The “backward looking” effect in the lattice hydrodynamic model

The novel lattice hydrodynamic model is presented by incorporating the “backward looking” effect. The stability condition for the the model is obtained using the linear stability theory. The result shows that considering one following site in vehicle motion leads to the stabilization of the system compared with the original lattice hydrodynamic model and the cooperative driving lattice hydrodynamic model. The Korteweg-de Vries (KdV, for short) equation near the neutral stability line is derived by using the reductive perturbation method to show the traffic jam which is proved to be described by KdV soliton solution obtained from the KdV equation. The simulation result is consistent with the nonlinear analysis.     

Modified coupled map car-following model and its delayed feedback control scheme

A modified coupled map car-following model is proposed, in which two successive vehicle headways in front of the considering vehicle is incorporated into the optimal velocity function. The steady state under certain conditions is obtained. An error system around the steady state is studied further. Moreover, the condition for the state having no traffic jam is derived. A new control scheme is presented to suppress the traffic jam in the modified coupled map car-following model under the open boundary. A control signal including the velocity differences between the following and the considering vehicles, and between the preceding and the considering vehicles is used. The condition under which the traffic jam can be well suppressed is analysed. The results are compared with that presented by Konishi et al. (the KKH model). The simulation results show that the temporal behaviour obtained in our model is better than that in the KKH model. The simulation results are in good agreement with the theoretical analysis.     

The Korteweg-de Vries soliton in the lattice hydrodynamic model

The lattice hydrodynamic model is not only a simplified version of the macroscopic hydrodynamic model, but is also closely connected with the microscopic car following model. The modified Korteweg-de Vries (mKdV) equation about the density wave in congested traffic has been derived near the critical point since Nagatani first proposed it. But the Korteweg-de Vries (KdV) equation near the neutral stability line has not been studied, which has been investigated in detail in the car following model. So we devote ourselves to obtaining the KdV equation from the lattice hydrodynamic model and obtaining the KdV soliton solution describing the traffic jam. Numerical simulation is conducted, to demonstrate the nonlinear analysis result.     

优化车流的交通流格子模型

在一维交通流格子模型的基础上，分别提出考虑最近邻车和次近邻车以及考虑前、后近邻车相互作用进行车流优化的一维交通流格子模型.应用线性稳定性理论和非线性理论进行分析，得出车流的稳定性条件，并导出了描述交通阻塞相变的mKdV方程.用数值模拟验证了mKdV方程的解，数值模拟结果表明考虑最近邻车和次近邻车的优化车流能够增强车流稳定性，而考虑前、后近邻车的优化车流将使稳定性减小. 关键词： 交通流 交通相变 稳定判据 mKdV方程     

Analysis of car-following model considering driver’s physical delay in sensing headway

An extended car-following model is proposed by taking into account the delay of the driver’s response in sensing headway. The stability condition of this model is obtained by using the linear stability theory. The results show that the stability region decreases when the driver’s physical delay in sensing headway increases. The KdV equation and mKdV equation near the neutral stability line and the critical point are respectively derived by applying the reductive perturbation method. The traffic jams could be thus described by soliton solution and kink-antikink soliton solution for the KdV equation and mKdV equation respectively. The numerical results in the form of the space-time evolution of headway show that the stabilization effect is weakened when the driver’s physical delay increases. It confirms the fact that the delay of driver’s response in sensing headway plays an important role in jamming transition, and the numerical results are in good agreement with the theoretical analysis.     

A new car-following model with consideration of the traffic interruption probability

In this paper, we present a new car-following model by taking into account the effects of the traffic interruption probability on the car-following behaviour of the following vehicle. The stability condition of the model is obtained by using the linear stability theory. The modified Korteweg--de Vries (KdV) equation is constructed and solved, and three types of traffic flows in the headway sensitivity space---stable, metastable, and unstable---are classified. Both the analytical and simulation results show that the traffic interruption probability indeed has an influence on driving behaviour, and the consideration of traffic interruption probability in the car-following model could stabilize traffic flow.     

驾驶员预估效应下车流能耗演化机理研究

考虑实际交通中驾驶员预估效应对车辆跟驰行为的影响, 提出了一个改进跟驰模型. 采用线性稳定性理论获得了该模型的线性稳定性判据. 运用数值仿真的方法, 系统研究了驾驶员预估效应下车流的整体平均能耗和单车能耗的演化机理. 研究结果表明, 驾驶员预估效应能显著提高车流稳定性, 且随着驾驶员预估时长的增加, 车流的整体平均能量损耗和单车能量损耗将逐渐降低.     

Multiple car-following model of traffic flow and numerical simulation

On the basis of the full velocity difference (FVD) model, an improved multiple car-following (MCF) model is proposed by taking into account multiple information inputs from preceding vehicles. The linear stability condition of the model is obtained by using the linear stability theory. Through nonlinear analysis, a modified Korteweg-de Vries equation is constructed and solved. The traffic jam can thus be described by the kink--antikink soliton solution for the mKdV equation. The improvement of this new model over the previous ones lies in the fact that it not only theoretically retains many strong points of the previous ones, but also performs more realistically than others in the dynamical evolution of congestion. Furthermore, numerical simulation of traffic dynamics shows that the proposed model can avoid the disadvantage of negative velocity that occurs at small sensitivity coefficients λ in the FVD model by adjusting the information on the multiple leading vehicles. No collision occurs and no unrealistic deceleration appears in the improved model.     

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.     

