Analysis of Phase Transition in Traffic Flow based on a New Model of Driving Decision

Different driving decisions will cause different processes of phase transition in traffic flow.To reveal the inner mechanism, this paper built a new cellular automaton (CA) model,based on the driving decision (DD). In the DD model, a driver's decision is divided intothree stages: decision-making, action, and result. The acceleration is taken as a decisionvariable and three core factors, i.e. distance between adjacent vehicles, their own velocity,and the preceding vehicle's velocity, are considered. Simulation results show that the DDmodel can simulate the synchronized flow effectively and describe the phase transitionin traffic flow well. Further analyses illustrate that various density will cause the phasetransition and the random probability will impact the process. Compared with the traditional NaSch model, the DD model considered the preceding vehicle's velocity, the deceleration limitation, and a safe
distance, so it can depict closer to the driver preferences on pursuing safety, stability and fuel-saving and has strong theoreticalinnovation for future studies.     

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.     

A new continuum model with driver's continuous sensory memory and preceding vehicle's taillight

Car taillights are ubiquitous during the deceleration process in real traffic, while drivers have a memory for historical information. The collective effect may greatly affect driving behavior and traffic flow performance. In this paper, we propose a continuum model with the driver's memory time and the preceding vehicle's taillight. To better reflect reality, the continuous driving process is also considered. To this end, we first develop a unique version of a car-following model. By converting micro variables into macro variables with a macro conversion method, the micro car-following model is transformed into a new continuum model. Based on a linear stability analysis, the stability conditions of the new continuum model are obtained. We proceed to deduce the modified KdV-Burgers equation of the model in a nonlinear stability analysis, where the solution can be used to describe the propagation and evolution characteristics of the density wave near the neutral stability curve. The results show that memory time has a negative impact on the stability of traffic flow, whereas the provision of the preceding vehicle's taillight contributes to mitigating traffic congestion and reducing energy consumption.     

瓶颈处车辆横纵向行为建模与分析

车辆的横向偏移现象在现实的交通流中广泛存在, 交通瓶颈处的横向偏移现象往往更加显著. 车辆间横纵向的运动相互干扰, 使得瓶颈交通流组织十分混乱, 通行能力受到显著影响. 为了研究瓶颈处车辆横纵向行为规律及其对交通流的影响, 提出一个考虑横向偏移特征的车辆行为模型: 通过引入目标转向角概念,并结合经典优化速度模型, 给出了用于描述车辆的横纵向运动规律的运动方程, 同时通过分析车辆横向偏移特征, 制定了基于车辆行驶状态划分的目标转向角确定规则集. 数值模拟结果表明: 车辆的横向偏移会对交通流的运行产生影响, 在一定的横向偏移反应阈值下, 瓶颈处横向干扰于交通流的影响随着密度的增加而增加; 同时观察到了实际城市交通瓶颈的宏观及微观现象, 验证了模型的有效性. 关键词： 交通流 瓶颈 车辆行为 横向偏移特征     

Establishment,maintenance, and re-establishment of the safe and efficient steady-following state

We present an integrated mathematical model of vehicle-following control for the establishment, maintenance, and re-establishment of the previous or new safe and efficient steady-following state. The hyperbolic functions are introduced to establish the corresponding mathematical models, which can describe the behavioral adjustment of the following vehicle steered by a well-experienced driver under complex vehicle following situations. According to the proposed mathematical models, the control laws of the following vehicle adjusting its own behavior can be calculated for its moving in safety,efficiency, and smoothness(comfort). Simulation results show that the safe and efficient steady-following state can be well established, maintained, and re-established by its own smooth(comfortable) behavioral adjustment with the synchronous control of the following vehicle's velocity, acceleration, and the actual following distance.     

The effect of stochastic accelerating and delay probability with the velocity and the gap between vehicles on traffic flow

This paper proposes a new combined cellular automaton (CA) model considering the driver behavior of stochastic acceleration and delay with the velocity of the preceding vehicle and the gap between the successive vehicles based on the WWH model and the noise-first NaSch model. It introduces the delay probability varying with the gap, adds the anticipation headway and increases the acceleration with a certain probability. Through these simulations, not only can the metastable state and start--stop wave be obtained but also the synchronized flow which the wide moving jam results in. Moreover, the effect of stochastic acceleration and delay on traffic flow is discussed by analyzing the correlation of traffic data. This indicates that synchronized flow easily emerges in the critical area between free flow and synchronized flow when acceleration and delay are synchronized or their probability is close to 0.5.     

