The scientific field of traffic engineering encompasses a rich set of mathematical techniques, as well as researchers with entirely different backgrounds. This paper provides an overview of what is currently the state-of-the-art with respect to traffic flow theory. Starting with a brief history, we introduce the microscopic and macroscopic characteristics of vehicular traffic flows. Moving on, we review some performance indicators that allow us to assess the quality of traffic operations. A final part of this paper discusses some of the relations between traffic flow characteristics, i.e., the fundamental diagrams, and sheds some light on the different points of view adopted by the traffic engineering community.
To gain essential understandings of traffic flow, four theorems are derived to establish the kinematics of the basic unit of traffic flow, namely two consecutive vehicles. The first is to determine the two critical distances of the vehicle spacing, the second is to derive the spacing margin and the critical distance difference as well as the relationship they must satisfy, the third is to complete the mathematical definition and give the necessary and sufficient condition for the time headway to remain constant, and the fourth is to derive the governing equation of the spacing margin and deter…
Reply to "What Faster-than-traffic Characteristic Speeds Mean for Vehicular Traffic Flow"
这一贡献是对H. M. Zhang的论文“What Faster-than-traffic Characteristic Speeds Mean for Vehicular Traffic Flow”，该论文对发表在本期《欧洲物理杂志B》上的手稿“On the Controversy around Daganzo's Approximation for and Aw-Rascle's Resurrection of Second-Order Traffic Flow Models”进行了评论。作者澄清了几点，并同意，适当的实验可以是一种方法来决定传播速度比车辆的速度是否存在争议。此外，他还提出了一个综合的理论，这是既在理论上一致，实践相关。
This paper aims to the conditions of traffic flow evolving to stability and the stability of equilibrium under demand time-varying of traffic networks. The general framework of the evolution of flow dynamics by adopting evolutionary game theory and dynamic system stability theory is proposed. The multi group and multi criteria travel choice flow evolution dynamic model is carried out.
With the widely used method of correlation matrix analysis, this study reveals the change of traffic states on parallel motorways in North Rhine-Westphalia, Germany. In terms of the time series of traffic flow and velocity, we carry out a quantitative analysis in correlations and reveal a high level of strongly positive traffic flow correlation and rich structural features in the corresponding correlation matrices. The strong correlation is mainly ascribed to the daily time evolution of traffic flow during the periods of rush hours and non-rush hours. In terms of free flow and congestion, the …
The emergence dynamics of traffic instability has always attracted particular attention. For several decades, researchers have studied the stability of traffic flow using deterministic traffic models, with less emphasis on the presence of stochastic factors. However, recent empirical and theoretical findings have demonstrated that the stochastic factors tend to destabilize traffic flow and stimulate the concave growth pattern of traffic oscillations. In this paper, we derive a string stability condition of a general stochastic continuous car-following model by the mean of the generalized Lyapu…
In this paper, we present a new approach that generalizes the existing second-order hydrodynamic traffic models. In the proposed approach, we use the expression for the relative velocity of disturbances propagation in traffic flow. We show that properties of any phenomenological model are fully defined by how the relative velocity of disturbances propagation expressed in the model. We verify the proposed approach through simulations of the Interstate 580 freeway segment in California, USA, with traffic measurements from the Performance Measurement System (PeMS).
Microscopic Theory of Traffic Flow Instability Governing Traffic Breakdown at Highway Bottlenecks: Growing Wave of Increase in Speed in Synchronized Flow
A critical analysis of the effect of autonomous driving vehicles on traffic breakdown in mixed traffic flow is made. Classical adaptive cruise control (ACC) and ACC based on three-phase traffic theory (TPACC) are considered. We show that within a wide range of dynamic parameters of classical ACC, the ACC-vehicles can initiate traffic breakdown and reduce highway capacity. Contrarily, in the same range of parameters of TPACC, the TPACC-vehicles do not initiate traffic breakdown. To understand physical reasons for the effect of classical ACC- and TPACC-vehicles on traffic breakdown, we introduce…
Recent applications of a new methodology to measure fundamental traffic relations on freeways shows that many of the critical parameters of the flow-density and speed-spacing diagrams depend on vehicle length. In response to this fact, we present in this work a generalization of the Prigogine-Herman traffic equation for aggressive drivers which takes into account the fact that vehicles are not point-like objects but have an effective length. Our approach is similar to that introduced by Enskog for dense gases and provides the construction of fundamental diagrams which are in excellent agreemen…
A novel constructive mathematical model based on the multifractal formalism in order to accurately characterizing the localized fluctuations present in the course of traffic flows today high-speed computer networks is presented. The proposed model has the target to analyze self-similar second-order time series representative of traffic flows in terms of their roughness and impulsivity.
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；Xiamen University（厦门大学）；National University of Singapore（新加坡国立大学）
Deep neural networks are being increasingly used for short-term traffic flow prediction, which can be generally categorized as convolutional (CNNs) or graph neural networks (GNNs). CNNs are preferable for region-wise traffic prediction by taking advantage of localized spatial correlations, whilst GNNs achieves better performance for graph-structured traffic data. When applied to region-wise traffic prediction, CNNs typically partition an underlying territory into grid-like spatial units, and employ standard convolutions to learn spatial dependence among the units. However, standard convolution…
