Phases of scaling and cross-correlation behavior in traffic

While many microscopic models of traffic flow describe transitions between different traffic phases, such transitions are difficult to quantify in measured traffic data. Here we study long-term traffic recordings consisting of ≈2900$\approx 2900$ days of flow, density, and velocity time series with minute resolution from a Spanish motorway. We calculate fluctuations, cross-correlations, and long-term persistence properties of these quantities in the flow–density diagram. This leads to a data-driven definition of (local) traffic states based on the dynamical properties of the data, which differ from those given in standard guidelines. We find that detrending techniques must be used for persistence analysis because of non-stationary daily and weekly traffic flow patterns. We compare our results for the measured data with analysis results for a microscopic traffic model, finding good agreement in most quantities. However, the simulations cannot easily reproduce the congested traffic states observed in the data. We show how fluctuations and cross-correlations in traffic data may be used for prediction, i.e., as indications of increasing or decreasing velocities.     

Traffic flow characteristics in a mixed traffic system consisting of ACC vehicles and manual vehicles: A hybrid modelling approach

In this paper, we have investigated traffic flow characteristics in a traffic system consisting of a mixture of adaptive cruise control (ACC) vehicles and manual-controlled (manual) vehicles, by using a hybrid modelling approach. In the hybrid approach, (i) the manual vehicles are described by a cellular automaton (CA) model, which can reproduce different traffic states (i.e., free flow, synchronised flow, and jam) as well as probabilistic traffic breakdown phenomena; (ii) the ACC vehicles are simulated by using a car-following model, which removes artificial velocity fluctuations due to intrinsic randomisation in the CA model. We have studied the traffic breakdown probability from free flow to congested flow, the phase transition probability from synchronised flow to jam in the mixed traffic system. The results are compared with that, where both ACC vehicles and manual vehicles are simulated by CA models. The qualitative and quantitative differences are indicated.     

提高道路交通系统的驾驶安全

道路交通系统是一个复杂的系统，其中包含了人的直接参与。在该系统中，人的因素起了重要的作用。本文中，在道路系统路面的某一点设计了一种类型控制信号，该点被称为信号点。在控制信号的作用下，当车辆经过信号点的时候，车辆需要降低速度。其目的在于能够通过控制信号控制交通流的状态，使其由无序变为有序，从而提高道路系统的交通安全。应用双车道的确定性NaSch模型进行仿真模拟，结果表明不仅交通流的状态能够由无序变为有序，而且交通流的状态是安全的。     

Freezing transition in bi-directional CA model for facing pedestrian traffic

We present a bi-directional cellular automaton (CA) model for facing traffic of pedestrians on a wide passage. The excluded-volume effect and bi-directionality of facing traffic are taken into account. The CA model is not stochastic but deterministic. We study the jamming and freezing transitions when pedestrian density increases. We show that the dynamical phase transitions occur at three stages with increasing density. There exist four traffic states: the free traffic, jammed traffic 1, jammed traffic 2, and frozen state. At the frozen state, all pedestrians stop by preventing from going ahead each other. At three transitions, the pedestrian flow changes from the free traffic through the jammed traffic 1 and jammed traffic 2, to the frozen state.     

自动巡航混合交通系统的研究

基于自动驾驶原理,建立了单车道上由两种长度、可分别以不同的最大速度行驶、具有自动巡航驾驶功能的车辆构成的混合交通流模型.通过计算机数值模拟,得到了混合车流在不同参数下交通流模型的基本图,并借助平均场理论对其进行解析.得到的理论结果与实验模拟相一致. 关键词： 元胞自动机 自动巡航控制系统 临界占用率 临界密度     

A game theory model of urban public traffic networks

We have studied urban public traffic networks from the viewpoint of complex networks and game theory. Firstly, we have empirically investigated an urban public traffic network in Beijing in 2003, and obtained its statistical properties. Then a simplified game theory model is proposed for simulating the evolution of the traffic network. The basic idea is that three network manipulators, passengers, an urban public traffic company, and a government traffic management agency, play games in a network evolution process. Each manipulator tries to build the traffic lines to magnify its “benefit”. Simulation results show a good qualitative agreement with the empirical results.     

