具有加权顾前势的交通流模型

交通流随机行为的研究对于理解交通系统的内在演化规律具有重要作用. 基于元胞自动机模型和顾前势模型, 提出了一种考虑加权顾前势的交通流模型. 通过引入顾前势加权系数及对越靠近自身车辆的相互作用势赋予越大的权重, 使得建模过程更符合实际交通中司机根据前面车辆和环境情况进行随机决策的过程. 通过数值模拟, 再现了丰富的高密度交通行为. 仿真结果表明, 加权系数在高密度情况下作用明显, 更有利于在保持较高交通密度的同时, 具有较高的交通流量和道路通行能力. 关键词： 交通流 顾前势 随机模型 加权     

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.     

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     

高速跟驰交通流动力学模型研究

为研究道路交通中的高速跟驰物理现象,针对高速跟驰车辆特点,综合考虑了驾驶员换道决策行为以及随机慢化等因素,结合前景理论等方法,提出了一种用于模拟道路交通流中高速跟驰物理现象的动力学模型(简称HCCA模型).通过计算机数值模拟,研究了高速跟驰交通流物理现象演化机理及高速跟驰特性.结果表明:与对称的双车道元胞自动机动力学模型相比,本文建立的HCCA动力学模型能够再现道路高速跟驰物理现象,并得到了道路小间距高速跟驰率超过7%的结果与实测结果相符合,最后模拟得到了丰富的交通物理现象,再现了自由流、同步流及运动阻塞等复杂交通物理现象.     

基于元胞自动机的行人和机动车相互干扰机理研究

在行人流量大的人行横道处,机动车和行人之间存在较为严重的干扰.通过引入行人和机动车的冲突干扰规则, 构建了能够刻画人行横道处机动车和行人相互干扰行为的元胞自动机模型.通过数值模拟研究了行人到达率、机动车到达率、 行人冒险穿越机动车道的阈值以及行人对机动车敏感系数等因素对机动车和行人流量的影响. 模拟结果显示,所提出的模型很好地反映了行人与机动车之间的干扰特性;随着行人冒险穿越机动车道的阈值的增加, 机动车流量增大,行人流量减小;随着行人对机动车敏感系数的增加,行人避让概率减小,机动车流量减小,行人流量增大. 所得结果对混合交通的控制和管理具有一定的指导意义.     

Station Model for Rail Transit System Using Cellular Automata

In this paper, we propose a new cellular automata model to simulate the railway traffic at station. Based on NaSch model, the proposed station model is composed of the main track and the siding track. Two different schemes for trains passing through station are considered. One is the scheme of ＂pass by the main track, start and stop by the siding track＂. The other is the scheme of ＂two tracks play the same role＂. We simulate the train movement using the proposed model and analyze the traffic flow at station. The simulation results demonstrate that the proposed cellular automata model can be successfully used for the simulations of railway traffic. Some characteristic behaviors of railway traffic flow can be reproduced. Moreover, the simulation values of the minimum headway are close to the theoretical values. This result demonstrates the dependability and availability of the proposed model.     

Cellular automaton model for traffic flow based on safe driving policies and human reactions

This paper proposes a new single-lane cellular automaton model for traffic flow. The model takes into account normal drivers’ spacing policies and transportation engineering practices to guarantee that microscopic vehicle behavior is more in line with vehicular movement in the real world. As a result, drivers’ reactions are based on a safety analysis that determines the most appropriate action for a vehicle to take. Hence, the model introduces a new set of simple rules to change the speed of vehicles that incorporates three important thresholds required by the follower vehicle to accelerate, slow down or maintain its speed. Thus, the space gap, relative speed and limited acceleration/deceleration capabilities are introduced into simulations. Simulation results obtained from a system with periodic conditions show that the model can smooth the speed drop when vehicles approach the upstream front of the traffic jam. Therefore, the model avoids unrealistic deceleration behavior found in most previous cellular automata models. Besides, the model is also capable of reproducing most empirical findings including the three states of traffic flow, the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Moreover, the new model preserves the computational simplicity of the cellular automata models.     

