Study of macroscopic fundamental diagram on Shanghai urban expressway network in China

The macroscopic fundamental diagram（ MFD） is studied to obtain the aggregate behavior of traffic in cities. This paper investigates the existence and the characteristics of different types of daily MFD for the Shanghai urban expressway network. The existence of MFD in the Shanghai urban expressway network is proved based on two weeks＇ data.Moreover, the hysteresis phenomena is present in most days and the network exhibits different hysteresis loops under different traffic situations. The relationship between the hysteresis phenomena and the inhomogeneity of traffic distribution is verified. The MFDs in the years of 2009 and 2012 are compared. The hysteresis loop still exists in 2012, which further verifies the existence of the hysteresis phenomenon. The direct relationship between the length of the hysteresis loop（ ΔO） and the congestion is proved based on sufficient data. The width of the hysteresis loop, i. e., the drop in network flow（ ΔQ） has no relationship with the congestion, and it varies from day to day under different traffic situations.

Perimeter traffic control strategy based on macroscopic fundamental diagrams

A perimeter traffic signal control strategy is proposed based on the macroscopic fundamental diagram theory(MFD)to solve the signal control problem in oversaturated states.First,the MFD of a specific regional network can be derived using VSS IM simulation software.Secondly,the maximum number of cumulative vehicles that the network can accommodate is determined based on the MFD.Then,through monitoring the influx flow,the number of vehicles existing in and exiting from the network,a perimeter traffic control model is proposed to optimize the signal timing of the boundary intersections.Finally,a virtual network simulation model is established and three different kinds o f traffic demand are loaded into the network.Simulation results show that a fer the strategy implementation,the number o f vehicles accumulating in the network can be kept near the optimal value,while the number o f both entering and exiting vehicles increases significantly and the road network can be maintained at a large capacity.Simultaneously,the queue length at the approach of the border intersections is reasonably controlled and vehicles entering and exiting the network can maintain a more efficient and stable speed.The network performance indices such as the average traffic delay and average number of stops can be improved to a certain degree,thus verifying the effectiveness and feasibility of the perimeter control strategy.

Vehicle emissions calculation for urban roads based on the Macroscopic Fundamental Diagram method and real-time traffic information

Vehicle emissions calculation methods mostly use ownership information or annual road monitoring data as the activity level to calculate air pollutant emissions,but it is hard to reflect either the emissions intensity under different conditions or the spatiotemporal characteristics in various sections based on such approaches.This paper presents a method based on the Macroscopic Fundamental Diagram and real-time traffic data to calculate vehicle emissions,which could reflect the operation conditions and emission characteristics of vehicles.Following the‘Technical Guide for the Compiling of Road Vehicle Air Pollutant Emissions Inventories’,the emissions of three roads with different lane numbers and road grades in Beijing were estimated and verified using this method.Compared with monitoring data,the average deviations of the traffic flow on the Fifth Expressway,Jingfu National Highway,and Jingzhou Provincial Highway were?25.5%,?26.5%,and?13.4%,respectively,and the average deviations of nitrogen oxides emissions were?27.7%,?12.9%,and?12%,respectively.This method showed good application potentials to construct the emissions inventory applied to the block-scale model and analyze the spatiotemporal distribution characteristics of motor vehicle emissions in urban areas.

Quantification of the Hysteresis of Macroscopic Fundamental Diagrams and Its Relationship with the Congestion Heterogeneity and Performance of a Multimodal Network

Recent studies have observed hysteresis loops in the macroscopic fundamental diagram (MFD). In particular, for the same network density, higher network flows occur during congestion onset than during congestion offset. To evaluate management strategies using the MFD, investigating the relationship between the size of these loops and network performance is needed. The existing literature has mainly discussed correlating loop width (difference in density) and height (capacity drop) with congestion heterogeneity, but has failed to prove a relationship between the capacity drop and traffic conditions. Moreover, quantification of the MFD loop in complex multimodal networks has not been investigated. The objective of this paper covers these aspects. We simulated the Sioux Falls network with different mode-share ratios (car and bus users) based on a multi-agent simulation, MATSim. We investigated the relationships between MFD loop size and congestion heterogeneity (standard deviation of density) and network performance (average passenger travel time), and found that both were directly correlated with loop width, while weakly correlated with loop height. Moreover, we divided the MFD loop into two parts according to congestion onset and offset periods and found that the heights of the two parts had opposite effects. Accordingly, we show why the relationship between capacity drop and congestion heterogeneity is not found in the literature. We also found that network performance inversely affected the height of part of the loop while the height of its other part increased with an increase in congestion heterogeneity. These results help to evaluate network performance in the presence of MFD hysteresis, leading to elaborated management decisions.