Two velocity difference model for a car following theory

In the light of the optimal velocity model, a two velocity difference model for a car-following theory is put forward considering navigation in modern traffic. To our knowledge, the model is an improvement over the previous ones theoretically, because it considers more aspects in the car-following process than others. Then we investigate the property of the model using linear and nonlinear analyses. The Korteweg-de Vries equation (for short, the KdV equation) near the neutral stability line and the modified Korteweg-de Vries equation (for short, the mKdV equation) around the critical point are derived by applying the reductive perturbation method. The traffic jam could be thus described by the KdV soliton and the kink-anti-kink soliton for the KdV equation and mKdV equation, respectively. Numerical simulations are made to verify the model, and good results are obtained with the new model.     

基于智能交通系统的耦合映射跟驰模型和交通拥堵控制

基于智能交通诱导信息，提出一种改进的耦合映射跟驰模型，用于描述单车道的交通流动力学特性及其拥堵控制.利用反馈控制理论，给出了在头车速度发生变化时交通流保持稳定的条件.分析结果表明，考虑前方更多车辆的信息对交通流有致稳作用，亦即稳定性条件明显减弱.数值模拟证实了理论分析的正确性，通过与他人相关工作的比较得知，考虑智能交通诱导信息能够更有效地抑制交通拥堵. 关键词： 交通流 智能交通系统 耦合映射跟驰模型 交通拥堵控制     

道路交通的流体物理模型与粒子仿真方法

针对受多种因素影响的复杂道路交通系统问题,基于颗粒动力学理论,结合传统的Lighthill-WhithamRichards物理模型,建立道路交通系统的流体物理模型,采用无网格粒子与网格相结合的方法进行数值仿真,并应用于典型道路交通问题的求解.在新模型中,将车辆比拟为硬颗粒,车辆的跟车比拟为颗粒间的碰撞相互作用,已知道路情况对驾驶员操作车辆的影响比拟为流-粒两相系统中的外部流体驱动力作用,不同车道间车辆的影响比拟为颗粒间的黏性作用,从而在颗粒动力学理论的基础上,推导建立了道路交通系统拟流体模型;引入光滑离散颗粒流体动力学(SDPH)对车辆系统模型进行离散,建立"SDPH车辆"与真实车辆之间的一一对应关系,再结合有限体积方法,对道路交通构建的双流体模型进行求解,建立求解交通流体物理模型的新型仿真方法.最后,采用所建立的模型和方法对车辆汇入以及机非混合对交通系统的影响过程进行了数值仿真,所得结果与实测值符合较好,表明新的模型和方法有效性好、可靠性高,为道路交通问题的解决提供了一条全新的途径.     

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.     

Stabilisation analysis of multiple car-following model in traffic flow

An improved multiple car-following model is proposed by considering the arbitrary number of preceding cars, which includes both the headway and the velocity difference of multiple preceding cars. The stability condition of the extended model is obtained by using the linear stability theory. The modified Korteweg--de Vries equation is derived to describe the traffic behaviour near the critical point by applying the nonlinear analysis. Traffic flow can be also divided into three regions: stable, metastable and unstable regions. Numerical simulation is accordance with the analytical result for the model. And numerical simulation shows that the stabilisation of traffic is increasing by considering the information of more leading cars and there is unavoidable effect on traffic flow from the multiple leading cars' information.     

A new macro model with consideration of the traffic interruption probability

In this paper, we present a new macro model which involves the effects that the probability of traffic interruption has on the car-following behavior through formulating the inner relationship between micro and macro variables. Linear stability analysis shows that consideration of the traffic interruption probability can improve the stability of traffic flow if and only if the drivers’ reactive time required for adjusting their acceleration based on the traffic interruption probability p is not greater than that one based on the non-interruption probability 1−p. Numerical results verify that the new model can be used to analyze the effects of traffic interruption probability and traffic interruption on shock, rarefaction wave, small perturbation and uniform flow. The model has been applied in reproducing some complex traffic phenomena resulted by some traffic interruptions (e.g., signal light, pedestrian and tolling station).     

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.     

考虑车与车互联通讯技术的交通流跟驰模型

基于Newell跟驰模型,建立考虑车与车互联(vehicle-to-vehicle,V2V)通讯技术的单车道跟驰模型.根据V2V技术的特征,引入参数α以表征驾驶员在收到V2V技术所提供的实时交通信息后的提前反应程度.根据线性稳定分析方法,得到V2V跟驰模型的中性稳定条件.通过计算机的模拟,研究V2V技术对交通流运行的影响,分析小扰动下V2V跟驰模型对参数变化的敏感性,研究不同α取值下交通流密度波及迟滞回环的变化.研究发现:1)与全速度差跟驰模型相比,在引入V2V后,交通流在加速起步、减速刹车及遇到突发事件时,车辆运行的安全性和舒适性均得到不同程度的提升;2)V2V跟驰模型对参数α及T的变化较为敏感,且在交通流较为拥堵时,V2V技术的引入可以提升交通流的平均速度;3)参数α的增大、T的减小可以有效提升V2V跟驰模型在不同交通环境下的运行稳定性.由于可以实时地获取交通流运行的状态并针对性地改变车辆自身的运行,V2V交通流跟驰模型提升了交通流运行的稳定性.     

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.     

A study of wide moving jams in a new lattice model of traffic flow with the consideration of the driver anticipation effect and numerical simulation

In this paper, a new lattice model of traffic flow is proposed to investigate wide moving jams in traffic flow with the consideration of the driver anticipation information about two preceding sites. The linear stability condition is obtained by using linear stability analysis. The mKdV equation is derived through nonlinear analysis, which can be conceivably taken as an approximation to a wide moving jam. Numerical simulation also confirms that the congested traffic patterns about wide moving jam propagation in accordance with empirical results can be suppressed efficiently by taking the driver anticipation effect of two preceding sites into account in a new lattice 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.