敏感换道对下匝道系统交通流的影响

在NaSh模型基础上,充分考虑驾驶员在匝口指示牌的诱导作用下驾驶方式的变化,定义了车辆在匝口上游的换道、直行驾驶规则,提出了敏感换道的元胞自动机下匝道交通流模型. 通过计算机数值模拟,结果表明：敏感换道过程能减少直行车道上的转出车辆比例,对非必要的换道行为有明显的抑制作用,且随敏感换道区长度增加,该作用越明显;匝口提示位置并非越长越好,系统转出车辆比例越小,系统所需的最佳敏感换道区长度越短. 工程设计中根据转出车辆比例选取一个适宜距离安放匝口指示牌,能有效增加系统流量和临界加入概率. 关键词： 交通流 元胞自动机 驾驶方式 计算机数值模拟     

Energy-optimal control model for train movements

In this paper, we propose a new cellular automaton (CA) model for train movement simulations under mixed traffic conditions. A kind of control strategy is employed for trains to reduce energy consumption. In the proposed CA model, the driver controls the train movements by using some updated rules. In order to obtain a good insight into the evolution behaviours of the rail traffic flow, we investigate the space--time diagram of the rail traffic flow and the trajectories of the train movements. The numerical simulation results demonstrate that the proposed CA model can well describe the dynamic behaviours of the train movements. Some complex phenomena of train movements can be reproduced, such as the train delay propagations, etc.     

An extended smart driver model considering electronic throttle angle changes with memory

Based on the fact that the electronic throttle angle effect performs well in the traditional car following model,this paper attempts to introduce the electronic throttle angle into the smart driver model(SDM)as an acceleration feedback control term,and establish an extended smart driver model considering electronic throttle angle changes with memory(ETSDM).In order to show the practicability of the extended model,the next generation simulation(NGSIM)data was used to calibrate and evaluate the extended model and the smart driver model.The calibration results show that,compared with SDM,the simulation value based on the ETSDM is better fitted with the measured data,that is,the extended model can describe the actual traffic situation more accurately.Then,the linear stability analysis of ETSDM was carried out theoretically,and the stability condition was derived.In addition,numerical simulations were explored to show the influence of the electronic throttle angle changes with memory and the driver sensitivity on the stability of traffic flow.The numerical results show that the feedback control term of electronic throttle angle changes with memory can enhance the stability of traffic flow,which shows the feasibility and superiority of the proposed model to a certain extent.     

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.     

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.     

Cellular automata model for traffic flow with safe driving conditions

In this paper, a recently introduced cellular automata （CA） model is used for a statistical analysis of the inner micro-scopic structure of synchronized traffic flow. The analysis focuses on the formation and dissolution of clusters or platoons of vehicles, as the mechanism that causes the presence of this synchronized traffic state with a high flow. This platoon formation is one of the most interesting phenomena observed in traffic flows and plays an important role both in manual and automated highway systems （AHS）. Simulation results, obtained from a single-lane system under periodic boundary conditions indicate that in the density region where the synchronized state is observed, most vehicles travel together in pla- toons with approximately the same speed and small spatial distances. The examination of velocity variations and individual vehicle gaps shows that the flow corresponding to the synchronized state is stable, safe and highly correlated. Moreover, results indicate that the observed platoon formation in real traffic is reproduced in simulations by the relation between vehicle headway and velocity that is embedded in the dynamics definition of the CA model.     

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.     

How we got here

This contribution summarizes and explains various principles from physics which are used for the simulation of traffic flows in large street networks, the modelling of destination, transport mode, and route choice, or the simulation of urban growth and regional development. The methods stem from many-particle physics, from kinetic gas theory, or fluid dynamics. They involve energy and entropy considerations, transfer the law of gravity, apply cellular automata and require methods from evolutionary game theory. In this way, one can determine interaction forces among driver?–?vehicle units, reproduce breakdowns of traffic including features of synchronized congested flow, or understand changing usage patterns of alternative roads. One can also describe daily activity patterns based on decision models, simulate migration streams and model urban growth as a particular kind of aggregation process.     