不同降雨量下基于宏观基本图的边界控制策略

在雨雪等不利天气条件下,城市交通拥堵加剧,北京、天津等大城市在降雨条件下经常发生多路段区域性交通拥堵。因此,根据天津市中心城区和市郊区域路网实际交通数据,以路网交通流宏观基本图模型为研究基础,对比不同降雨量以及不同路网的路网交通流时序和宏观基本图变化规律,分析不同降雨量对天津市中心城区和市郊区域路网交通状态的影响。基于不同降雨量下中心城区和市郊区域路网宏观交通流的变化规律,分别构建路网动态演化模型,并对模型的参数进行标定和有效性验证。针对降雨条件下路网发生的区域性拥堵问题,基于宏观基本图的边界控制分别设计了不同降雨量下中心城区和市郊区域路网控制策略,通过仿真实验分析验证了不同控制策略的效果,并给出了能够缓解中心城区和市郊区域路网拥堵的可行策略。结果表明:在小雨天气条件下,将从市郊区域向中心城区的交通流量的转移比例减小量控制在9%~50%范围之内时,中心城区与市郊区域交通状态更加均衡,路网调控效果更好;在大雨天气条件下,将从市郊区域向中心城区的交通流量的转移比例减小量控制在23%~50%范围之内时,中心城区与市郊区域交通状态更加均衡,路网调控效果更好。这表明该控制策略能够缓解中心城区和市郊区域路网的交通拥堵,保障路网交通系统的稳定运行。

考虑宏观碳排放阈值的快速路入口匝道控制

为缓解日益严重的快速路交通拥堵及交通污染问题,在经典ALINEA匝道控制算法基础上考虑碳排放的影响,通过宏观基本图将实时碳排放测度指标与占有率指标相结合提出宏观碳排放阈值指标,构建兼顾主线与匝道碳减排以及路网运行效率提升的CE-ALINEA(carbonemission-ALINEA)分级控制算法,并通过VISSIM仿真实验比较不同控制算法的控制效果.结果表明:相比ALINEA控制,CE-ALINEA控制不仅能有效减少主线排放量并提升主线运行效率,还能明显减少因匝道控制而增加的匝道碳排放;CE-ALINEA控制在改变检测器布设下能有效测度主线碳排放并对主线交通具有稳定的控制效果;随着电动汽车渗透率增加,CE-ALINEA减排效果有所减弱,但与ALINEA相比对匝道碳排放仍有较好的减排效果.

考虑干扰的交通子区模糊迭代学习边界控制

针对固定增益迭代学习控制器跟踪交通子区内期望累计车辆数n^(*)的速度较慢,迭代次数过多的问题,并考虑到实际交通子区内存在的干扰对其运行状态的影响,建立了含有干扰项的交通流模型并对其进行离散化。采用开闭环比例微分(proportion differentiation,PD)型模糊迭代学习控制器,根据研究子区实际路网内的累计车辆数与期望累计车辆数n^(*)的误差及其变化率对开闭环PD型迭代学习控制器的迭代学习增益和反馈增益进行调整,使交通子区内的实际累计车辆数可以较快速地跟踪期望累计车辆数n^(*),并对开闭环PD型模糊迭代学习控制器的收敛性进行严格证明。通过对轻度和中度干扰影响下的交通子区进行仿真,结果显示,对比固定增益迭代学习控制器,开闭环PD型模糊迭代学习控制器的误差收敛速度分别提高24%和31%,平均排队长度分别减少24.52%和16.55%,平均延误分别减少21.63%和19.23%,平均停车次数分别减少23.68%和10.77%。

基于三维宏观基本图的城市机非混行交通研究

为解决城市交通中机动车与非机动车混合行驶造成的交通拥堵,提出一种三维宏观基本图的理论分析方法,探究机动车与非机动车混行交通流的微观运行特征和宏观演化规律,揭示在非机动车干扰下交通拥堵的形成、传播和消散机理。先分别建立描述非机动车流的元胞自动机模型和机动车流的元胞传输模型,并借助非机动车越线次数函数将两个模型耦合;然后,在Simulink仿真平台上,运行该耦合模型以求得路网的三维宏观基本图,并以此分析非机动车驶入流量与路网平均流量、冲突次数三者间的相互关系;最后,提出提高路网硬隔离占比和加大非机动车道宽度的两种方法,借助三维宏观基本图来验证其缓解交通拥堵的效果。研究结果表明:三维宏观基本图的分析方法可量化机动车和非机动车冲突的影响,指导混行交通拥堵的治理,该结论为改善中国城市交通出行秩序和出行环境提供了参考。

