First order phase transition from free flow to synchronized flow in a cellular automata model

This paper presents an improved cellular automata model, which is based on three phase traffic theory and can reproduce the first order phase transition from free flow to synchronized flow. The fundamental diagram, the spacetime plots, and the 1-min average flux density diagram are presented. The autocorrelation and cross correlation functions are studied to identity the synchronized flow state. It is shown that the results of the model are well consistent with the empirical findings.     

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.     

Cellular automaton model within the fundamental-diagram approach reproducing some findings of the three-phase theory

We propose a simple cellular automaton for traffic flow within the fundamental diagram, which could reproduce aspects of the three-phase theory. This so-called average space gap model (ASGM) is based on the Nagel–Schreckenberg model with additional slow-to-start and anticipation rules. The anticipation rule takes into account the average space gap of multiple leading vehicles and conveys to the model its three-phase property. Due to the anticipation rule, ASGM can show the transition from free flow to synchronized flow. Due to the slow-to-start rule, ASGM can show the spontaneous wide moving jam emerges in the synchronized flow. Simulations are carried out for periodic and open boundary conditions. Under periodic boundary condition, the fundamental diagram, and the properties of synchronized flow are studied. Under open boundary condition, different congested patterns induced by an on-ramp are analyzed. We found that the ASGM produces the same spatiotemporal dynamics as many of the more complex three-phase models. Due to its simplicity and its close relation to conventional slow-to-start models, this model can shed light on the relation between ‘two-phase’ and three-phase models.     

Modelling widely scattered states in ‘synchronized’ traffic flow and possible relevance for stock market dynamics

Traffic flow at low densities (free traffic) is characterized by a quasi-one-dimensional relation between traffic flow and vehicle density, while no such fundamental diagram exists for ‘synchronized’ congested traffic flow. Instead, a two-dimensional area of widely scattered flow-density data is observed as a consequence of a complex traffic dynamics. For an explanation of this phenomenon and transitions between the different traffic phases, we propose a new class of molecular-dynamics like microscopic traffic models based on times to collisions and discuss the properties by means of analytical arguments. Similar models may help to understand the laminar and turbulent phases in the dynamics of stock markets as well as the transitions among them.     

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].     

Cellular automaton model in the fundamental diagram approach reproducing the synchronized outflow of wide moving jams

Velocity effect and critical velocity are incorporated into the average space gap cellular automaton model [J.F. Tian, et al., Phys. A 391 (2012) 3129], which was able to reproduce many spatiotemporal dynamics reported by the three-phase theory except the synchronized outflow of wide moving jams. The physics of traffic breakdown has been explained. Various congested patterns induced by the on-ramp are reproduced. It is shown that the occurrence of synchronized outflow, free outflow of wide moving jams is closely related with drivers time delay in acceleration at the downstream jam front and the critical velocity, respectively.     

考虑动态车间距的一维元胞自动机交通流模型

基于NaSch元胞自动机交通流模型, 考虑司机复杂的性格特征和驾驶行为差异, 引入相邻车辆的动态车间距, 提出了一个改进的单车道元胞自动机交通流模型. 通过数值模拟得到了流量-密度关系, 在中高密度区域呈现出一种弥散分布的状态而非惟一确定的关系, 再现了交通系统中的自由流、同步流及宽幅运动阻塞, 表明道路上即使没有交通瓶颈也会出现同步流和拥挤交通, 同时揭示了在同步流中存在的车辆高速跟驰现象, 高速跟驰率与交通实测结果较为符合.     

The influence of nonmonotonic synchronized flow branch in a cellular automaton traffic flow model

In this paper we study the congested patterns upstream of an isolated on-ramp in a cellular automaton traffic flow model, which is proposed in our previous paper [Cheng-Jie Jin, Wei Wang, Rui Jiang, Kun Gao, J. Stat. Mech (2010) P03018]. The simulation results under open boundary conditions are presented by spatiotemporal diagrams. Our diagram of congested patterns is quite similar to that of the cellular automaton models within Kerner’s three-phase traffic theory, while some differences in the “moving synchronized flow pattern” (MSP) should be noted. In our model the upstream front of MSP propagates not only upstream, but also downstream. The propagation direction depends on the flow rates and densities of free flow and synchronized flow. Besides, in our model the outflow of wide moving jams or bottlenecks could be free flow or synchronized flow, as reported in many empirical data. In the dissolving of congestions, the form of free flow may be hindered and stable synchronized flow may emerge. This phenomenon can help us understand more about the outflow. All the interesting characteristics of our model are due to the nonmonotonic structure of synchronized flow branch in the fundamental diagram, which has not been found in previous models.     