Stochastic Description of Traffic Flow

We propose a traffic model based on microscopic stochastic dynamics. We built a Markov chain equipped with an Arrhenius interaction law. The resulting stochastic process is comprised of both spin-flip and spin-exchange dynamics which models vehicles exiting, entering and interacting in a two-dimensional lattice environment corresponding to a multi-lane highway. The process is further equipped with a novel look-ahead type, anisotropic interaction potential which allows drivers/vehicles to ascertain local fluctuations and advance to new cells forward or sideways. The resulting vehicular traffic model is simulated via kinetic Monte Carlo and examined under both, typical and extreme traffic flow scenarios. The model is shown to correctly predict both qualitative as well as quantitative traffic observables for any highway geometry. Furthermore it also captures interesting multi-scale phenomena in traffic flows after a simulated accident which lead to oscillatory, dissipating, traffic waves with different periods per lane.     

基于元胞自动机的行人疏散流仿真研究

基于元胞自动机对行人疏散流进行仿真研究.模型利用两个动态参数反映行人移动区域内的疏散情况,从而决定行人的行为选择.模型中行人可以根据自身周围的情况选择移动、等待行为.本文仿真研究了行人在正常疏散环境下,系统规模、疏散人数、安全出口宽度、多个安全出口布局对行人疏散时间的影响.研究结果表明,行人疏散时间随行人数量呈线性增加;随安全出口宽度呈负指数性减少;同时,多个安全出口布局的不平衡也会对行人的疏散过程和疏散时间产生一定的影响. 关键词： 元胞自动机 行人疏散流 动态参数 疏散时间     

A study on the effects of the transit parking time on traffic flow based on cellular automata theory

This paper mainly deals with the effects of transit stops on vehicle speeds and conversion lane numbers in a mixed traffic lane.Based on thorough research of traffic flow and cellular automata theory,it calibrates the cellular length and the running speed.Also,a cellular automata model for mixed traffic flow on a two-lane system under a periodic boundary condition is presented herewith,which also takes into consideration the harbour-shaped transit stop as well.By means of computer simulation,the article also studies the effects of bus parking time on the traffic volume,the transit speed and the fast lane speed at the same time.The results demonstrate that,with the increase of the bus parking time,the traffic volume of the transit stop and the transit speed decrease while the fast lane speed increases.This result could help calculate the transit delay correctly and make arrangements for transit routes reasonably and scientifically.     

多路段元胞自动机交通流模型

在经典单路段元胞自动机交通流模型的基础上,将多个路段视为一个道路系统,提出并研究了多路段条件下的交通流问题.针对多路段道路的特点,通过引入车辆流入规则、路口随机慢化规则和路口车辆流入规则,控制车辆从上一路段流入下一路段.首先提出了"汽车池"的概念,来控制每一路口车辆的流入;然后通过路口随机慢化,来模拟路口对交通的影响;最后,当车辆离开时,依直行率进入下一路段,实现车流的继续流动.同时,通过数值模拟,仿真了不同条件下的交通情况,对重要参数进行了研究.结果表明,出现了混合流这一新的现象,拥堵地段与非拥堵地段间存在明显的界限.拥堵往往最先从路口开始,然后蔓延到整个路段.多路段道路还存在临界突变的特性.随着车辆流入概率的增大,路口对平均速度和车流密度的影响愈加明显.当流入概率超过一定阈值时,车辆缓慢地增加也会引起整体道路通行能力的迅速下降.     

开放边界条件下二维可转向主干道交通流模型的研究

在开放性边界条件下，利用改进的Nagel-Schreckenberg交通流模型，引入过路口车辆的可 转向机理，建立二维n速主干道元胞自动机交通流模型，研究了转向概率和边界条件对 干道交通状况的影响而导致的不同相变特性以及这两个因素对实现改善干道交通的组织作用 . 关键词： 元胞自动机 交通流 转向概率 相变