A refined cellular automaton model to rectify impractical vehicular movement behavior

When implementing cellular automata (CA) into a traffic simulation, one common defect yet to be rectified is the abrupt deceleration when vehicles encounter stationary obstacles or traffic jams. To be more in line with real world vehicular movement, this paper proposes a piecewise-linear movement to replace the conventional particle-hopping movement adopted in most previous CA models. Upon this adjustment and coupled with refined cell system, a new CA model is developed using the rationale of Forbes’ et al. car-following concept. The proposed CA model is validated on a two-lane freeway mainline context. It shows that this model can fix the unrealistic deceleration behaviors, and thus can reflect genuine driver behavior in the real world. The model is also capable of revealing Kerner’s three-phase traffic patterns and phase transitions among them. Furthermore, the proposed CA model is applied to simulate a highway work zone wherein traffic efficiency (maximum flow rates) and safety (speed deviations) impacted by various control schemes are tested.     

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     

考虑驾驶方式改变的一维元胞自动机交通流模型

在一维元胞自动机交通流WWH模型和SDNS模型的基础上,建立了考虑驾驶方式改变的元胞自动机模型（Change-CA模型）.具体描述为驾驶员可根据交通环境选择不同的驾驶方式在道路上驾车行驶,以各自的演化规则进行状态更新,同时定义了驾驶方式更新原则.通过计算机数值模拟,发现驾驶方式可变时,模型模拟得到的混合交通流流量较大;保守型驾驶方式对交通流变化的影响随改变概率增大而减少.并且在演化过程中,驾驶方式改变频率的变化趋势与改变概率、安全概率密切相关.与NS模型和SDNS模型相比,Change-CA模型减少了车流 关键词： 交通流 元胞自动机 驾驶方式 计算机数值模拟     

Traffic Modelling for Moving-Block Train Control System

This paper presents a new cellular automaton （CA） model for train control system simulation. In the proposed CA model, the driver reactions to train movements are captured by some updated rules. The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow. A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic. Not only the characteristic behavior of railway traffic flow can be reproduced, but also the simulation values of the minimum time headway are close to the theoretical values.     

Explaining traffic patterns at on-ramp vicinity by a driver perception model in the framework of three-phase traffic theory

In traffic system, driving behaviors change with the surrounding traffic perceived by drivers, resulting in the complex spatio-temporal traffic patterns. Accordingly, in the majority of traffic models, vehicle accelerations are described by dynamic equations based on driving behavior, system dynamics and some underlying steady-state velocity-gap (bumper-to-bumper spacing) relation in order to guarantee the realistic human behavior. This paper proposes a deterministic car-following model based on a multi-branch fundamental diagram with each branch representing a particular category of driving style. Furthermore, an additional dynamic perception equation is introduced to reflect the driving style adaptation in response to the change in surrounding traffic situations. With simulation based on the proposed “driver perception model” (DP model), empirical findings of traffic breakdown and observed spatio-temporal patterns at on-ramp vicinity are reproduced. Furthermore, comparison results show the consistency between numerical simulation and the real traffic data of Beijing urban freeway.     

基于驾驶员行为的元胞自动机模型研究

从研究驾驶员行为入手,分析了驾驶员行为作用机理,并结合元胞自动机(CA)模型,将与车辆自身速度、相对速度、车间距和安全车间距有关的驾驶员行为作用机理引入CA模型(简称ACA).并利用ACA模型进行微观交通仿真观察到亚稳态、相分离和回滞现象,并将ACA模型与只考虑车辆自身速度和车间距的CA模型(简称BCA)的仿真结果进行比较可得:宏观方面,从最大车流量、稳定性和堵塞消溶效率三方面进行对比,ACA模型的仿真结果显示有更高并更接近实测数据的最大流量值,有更强的稳定性,堵塞消溶的效率更高;微观方面,从车辆速度波动和车头间距波动两方面进行对比,ACA模型的仿真结果显示车辆不会骤然加速或减速,车辆能够相对均匀地分布在道路上.这些结果说明相对速度和安全间距对驾驶员行为会产生重要影响,也说明ACA模型与实际情况更符,有一定实际意义.     