Traffic flow prediction based on BILSTM model and data denoising scheme

Accurate prediction of road traffic flow is a significant part in the intelligent transportation systems. Accurate prediction can alleviate traffic congestion, and reduce environmental pollution. For the management department, it can make effective use of road resources. For individuals, it can help people plan their own travel paths, avoid congestion, and save time. Owing to complex factors on the road, such as damage to the detector and disturbances from environment, the measured traffic volume can contain noise. Reducing the influence of noise on traffic flow prediction is a piece of very important work. Therefore, in this paper we propose a combination algorithm of denoising and BILSTM to effectively improve the performance of traffic flow prediction. At the same time, three denoising algorithms are compared to find the best combination mode. In this paper, the wavelet (WL) denoising scheme, the empirical mode decomposition (EMD) denoising scheme, and the ensemble empirical mode decomposition (EEMD) denoising scheme are all introduced to suppress outliers in traffic flow data. In addition, we combine the denoising schemes with bidirectional long short-term memory (BILSTM) network to predict the traffic flow. The data in this paper are cited from performance measurement system (PeMS). We choose three kinds of road data (mainline, off ramp, on ramp) to predict traffic flow. The results for mainline show that data denoising can improve prediction accuracy. Moreover, prediction accuracy of BILSTM+EEMD scheme is the highest in the three methods (BILSTM+WL, BILSTM+EMD, BILSTM+EEMD). The results for off ramp and on ramp show the same performance as the results for mainline. It is indicated that this model is suitable for different road sections and long-term prediction.     

Phase transition of traffic states with on-ramp

We study the phase transition on a highway in a modified anisotropic continuum model with an on-ramp, which is recently developed by Gupta and Katiyar (J. Phys. A: Math. Nucl. Gen. 38 (2005) 4069]. To investigate whether this model can describe several distinct traffic states that are identified from real-traffic data [Kerner and Rehborn, Phys. Rev. Lett. 79 (1997) 4030; Kerner, Phys. Rev. Lett. 81 (1998) 3797], we carry out numerical simulations with an open boundary condition. The observed transition between free flow and various types of congested flow such as localized clusters, stop-and-go traffic and different kinds of synchronized traffic flow is obtained by applying a triggering pulse through an on-ramp in our simulation.We present the phase diagram for three representative values of the upstream boundary flux and for the whole range of the on-ramp flux. Several states like pinned localized cluster, triggered stop-and-go, recurring hump state, the oscillatory congested traffic and the homogeneous congested traffic are observed in phase transition from free flow to traffic-jam state. The phase diagram for our model near on-ramp is consistent with the results obtained by Lee et al. [Phys. Rev. E 59(5) (1999) 5101]. The results suggest that the modified model is able to describe all the three phases of traffic-flow theory developed by Kerner [Physica A 333 (2004) 379].     

道路交通流状态的多参数融合预测方法

针对道路交通流普遍存在的混沌特性以及单交通参数不足 以全面反映交通流状态的实际情况,考虑交通动力学系统中多个 交通参数之间的关联关系,提出一种新的多参数混沌时间序列预 测算法.该算法在相空间重构理论的基础上,借助Bayes估计将多个参数在 同一高维相空间中进行相点最优融合,从而增加重构相空间的系统信息量, 使得相空间的相点轨迹更加逼近原交通系统的动力学行为.同时借鉴单 参数混沌时间序列预测方法,从不同角度对动力学系统的运动状态进行描 述,以实现多参数时间序列的混沌预测.实验结果表明,通过融合多交通参数时 间序列,获得了更加完整的交通流状态变化特征.与单交通参数时间序列的预测 结果相比,其预测误差显著降低,均衡系数相应增大,提高了交通流状态预测的准确率.     

