Cellular automaton model considering headway-distance effect

This paper presents a cellular automaton model for single-lane traffic flow. On the basis of the Nagel-Schreckenberg （NS） model, it further considers the effect of headway-distance between two successive cars on the randomization of the latter one. In numerical simulations, this model shows the following characteristics. （1） With a simple structure, this model succeeds in reproducing the hysteresis effect, which is absent in the NS model. （2） Compared with the slow-tostart models, this model exhibits a local fundamental diagram which is more consistent to empirical observations. （3） This model has much higher efficiency in dissolving congestions compared with the so-called NS model with velocitydependent randomization （VDR model）. （4） This model is more robust when facing traffic obstructions. It can resist much longer shock times and has much shorter relaxation times on the other hand. To summarize, compared with the existing models, this model is quite simple in structure, but has good characteristics.     

元胞自动机交通流模型的相变特性研究

系统地研究 VDR模型和T²模型在不同车流密度时车辆位置的相关性. 通过VDR模型、BJH模型和T²模型的序参量计算，确定在这三个模型中车流从自由流动到阻塞的相变特性，结果发现引入慢启动规则后，在不同的延迟概率和最大速度情况下，将引起交通相变特性的改变. 关键词： 交通流 元胞自动机 相关函数 序参量     

TASEP related models with traffic light boundary

Cellular automata models play an important role in traffic modeling. For some variants of the Nagel-Schreckenberg model, the effects of traffic light boundary conditions are considered. Based on previous results, the exact density profiles can be derived easily for deterministic dynamics. Additionally, the exact average outflow per traffic light cycle is presented not only in the deterministic case, but also for an important semi-stochastic variant with slow-to-start behaviour. Thereby, the models are strongly related to the well-known totally asymmetric simple exclusion process (TASEP) which can be regarded as a generic model for many driven particle systems.     

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.     

Traffic flow models with ‘slow-to-start’ rules

We investigate two models for traffic flow with modified acceleration (‘slow-to-start’) rules. Even in the simplest case v_max = 1 these rules break the ‘particle-hole’ symmetry of the model. We determine the fundamental diagram (flow-density relationship) using the so-called car-oriented mean-field approach (COMF) which yields the exact solution of the basic model with v_max = 1. Here we find that this is no longer true for the models with modified acceleration rules, but the results are still in good agreement with simulations. We also compare the effects of the two different slow-to-start rules and discuss their relevance for real traffic. In addition, in one of these models we find a new phase transition to a completely jammed state.     

A new cellular automaton for signal controlled traffic flow based on driving behaviors

The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined.     

Effect of slow-to-start in the extended BML model with four-directional traffic

In this paper, an extended Biham–Middleton–Levine (BML) model is proposed to simulate complex characteristics of four-directional traffic flow by considering the effect of slow-to-start. The simulation results show that the system does not exhibit a sharp transition from moving phase to jamming phase, which is consistent with the results of the latest studies about the original BML model. Differently from the structure geometric patterns in previous studies, a new phase separation phenomenon, i.e., the coexistence of multiple free flow stripes and multi-local jams, can be observed. The formation mechanisms of typical dynamic patterns are also explored. Furthermore, a mean field analysis for the maximum velocity in the moving phase is obtained, which is in good accordance with simulation results. In addition, an interesting feature is found that this new coexistence phenomenon of two phases is determined only by the effect of slow-to-start and is completely independent of traffic light (only considering red light and green light) period.     

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 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.     

Hysteresis Phenomenon in Deterministic Traffic Flows

We study phase transitions of a system of particles on the one-dimensional integer lattice moving with constant acceleration, with a collision law respecting slower particles. This simple deterministic “particle-hopping” traffic flow model being a straightforward generalization to the well known Nagel–Schreckenberg model covers also a more recent slow-to-start model as a special case. The model has two distinct ergodic (unmixed) phases with two critical values. When traffic density is below the lowest critical value, the steady state of the model corresponds to the “free-flowing” (or “gaseous”) phase. When the density exceeds the second critical value the model produces large, persistent, well-defined traffic jams, which correspond to the “jammed” (or “liquid”) phase. Between the two critical values each of these phases may take place, which can be interpreted as an “overcooled gas” phase when a small perturbation can change drastically gas into liquid. Mathematical analysis is accomplished in part by the exact derivation of the life-time of individual traffic jams for a given configuration of particles. This research has been partially supported by Russian Foundation for Fundamental Research and French Ministry of Education grants.     

Effect of restart at signals on traffic flow through a series of signals

We study the effect of restart at signals on the vehicular traffic controlled by a series of signals. The Nagel–Schreckenberg model (NS model) and Fukui–Ishibashi model (FI model) are applied to the vehicular motion. In the FI model, the step-by-step acceleration is not taken into account but the acceleration effect is included in the NS model. It is shown that the difference between both models results in the restart effect at signals. The extended version of the NS model with signals is formulated by the difference equation. The restart at signals has an effective effect on the traffic flow. The fundamental diagram changes highly by the restart effect. The dependences of mean speed on the cycle time are shown.     