Effect of driver over-acceleration on traffic breakdown in three-phase cellular automaton traffic flow models

Based on simulations with cellular automaton (CA) traffic flow models, a generic physical feature of the three-phase models studied in the paper is disclosed. The generic feature is a discontinuous character of driver over-acceleration caused by a combination of two qualitatively different mechanisms of over-acceleration: (i) Over-acceleration through lane changing to a faster lane, (ii) over-acceleration occurring in car-following without lane changing. Based on this generic feature a new three-phase CA traffic flow model is developed. This CA model explains the set of the fundamental empirical features of traffic breakdown in real heterogeneous traffic flow consisting of passenger vehicles and trucks. The model simulates also quantitative traffic pattern characteristics as measured in real heterogeneous flow.     

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.     

A New Cellular Automata Model Considering Finite Deceleration and Braking Distance

We present a new cellular automata model for one-lane traffic flow. In this model, we consider the driver prejudgment according to the state of the leading car. We also consider that the vehicle deceleration capability is finite and the braking distance of the high-speed running cars cannot be ignored, which is not considered in most models. Furthermore, comfortable driving is considered, too. Using computer simulations we obtain some basic qualitative results and the fundamental diagram of the proposed model. In comparison with the known models, we find that the fundamental diagram of the proposed model is more realistic than that of the known 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.     

A new car-following model: full velocity and acceleration difference model

By introducing acceleration difference terms into the full velocity difference models (FVDM) by Jiang et al. (1995), we present a full velocity and acceleration difference model (FVADM). The main improvement upon the previous models is that the FVADM can exactly describe the driver’s behavior under an urgent case, where no collision occurs and no unrealistic deceleration appears in this model, while vehicles determined by the previous car-following models collide after only few seconds. The model is investigated by numerical methods. The simulation results indicate that the acceleration difference has an important impact on the traffic dynamics, especially under urgent conditions. Besides the urgent situations, the model still remains similar properties to those of the FVDM. In the model, the phase transition of traffic flow is observed, and the hysteresis loop is obtained in the headway- velocity plane, also.     

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：     

New insights into traffic dynamics: a weighted probabilistic cellular automaton model

From the macroscopic viewpoint for describing the acceleration behaviour of drivers, a weighted probabilistic cellular automaton model （the WP model, for short） is proposed by introducing a kind of random acceleration probabilistic distribution function. The fundamental diagrams, the spatiotemporal patterns, are analysed in detail. It is shown that the presented model leads to the results consistent with the empiricaZ data rather well, nonlinear flow-density relationship existing in lower density regions, and a new kind of traific phenomenon called neo-synchronized flow. Furthermore, we give the criterion for distinguishing the high-speed and low-speed neo-synchronized flows and clarify the mechanism of this kind of traffic phenomenon. In addition, the result that the time evolution of distribution of headways is displayed as a normal distribution further validates the reasonability of the neo-synchronized flow. These findings suggest that the diversity and the randomicity of drivers and vehicles have indeed a remarkable effect on traffic dynamics.     

A quantum mechanics-based approach to model incident-induced dynamic driver behavior

A better understanding of the psychological factors influencing drivers, and the resulting driving behavior responding to incident-induced lane traffic phenomena while passing by an incident site is vital to the improvement of road safety. This paper presents a microscopic driver behavior model to explain the dynamics of the instantaneous driver decision process under lane-blocking incidents on adjacent lanes. The proposed conceptual framework decomposes the corresponding driver decision process into three sequential phases: (1) initial stimulus, (2) glancing-around car-following, and (3) incident-induced driving behavior. The theorem of quantum mechanics in optical flows is applied in the first phase to explain the motion-related perceptual phenomena while vehicles approach the incident site in adjacent lanes, followed by the incorporation of the effect of quantum optical flows in modeling the induced glancing-around car-following behavior in the second phase. Then, an incident-induced driving behavior model is formulated to reproduce the dynamics of driver behavior conducted in the process of passing by an incident site in the adjacent lanes. Numerical results of model tests using video-based incident data indicate the validity of the proposed traffic behavior model in analyzing the incident-induced lane traffic phenomena. It is also expected that such a proposed quantum-mechanics based methodology can throw more light if applied to driver psychology and response in anomalous traffic environments in order to improve road safety.