A New Macro Model for Traffic Flow on a Highway with Ramps and Numerical Tests

In this paper, we present a new macro model for traffic flow on a highway with ramps based on the existing models. We use the new model to study the effects of on-off-ramp on the main road traffic during the morning rush period and the evening rush period. Numerical tests show that, during the two rush periods, these effects are often different and related to the status of the main road traffic. If the main road traffic flow is uniform, then ramps always produce stop-and-go traffic when the main road density is between two critical values, and ramps have little effect on the main road traffic when the main road density is less than the smaller critical value or greater than the larger critical value. If a small perturbation appears on the main road, ramp may lead to stop-and-go traffic, or relieve or even eliminate the stop-and-go traffic, under different circumstances. These results are consistent with real traffic, which shows that the new model is reasonable.     

Effective strategy of adding nodes and links for maximizing the traffic capacity of scale-free network

In this paper, we propose an efficient strategy to enhance traffic capacity via the process of nodes and links increment. We show that by adding shortcut links to the existing networks, packets are avoided flowing through hub nodes. We investigate the performances of our proposed strategy under the shortest path routing strategy and the local routing strategy. Our obtained results show that using the proposed strategy, the traffic capacity can be effectively enhanced under the shortest path routing strategy. Under the local routing strategy, the obtained results show that the proposed strategy is efficient only when packets are more likely to be forwarded to low-degree nodes in their routing paths. Compared with other strategies, the obtained results indicate that our proposed strategy of adding nodes and links is the most effective in enhancing the traffic capacity, i.e., the traffic capacity can be maximally enhanced with the least number of additional nodes and links.     

Second-order phase transition in two-dimensional cellular automaton model of traffic flow containing road sections

Two-dimensional cellular automaton model has been broadly researched for traffic flow, as it reveals the main characteristics of the traffic networks in cities. Based on the BML models, a first-order phase transition occurs between the low-density moving phase in which all cars move at maximal speed and the high-density jammed phase in which all cars are stopped. However, it is not a physical result of a realistic system. We propose a new traffic rule in a two-dimensional traffic flow model containing road sections, which reflects that a car cannot enter into a road crossing if the road section in front of the crossing is occupied by another car. The simulation results reveal a second-order phase transition that separates the free flow phase from the jammed phase. In this way the system will not be entirely jammed (“don’t block the box” as in New York City).     

Phase diagrams in unidirectionally coupled map lattice for open traffic flow

The jamming transition from the free traffic to the oscillatory traffic is investigated with the unidirectionally coupled map lattice model which has the hyperbolic tangent local map. Spatio-temporal structures in the jamming transition are found with the use of numerical simulation. The traffic states are studied for both constant and noisy boundary conditions. We show the phase diagrams of different kinds of congested traffic. It is found that the noise at the boundary has an important effect on the traffic states. The traffic behavior in the coupled map lattice model exhibits a jamming transition similar to that found in the car-following model.     

Techniques for the investigation of road traffic noise in regions of restricted flow by the use of digital computer simulation methods

Computer methods of calculating and predicting the noise from road traffic operating in restricted flow conditions are discussed. A method of calculating the noise from road traffic as a function of the manoeuvring parameters by means of a Monte Carlo digital computer simulation model is briefly described. The model is used in deriving correction contours for single streams of traffic which enable free flow L₁₀ levels to be modified to allow for a flow restriction. Flow restrictions of the type encountered at traffic signals, priority intersections and pelican crossings are considered. The contours cover a stretch of road 600 m long and a distance of 60 m from the kerb line and in general show a reduction in L₁₀ level in transferring from the free to the restricted flow situation. A method of applying the contours as a modification of the United Kingdom Department of the Environment prediction method for L₁₀ is proposed and compared with experimental results. Computer simulation models of complete road intersections are discussed. Two types of intersection controls are considered, the traffic signal control and the roundabout. The results of the two types of simulation are compared and the L₁₀ level adjacent to the accelerating traffic streams is generally found to be greater than that adjacent to decelerating streams. Experimental results for both types of intersection are compared with simulation runs in which the observed traffic parameters are used.     

