The effect of ACC vehicles to mixed traffic flow consisting of manual and ACC vehicles

This paper studies the effect of adaptive cruise control （ACC） system on traffic flow by using simulations. The multiple headway and velocity difference （MHVD） model is used to depict the motion of ACC vehicles, and the simulation results are compared with the optimal velocity （OV） model which is used to depict the motion of manual vehicles. Compared the cases between the manual and the ACC vehicle flow, the fundamental diagram can be classified into four regions： I, II, III, IV. In low and high density the flux of the two models is the same; in region II the free flow region of the MHVD model is enlarged, and the flux of the MHVD model is larger than that of the OV model; in region III serious jams occur in the OV model while the ACC system suppresses the jams in the MHVD model and the traffic flow is in order, but the flux of the OV model is larger than that of the MHVD model. Similar phenomena also appeared in mixed traffic flow which consists of manual and ACC vehicles. The results indicate that ACC vehicles have significant effect on traffic flow. The improvement induced by ACC vehicles decreases with the increasing proportion of ACC vehicles.     

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.     

考虑自适应巡航车辆影响的上匝道系统混合交通流模型

在考虑自适应巡航(adaptive cruise control, ACC)车辆的交通流模型的基础上, 建立了考虑ACC车辆影响的上匝道系统混合交通流模型, 研究ACC车辆引入对上匝道交通系统交通流的影响. 为了描述ACC车辆和手动驾驶车辆在交通流运行中的差异, 分别构建了基于常车头时距原则的ACC 车辆跟驰子模型和手动驾驶车辆MCD元胞自动机子模型; 基于上匝道车辆合流驶入主线的需求, 建立了换道子模型, 引入了表征驾驶员换道心理的参数λ. 通过对混合交通流模型进行数值模拟发现, ACC车辆的混入可以有效改善上匝道系统交通流的运行, 降低合流等事件对于交通流运行的影响, 抑制交通拥堵的时空范围及拥堵强度, 提高交通流的平均速度和流量. 此外在混合交通流模型中, ACC车辆期望车头时距H_d的减小与换道心理参数λ 的增大均可以提高混合交通流运行的速度和流量, 而合流区长度l_w对混合交通流影响则因上匝道车辆驶入概率的不同而存在差异.     

Characteristics of synchronized traffic in mixed traffic flow

In this paper, the characteristics of synchronized traffic in mixed traffic flow are investigated based on the braking light model. By introducing the energy dissipation and the distribution of slowdown vehicles, the effects of the maximum velocity, the mixing ratio, and the length of vehicles on the synchronized flow are discussed. It is found that the maximum velocity plays a great role in the synchronized flow in mixed traffic. The energy dissipation and the distribution of slowdown vehicles in the synchronized flow region are greatly different from those in free flow and a traffic jamming region. When all of vehicles have the same maximum velocity with V max > 15, the mixed traffic significantly displays synchronized flow, which has been demonstrated by the relation between flow rate and occupancy and estimation of the cross-correlation function. Moreover, the energy dissipation in the synchronized flow region does not increase with occupancy. The distribution of slowdown vehicles shows a changeless platform in the synchronized flow region. This is an interesting phenomenon. It helps to deeply understand the synchronized flow and greatly reduce the energy dissipation of traffic flow.     

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.     

混入智能车的下匝道瓶颈路段交通流建模与仿真分析

以下匝道瓶颈路段为研究背景,以手动驾驶汽车和两类智能车为研究对象,包括自适应巡航(ACC)汽车和协同自适应巡航(CACC)汽车,建立了混入智能车的混合交通流模型.在车辆的纵向控制层面,分别构建了手动驾驶汽车改进舒适驾驶元胞自动机规则和智能车的跟驰模型;基于车辆下匝道行驶特性,引入车辆感知范围R、换道控制区域LLC、换道冒险因子λ等参数,建立了控制车辆横向运动的自由换道和强制换道模型.通过对混合交通流模型进行数值仿真发现,CACC车辆混入率PCACC、车辆感知范围R、换道区域长度LLC和换道冒险程度λ均对下匝道交通系统产生影响.当CACC车辆混入率低于0.5时,CACC退化为ACC的概率增大,系统稳定性下降,交通拥堵呈恶化趋势;当CACC车辆混入率大于0.5时,车辆运行速度显著提升,拥堵消散能力提高.增大车辆感知范围、加长换道区域长度、提高换道冒险程度,都能够有效缓解改善下匝道瓶颈路段主线的拥挤状况,而对匝道运行效率影响并不明显.     