Simulating synchronized traffic flow and wide moving jam based on the brake light rule

A new cellular automaton (CA) model based on brake light rules is proposed, which considers the influence of deterministic deceleration on randomization probability and deceleration extent. To describe the synchronized flow phase of Kerner’s three-phase theory in accordance with empirical data, we have changed some rules of vehicle motion with the aim to improve speed and acceleration vehicle behavior in synchronized flow simulated with earlier cellular automaton models with brake lights. The fundamental diagrams and spatial–temporal diagrams are analyzed, as well as the complexity of the traffic evolution, the emergence process of wide moving jam. Simulation results show that our new model can reproduce the three traffic phases: free flow, synchronized flow and wide moving jam. In addition, our new model can well describe the complexity of traffic evolution: (1) with initial homogeneous distribution and large densities, the traffic will evolve into multiple steady states, in which the numbers of wide moving jams are not invariable. (2) With initial homogeneous distribution and the middle range of density, the wide moving jam will emerge stochastically. (3) With initial mega-jam distribution and the density close to a point with the low value, the initial mega-jam will disappear stochastically. (4) For the cases with multiple wide moving jams, the process is analyzed involving the generation of narrow moving jam due to “pinch effect”, which leads to wide moving jam emergence.     

Synchronized Flow in a Cellular Automaton Model with Time Headway Dependent Randomization

We propose another possible mechanism of synchronized flow, i,e. that a time headway dependent randomization can exhibit synchronized flow. Based on this assumption, we present a new cellular automaton （CA） model for traffic flow, in which randomization effect is enhanced with the decrease of time headway. We study fundamental diagram and spatial-temporal diagrams of the model and perform microscopic analysis of time series data, which shows the model could reproduce synchronized flow as expected. It is also shown that a spontaneous transition from synchronized flow to jam could be observed by incorporating slow-to-start effect into the model. We expect that our work could contribute to the understanding of the real origin of synchronized flow.     

Noise-Induced Phase Transition in Traffic Flow

One of the dynamic phases of the traffic flow is the traffic jam. It appears in traffic flow when the vehicledensity is larger than the critical value. In this paper, a new method is presented to investigate the traffic jam when thevehicle density is smaller than the critical value. In our method, we introduce noise into the traffic system after sufficienttransient time. Under the effect of noise, the traffic jam appears, and the phase transition from tree to synchronized flowoccurs in traffic flow. Our method is tested for the deterministic NaSch traffic model. The simulation results demonstratethat there exist a broad range of lower densities at which the noise effect leading to traffic jam can be observed.     

Phase transition in a mixture of adaptive cruise control vehicles and manual vehicles

In this paper, we have investigated the effects of adaptive cruise control (ACC) vehicles in a mixture with manually-controlled (manual) vehicles. The manual vehicles are simulated by using the modified comfortable driving model, which can describe synchronized traffic flow. The phase transition probabilities from free flow to synchronized flow and from synchronized flow to jams are studied. The impact of ACC vehicles on the flow rates in free flow and synchronized flow and on the propagation velocity of the downstream front of jams are investigated. The dependence of microscopic properties of traffic flow, including the spatiotemporal patterns and the velocity distribution, is explored. Our results are expected to be useful for developing ACC systems.     

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.     

Presence of many stable nonhomogeneous states in an inertial car-following model

We present a single lane car- following model of traffic flow which is inertial and free of collisions. It demonstrates observed features of traffic flow such as existence of three regimes: free, nonhomogeneous congested (NHC) or synchronized, and homogeneous congested (HC) or jammed flow; bistability of free and NHC flow states in a range of densities, hysteresis in transitions between these states; jumps in the density-flux plane in the NHC regime; gradual spatial transition from synchronized to free flow; long survival time of jams in the HC regime. The model predicts that in the NHC regime there exist many stable states with different wavelengths, and noise can cause transitions between them.     