Analytical investigation of the boundary-triggered phase transition dynamics in a cellular automata model with a slow-to-start rule

Previous studies suggest that there are three different jam phases in the cellular automata automaton model with a slow-to-start rule under open boundaries.In the present paper,the dynamics of each free-flow-jam phase transition is studied.By analysing the microscopic behaviour of the traffic flow,we obtain analytical results on the phase transition dynamics.Our results can describe the detailed time evolution of the system during phase transition,while they provide good approximation for the numerical simulation data.These findings can perfectly explain the microscopic mechanism and details of the boundary-triggered phase transition dynamics.     

One-Dimensional Particle Processes with Acceleration/Braking Asymmetry

The slow-to-start mechanism is known to play an important role in the particular shape of the Fundamental Diagram of traffic and to be associated to hysteresis effects of traffic flow. We study this question in the context of exclusion and queueing processes, by including an asymmetry between deceleration and acceleration in the formulation of these processes. For exclusions processes, this corresponds to a multi-class process with transition asymmetry between different speed levels, while for queueing processes we consider non-reversible stochastic dependency of the service rate w.r.t. the number of clients. The relationship between these 2 families of models is analyzed on the ring geometry, along with their steady state properties. Spatial condensation phenomena and metastability are observed, depending on the level of the aforementioned asymmetry. In addition, we provide a large deviation formulation of the fundamental diagram which includes the level of fluctuations, in the canonical ensemble when the stationary state is expressed as a product form of such generalized queues.     

决定论性逐步加速交通流模型的渐近稳态行为

研究Nagel-Schreckenberg(NS)交通流元胞自动机模型在不考虑车辆随机延迟情况下的决定论性模型的基本图,即渐近稳态的车流平均速度作为车辆密度的函数关系．证明决定论性NS模型,在车流的自组织作用下,其渐近稳态的基本图,与决定论性Fukui-Ishibashi(FI)交通流模型的基本图完全相同．这个结果表明,若把FI交通流模型中的车辆突然加速方式（即车辆速度可以在仅仅一个时步内加速到其最高速限M或前方空距所允许的最大速度）,改变为车辆逐步加速方式（车辆速度在每一时步中最多仅能增加一个速度单位）,则车辆的自组织相互作用,并不会改变其车流的长时间渐近稳态行为． 关键词：     

双车道多速车辆混合交通流元胞自动机模型的研究

把NaSch模型的刹车概率分开为独立的加速和减速概率，引入转道规则，建立了双车道多速车辆的混合交通流模型.通过计算机数值模拟，得出了不同参数下混合交通的速度和流量与 密度关系的基本图.结果表明，转道概率、混合比例和加减速概率对混合交通都有重要的影 响，慢车的特性对混合交通起着决定性的作用. 关键词： 元胞自动机 混合交通流 NaSch模型     

多速混合车辆单车道元胞自动机交通流模型的研究

在交通流NS模型的基础上，建立了多速混合车辆单车道元胞自动机交通流模型， 通过计算机数值模拟，得到了混合车辆在不同参数下交通流模型的基本图，并对混合交通的 特性进行了分析和讨论. 关键词： 元胞自动机 混合交通流模型 计算机模拟     

高速车随机延迟逐步加速交通流元胞自动机模型

提出介于Nagel-Schreckenberg(NS)模型和Fukui-Ishibashi(FI)模型之间的一种新的一维交通流元胞自动机模型. 此模型采用NS模型中的车辆逐步加速方式,和FI模型中的仅最大速车可随机减速的车辆延迟方式.证明新模型的基本图,即车流渐近稳态的平均速度与道路上的车辆密度之间的函数关系与FI模型的完全相同.这也就是说,只允许最高速车辆可发生延迟的FI交通流模型,如果将其突然无限制加速方式(车辆可在一个时步内从零速加速到最高速限M或车头距离所允许的最大速度),改变为车辆的逐步有限加速 关键词： 交通流 元胞自动机模型 相变基本图 Nagel-Schreckenberg模型 Fukui-Ishibashi模型     

考虑行车状态的一维元胞自动机交通流模型

在Nagel Schrekenberg单车道元胞自动机交通流模型（简称NS模型）的基础上，考虑车辆之间的相对运动薛郁等提出了一种改进的单车道元胞自动机交通流模型（简称改进的NS模型）.通过两种情况列出了改进的NS模型存在不尽周严的地方，随之在新模型中引入了行车状态 变量和反馈规则，从而控制车辆出现倒车和刹车过急等现象.通过计算机对新模型进行模拟 ，发现减速概率和车流密度对车流状态的演化影响很大，当减速概率高（如道路条件差）时 ，即使车流密度低，车流也会出现局部堵塞状态；而当减速概率一定时，随着车流密度增加 ，车流的运动相与堵塞相发生了全局性的交替出现，此时类似于波的波峰和波谷的传播.与 改进的NS模型相比较，新模型模拟的车流量较高，说明新模型减少了车流的总体停滞状态. 关键词： 交通流 元胞自动机 行车状态 反馈规则