Traffic flow on a toll highway with electronic and traditional tollgates

We study the traffic states and jams occurring in traffic flow on a two-lane toll highway with electronic and manual (traditional) tollgates. The electronic and manual collection vehicles sort themselves into their respective lanes at low density, while they mix at each tollgate at high density. We derive the fundamental diagrams (flow-density diagrams) for the electronic and manual collection vehicles. The traffic states change with increasing density and varying the ratio. Dynamical phase transitions occur. It is shown that the fundamental diagrams for the two tollgates depend greatly on the density and fraction of both vehicles.     

Navier-Stokes-like equations applicable to adaptive cruise control traffic flows

Under the scenario in which, within a traffic flow, each vehicle is controlled by adaptive cruise control (ACC), and the macroscopic one-vehicle probability distribution function fits the Paveri-Fontana hypothesis, a set of reduced Paveri-Fontana equations considering the ACC effect is derived. With the set, by maximizing the specially defined informational entropy deviating from a certain reference homogeneous steady state, the Navier-Stokes-like equations considering ACC are introduced. For a homogeneous steady traffic flow in a single circular lane, when the steady velocity or density is perturbed along the lane, numerical simulations indicate that ACC-controlled vehicles require less time for re-equilibration than manually driven vehicles. The re-equilibrated steady densities for ACC and manually driven traffic flows are all close to the original values; the same is true for the re-equilibrated steady velocity for manually driven traffic flows. For ACC traffic flows, the re-equilibrated steady velocity may be higher or lower than the original value, depending upon a parameter ω (introduced to solve the distribution function of the reference steady state), and the headway time (introduced in ACC models). Also, the simulations indicate that only an appropriate parameter set can ensure the performance of ACC; otherwise, ACC may result in low traffic running efficiency, although traffic flow stability becomes better.     

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.     

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.     

混有协同自适应巡航控制车辆的异质交通流稳定性解析与基本图模型

针对传统车辆和协同自适应巡航控制(cooperative adaptive cruise control,CACC)车辆构成的异质交通流,研究其稳定性与基本图模型.应用实车测试验证的CACC模型和智能驾驶员模型(intelligent driver model)分别作为CACC车辆和传统车辆的跟驰模型,建立异质流稳定性解析框架,研究不同平衡态速度、不同CACC车辆比例时的异质流稳定性.推导异质流基本图模型,并进行数值仿真实验.研究结果表明,在传统车辆稳定的速度范围,异质流处于稳定状态.在传统车辆不稳定的速度范围,CACC车辆比例增加以及平衡态速度远离9.6—18.6 m/s速度范围,均能够改善异质流的不稳定性.通行能力随着CACC车辆比例的增加而提高.此外,CACC模型的期望车间时距越大,异质流稳定域越大,但通行能力降低.因此,恒定车间时距CACC控制策略下的期望车间时距取值应权衡异质流稳定域和通行能力两个方面的影响.     

Discontinuous transition from free flow to synchronized flow induced by short-range interaction between vehicles in a three-phase traffic flow model

In this paper, we incorporate a limitation on the interaction range between neighboring vehicles into the cellular automaton model proposed by Gao and Jiang et al. [K. Gao, R. Jiang, S. X. Hu, B. H. Wang and Q. S. Wu, Phys. Rev. E 76 (2007) 026105], which was established within the framework of Kerner’s three-phase traffic theory and has been shown to be able to reproduce the three-phase traffic flow. This modification eliminates an unrealistic phenomenon found in the previous model, where the velocity-adaptation effect between neighboring vehicles can exist even if those vehicles are infinitely far away from each other. Therefore, in the improved model, we regulate that such interactions can only occur within a finite distance. For simplicity, we suppose a constant value to describe this distance in this paper. As a result, when compared to the previous model, the improved model mainly simulates the following results which are believed to be an improvement. (1) The improved model successfully reproduces the expected discontinuous transition from free flow to synchronized flow and the related “moving synchronized flow pattern”, which are both absent in the original model but have been observed in real traffic. (2) The improved model simulates the correlation functions, time headway distributions and optimal velocity functions which are all more consistent with the empirical data than the previous model and most of the other models published before. (3) Together with the previous two models considering the velocity-difference effect, this model finally accomplishes a significative process of developing traffic flow models from the traditional “fundamental diagram approach” to the three-phase traffic theory. This process should be helpful for us to understand the traffic dynamics and mechanics further and deeper.     

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.     

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.     