Fluctuations in airport arrival and departure traffic: A network analysis

Air traffic is a typical complex system,in which movements of traffic components(pilots,controllers,equipment,and environment),especially airport arrival and departure traffic,form complicated spatial and temporal dynamics.The fluctuations of airport arrival and departure traffic are studied from the point of view of networks as the special correlation between different airports.Our collected flow volume data on the time-dependent activity of US airport arrival and departure traffic indicate that the coupling between the average flux and the fluctuation of an individual airport obeys a certain scaling law with a wide variety of scaling exponents between 1/2 and 1.These scaling phenomena can explain the interaction between the airport internal dynamics(e.g.queuing at airports,a ground delay program and following flying traffic) and a change in the external(network-wide) traffic demand(e.g.an increase in traffic during peak hours every day),allowing us to further understand the mechanisms governing the collective behaviour of the transportation system.We separate internal dynamics from external fluctuations using a scaling law which is helpful for us to systematically determine the origin of fluctuations in airport arrival and departure traffic,uncovering the collective dynamics.Hot spot features are observed in airport traffic data as the dynamical inhomogeneity in the fluxes of individual airports.The intrinsic characteristics of airport arrival and departure traffic under severe weather is discussed as well.     

Theoretical vs. empirical classification and prediction of congested traffic states

Starting from the instability diagram of a traffic flow model, we derive conditions for the occurrence of congested traffic states, their appearance, their spreading in space and time, and the related increase in travel times. We discuss the terminology of traffic phases and give empirical evidence for the existence of a phase diagram of traffic states. In contrast to previously presented phase diagrams, it is shown that “widening synchronized patterns” are possible, if the maximum flow is located inside of a metastable density regime. Moreover, for various kinds of traffic models with different instability diagrams it is discussed, how the related phase diagrams are expected to approximately look like. Apart from this, it is pointed out that combinations of on- and off-ramps create different patterns than a single, isolated on-ramp.     

The theoretical analysis of the lattice hydrodynamic models for traffic flow theory

The lattice hydrodynamic model is not only a simplified version of the macroscopic hydrodynamic model, but also connected with the microscopic car following model closely. The modified Korteweg-de Vries (mKdV) equation related to the density wave in a congested traffic region has been derived near the critical point since Nagatani first proposed it. But the Korteweg-de Vries (KdV) equation near the neutral stability line has not been studied, which has been investigated in detail for the car following model. We devote ourselves to obtaining the KdV equation from the original lattice hydrodynamic models and the KdV soliton solution to describe the traffic jam. Especially, we obtain the general soliton solution of the KdV equation and the mKdV equation. We review several lattice hydrodynamic models, which were proposed recently. We compare the modified models and carry out some analysis. Numerical simulations are conducted to demonstrate the nonlinear analysis results.     

Controlling Disorder in Traffic Flow by Perturbation

We propose a new technique for controlling disorder in traffic system. A kind of control signal which can be considered as a perturbation has been designated at a given site (perturbation point) of the single-lane highway. When a vehicle passes the perturbation point at a time, the velocity of the vehicle will be changed at the next time by the perturbation. This technique is tested for the deterministic NaSch traffic model. The simulation results indicate that the traffic system can be transited from the disorder states to the order states, such as fixed-point, periodic motion, etc.     

Network traffic behaviour near phase transition point

We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.     

Controlling Disorder in Traffic Flow by Perturbation

We propose a new technique for controlling disorder in traffic system. A kind of control signal which can be considered as a perturbation has been designated at a given site (perturbation point) of the single-lane highway. When a vehicle passes the perturbation point at a time, the velocity of the vehicle will be changed at the next time by the perturbation. This technique is tested for the deterministic NaSch traffic model. The simulation results indicate that the traffic system can be transited from the disorder states to the order states, such as fixed-point, periodic motion, etc.