）, it describes the one-by-one following process of vehicles on the same lane in traffic flow, and one of its important issues is congestion control To explore the strategy for controlling traffic congestion, this paper introduces and analyzes some classic car following models, and gives a systematic review of their developments. Moreover, in order to introduce the approach to analyze the stability, taking the full velocity difference （FVD） model for example, the local and asymptotic stability analysis is discussed, while the corresponding nonlinear analysis is also conducted. Then, some perspectives of the car following model are given in the final.

关键词： Intelligent transportation systems Car-following model traffic flow Stability analysis Nonlinear anal-ysis

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Stabilization of traffic flow Based on the Multiple Information of Preceding Cars

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Communications in Computational Physics 2008年第4期3卷 899-912页

作者： D.F.Xie Z.Y.Gao X.M.Zhao State Key Laboratory of Rail traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China. Institute of System Science School of Traffic and TransportationBeijing Jiaotong UniversityBeijing 100044China.

To enhance the stability of traffic flow,a new car-following model is proposed by taking into account the support of intelligent transportation system(ITS)information,which includes both the headway and the velocity difference of multiple preceding cars.The new model is based on the Optimal Velocity(OV)model and its extended models.The stability condition of the model is obtained by using the linear stability theory.Through nonlinear analysis,the modified Korteweg-de Vries equation is constructed and solved,and the traffic flow is classified into three types,i.***.stable,metastable,and unstable.The jam phase can thus be described by the kink-antikink soliton solution for the mKdV equation.The numerical simulation results show that compared with previous models considering only one of the ITS information,the proposed model can suppress traffic jams more efficiently when both headway and velocity difference of arbitrary preceding cars are taken into account.The results of numerical simulation coincide with the theoretical ones.

关键词： traffic flow car-following model stability analysis ITS information

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Recognition Method for Change Point of traffic flow Linear Regressions

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Journal of Donghua University(English Edition) 2012年第1期29卷 59-61页

作者：张敬磊王晓原马立云 School of Transportation and Vehicle Engineering Shandong University of Technology

Recognition method of traffic flow change point was put forward based on traffic flow theory and the statistical change point analysis of multiple linear regressions. The method was calibrated and tested with the field data of Liantong Road of Zibo city to verify the validity and the feasibility of the theory. The results show that change point method of multiple linear regression can make out the rule of quantitative changes in traffic flow more accurately than ordinary methods. So, the change point method can be applied to traffic information management system more effectively.

关键词： traffic flow quantitative changes multiple linear regressions change point recognition

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A Simulation Model for Mixing traffic flow at An Intersection

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Journal of Systems Engineering and Electronics 1996年第3期7卷 63-68页

作者： Juan Zhicai Chen Ling & Zhang Jie(Jilin Univ. of Technology P.R. China) Jilin Univ. of Technology P.R. China

This paper will develop a model simulation mixing traffic flow in the signal controlintersection. Applying the model, the schemes of traffic channeling and controlling in the typical intersection are analyzed and optimized and the optimal scheme make the average stop frequency be reduced by 31.8% and average stop time be reduced by 27.7%.

关键词： traffic flow Simulation model.

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A Modified Cellular Automaton Model for traffic flow

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Journal of Shanghai University(English Edition) 2004年第1期8卷 1-3页

作者：葛红霞董力耘雷丽戴世强 Shanghai Institute of Applied Mathematics and Mechanics Shanghai University Shanghai 200072 P.R. China

A modified cellular automaton model for traffic flow was proposed. A novel concept about the changeable security gap was introduced and a parameter related to the variable security gap was determined. The fundamental diagram obtained by simulation shows that the maximum flow more approaches to the observed data than that of the NaSch model, indicating that the presented model is more reasonable and realistic.

关键词： traffic flow cellular automaton model changeable security gap.

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