Phase diagram of speed gradient model with an on-ramp

In this paper, phase transitions are investigated in speed gradient model with an on-ramp. Phase diagrams of traffic flow composed of manually driven vehicles and adaptive cruise control (ACC) vehicles are studied, respectively. The traffic flow composed of ACC vehicles is modeled by enhancing propagation speed of small disturbance. The phase diagram of traffic flow composed of manually driven vehicles is similar to that in previous works, in which such states as pinned localized cluster (PLC), moving localized cluster (MLC), triggered stop-and-go traffic (TSG), oscillatory congested traffic (OCT), and homogeneous congested traffic (HCT) are reproduced. In the phase diagram of traffic flow composed of ACC vehicles, traffic stability is enhanced and such states as PLC, MLC, and TSG disappear. Furthermore, some interesting phenomena, such as stationary OCT upstream of on-ramp and appearance of second OCT in HCT, are identified.     

Analysis of the influence of occupation rate of public transit vehicles on mixing traffic flow in a two-lane system

Based on the existing classical cellular automaton model of traffic flow, a cellular automaton traffic model with different-maximum-speed vehicles mixed on a single lane is proposed, in which public transit and harbour-shaped bus stops are taken into consideration. Parameters such as length of cellular automaton, operation speed and random slow mechanism are re-demarcated. A harbour-shaped bus stop is set up and the vehicle changing lane regulation is changed. Through computer simulation, the influence of occupation rate of public transit vehicles on mixed traffic flow and traffic capacity is analysed. The results show that a public transport system can ease urban traffic congestion but creates new jams at the same time, and that the influence of occupation rate of public transit vehicles on traffic capacity is considerable. To develop urban traffic, attention should be paid to the occupation rate of public transit vehicles and traffic development in a haphazard way should be strictly avoided.     

Abnormal hysteresis effect and phase transitions in a velocity-difference dependent randomization CA model

Additional to the basic Nagel-Schreckenberg model for single-lane traffic flow, we consider the effect of the velocity-difference between two successive vehicles on the randomization of the latter one. This modification improves the transit capacity of the model, which results in a much higher simulated flux. Moreover, in a circular road, this model simulates an abnormal hysteresis effect. The characteristic shape of hysteresis curves may shed some light on the distinguish of synchronized flow and jams.     

Synchronized flow and phase separations in single-lane mixed traffic flow

In this paper, we have studied synchronized flow and phase separations in mixed (heterogeneous) single-lane highway traffic. It is found that the flux–density (occupancy) curve of heterogeneous flow, as expected, lies in between two flux–density (occupancy) curves of homogeneous flow R=0$R=0$ (all vehicles are slow vehicles) and R=1$R=1$ (all vehicles are fast vehicles). However, unexpectedly, the velocity–density (occupancy) curve of heterogeneous flow does not. We also found that cross-correlation function (CCF) analysis shows that heterogeneous flow has almost the same strong coupling as homogeneous flow. In other words, when traffic is in free flow or jams, the value of CCF is approximate to be 1.0, while the value is about 0.1 in synchronized flow.     

Characteristics of mixed traffic flow with non-motorized vehicles and motorized vehicles at an unsignalized intersection

In this paper, a new two-dimensional car-following model is proposed to depict the features of mixed traffic flow consisting of motorized vehicles (m-vehicle) and non-motorized vehicles (nm-vehicle), based on the two-dimensional optimal velocity (OV) model by Nakayama et al. [A. Nakayama, K. Hasebe, Y. Sugiyama, Phys. Rev. E 71 (2005) 036121]. In the proposed model, velocity difference terms are introduced, which are regarded as important factors for traffic behavior. Numerical simulations are carried out to investigate the interaction between left-turning nm-vehicle flow and straight-going m-vehicle flow at a typical unsignalized interaction. The results show that the straight-going m-vehicle flow just next to nm-lane is disturbed more seriously than others. In addition, a well-known phenomenon in reality is observed that groups of m-vehicles and nm-vehicles pass through the intersection alternately.     

Fundamental diagram in traffic flow of mixed vehicles on multi-lane highway

We study the fundamental diagram for traffic flow of vehicular mixture on a multi-lane highway. We present the car-following model of multi-lane traffic in which slow and fast vehicles flow with changing lanes. We investigate the traffic states of the vehicular mixture under the periodic boundary. Two values of the current appear at a density and two current curves are obtained. Vehicles move with changing lanes in the traffic state of high current, while vehicles move without changing lanes in the traffic state of low current. They depend on the density, the fraction of slow vehicles, and the initial condition. In the high-current curve, the jamming transition between the free flow and the jammed state occurs at a low density. The fundamental diagrams (current-density diagrams) are shown for the single-lane, two-lane, three-lane, and four-lane traffics.