驾驶员属性对信号灯路口交通流的影响研究

采用元胞自动机模型研究信号灯路口的交通流特性,系统地分析了与性别、驾驶经验、性格等驾驶员属性相关的驾驶行为对交通流的影响.数值模拟发现,技术生疏或紧张驾驶、急躁行驶等驾驶行为更易引发自由流到阻塞流的相变,是路口通行低效率及事故隐患的重要原因,信号周期是影响流量与个人通行时间公平的主要因素.     

Macroscopic phase states of traffic flow in tunnels

The studies of traffic flows are reviewed and different approaches in the analysis of the phase states of flows and the fundamental diagram are described. A comparison with the experimental results is performed. The attention is focused on the analysis of the empirical data collected on the linear branch of the Lefortovo tunnel (Moscow’s third ring road). The analysis performed gives a fundamental diagram with a very complex structure. It is shown that the congested traffic flow observed in the tunnel can be considered indeed as cooperative vehicle motion. In particular, it is established that there are long-scale spatial correlations in the motion speed and that the fundamental diagram contains a region of widely scattered states. These two features are typical of phase cooperative vehicle motion. The phase portrait of the traffic flow dynamics is analyzed. Two regions with radically different properties, separated by a narrow layer with a nearly constant vehicle density, are revealed. One of these regions corresponds to cooperative vehicle motion and contains a core with chaotic dynamics. The other part of the phase plane describes the jammed phase formation.     

Towards the bi-directional cellular automaton model with perception ranges

The traditional cellular automaton (CA) model assumes that drivers only receive information from the preceding vehicles, e.g. the brake light information. However, in reality, drivers not only perceive information from downstream but can also get upstream information, e.g. the honk stimulation. The CA model involving traffic information from downstream and upstream is called the bi-directional CA model here. Meanwhile, with the introduction of Connected Vehicle Technologies, the perception range of drivers is expected to significantly increase which can lead to more informed driving behavior. Such an impact cannot be easily modeled by traditional one-directional CA models. In this study, the perception ranges of both the brake light effect and honk stimulation are introduced into the bi-directional CA model. Fundamental diagrams and spatial–temporal diagrams are then analyzed and two methods, i.e. the traffic flow interruption effect and microscopic analysis of time series data, are utilized to distinguish the synchronized traffic flow. Further numerical results illustrate that the perception range and slow-to-start sensitivity threshold are two important factors to reproduce the synchronized flow, and consideration of the honk information and the larger perception range both benefit the stability of traffic flow, which implies the potential significance of the application of Connected Vehicle Technologies.     

Synchronized traffic flow simulating with cellular automata model

The synchronized flow traffic phase of Kerner’s three-phase traffic theory can be well reproduced by the model proposed by Jiang and Wu [R. Jiang, Q.S. Wu, J. Phys. A: Math. Gen. 36 (2003) 381]. But in the Jiang and Wu model, the rule for brake light-after switching on, the brake light will not set off until the vehicle accelerates-is obviously unrealistic. Thus we improved the model by considering the difference in accelerating and decelerating performance under different driving conditions. The fundamental diagram and spatial-temporal diagrams are analyzed. We confirmed that the new model could reproduce the synchronized flow by two methods, i.e. the traffic flow interruption effect and performing microscopic analysis of time series data. Simulation results show that the decelerating difference is an important factor to reproduce the synchronized flow. We expect that our work could make contributions to understanding the mechanism of the synchronized flow.     

A modified weighted probabilistic cellular automaton traffic flow model

This paper modifies the weighted probabilistic cellular automaton model (Li X L, Kuang H, Song T, et al 2008 Chin. Phys. B 17 2366) which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits. In the new model, the effects of the velocity at the last time step and drivers' desire for acceleration are taken into account. The fundamental diagram, spatial-temporal diagram, and the time series of one-minute data are analyzed. The results show that this model reproduces synchronized flow. Finally, it simulates the on-ramp system with the proposed model. Some characteristics including the phase diagram are studied.     

A cellular automata model for highway traffic

We present results relative to a simple cellular automata model without periodic boundary conditions for an highway with on-ramps. Simulations performed with this model reproduce experimental phenomena observed in traffic such as free flow, synchronized flow, congested flow, lane inversion, forward and backward propagating waves. On-ramps play the important role of nucleation points for the dynamic features of traffic. Received 4 February 2000 and Received in final form 5 May 2000