基于PID控制的交通边界控制方法

随着城市化进程的不断加速,交通拥堵已成为城市面临的主要挑战之一。为了解决城市路网中心区域因车辆累积而导致的拥堵问题,本文利用宏观基本图的特有属性,提出了基于PID控制的交通边界控制方法。首先,建立被控区域车辆动态平衡方程,确定被控区域与外部区域车辆转移关系;其次,引入PID控制器作为路网边界控制器,通过调节进入被控区域的车辆转移比率,控制进入被控区域内部的车辆数;最后,利用VISSIM仿真软件的仿真结果表明:路网内部的车辆总数能够稳定在最佳累积值附近。

An identification model of urban critical links with macroscopic fundamental diagram theory

How to identify the critical links of the urban road network for actual traffic management and intelligent trans- portation control is an urgent problem, especially in the con- gestion environment. Most previous methods focus on traf- fic static characteristics for traffic planning and design. How- ever, actual traffic management and intelligent control need to identify relevant sections by dynamic traffic information for solving the problems of variable transportation system. Therefore, a city-wide traffic model that consists of three re- lational algorithms, is proposed to identify significant links of the road network by using macroscopic fundamental diagram （MFD） as traffic dynamic characteristics. Firstly, weighted- traffic flow and density extraction algorithm is provided with simulation modeling and regression analysis methods, based on MFD theory. Secondly, critical links identification algo- rithm is designed on the first algorithm, under specified prin- ciples. Finally, threshold algorithm is developed by cluster analysis. In addition, the algorithms are analyzed and applied in the simulation experiment of the road network of the cen- tral district in Hefei city, China. The results show that the model has good maneuverability and improves the shortcom- ings of the threshold judged by human. It provides an ap- proach to identify critical links for actual traffic management and intelligent control, and also gives a new method for eval- uating the planning and design effect of the urban road net- work.

改进狼群算法的交通子区迭代学习边界控制方法

针对基于固定增益迭代学习的交通子区边界控制方法收敛速度慢、迭代次数过多及控制精度差的问题。提出了一种迭代学习结合改进狼群算法的交通子区边界控制方案。该方案首先根据宏观基本图理论建立交通子区路网的车辆平衡方程,设计出系统的迭代学习控制律。其次分析了迭代学习控制对宏观基本图的影响,引入自适应步长的狼群算法,该算法以上一批次的宏观基本图为模型,离线对迭代学习控制器的比例和微分增益系数进行寻优,再将最优结果代入下一控制周期迭代学习控制中,进而改善收敛速度与精度。最后,对该方案的收敛性提供了数学证明,而仿真实验结果也表明该算法相较于具有固定增益的迭代学习控制器,收敛速度得到提升,对系统期望轨迹也具有较好的跟踪精度,具有较强的可行性与有效性。

基于MFD的快速路新型混合交通流特性分析

为探究智能网联车辆(CAV)与人工驾驶车辆混行情况下快速路的宏观交通流特性,研究了CAV渗透率对快速路宏观基本图(MFD)的影响规律.首先,利用MFD临界点和拥堵拐点的特征属性,构建考虑CAV渗透率的MFD分段拟合模型;其次,从拥堵持续时间、拥堵严重程度和MFD迟滞现象3个方面分析CAV渗透率对快速路拥堵过程的影响;最后,采用SUMO搭建仿真环境,对提出方法进行验证.结果表明:提出的分段拟合方法在拟合优度及跟踪MFD临界点上均优于三次拟合方法;CAV的引入并不会消除快速路MFD的迟滞现象,但其持续时间会随着CAV渗透率的增加而降低;快速路拥堵严重程度随CAV渗透的增大而降低,当CAV渗透率超过0.5时,拥堵的改善效果开始减弱.

Bus frequency optimization in a large-scale multi-modal transportation system:integrating 3D-MFD and dynamic traffic assignment

A properly designed public transport system is expected to improve traffic efficiency.A high-frequency bus service would decrease the waiting time for passengers,but the interaction between buses and cars might result in more serious congestion.On the other hand,a low-frequency bus service would increase the waiting time for passengers and would not reduce the use of private cars.It is important to strike a balance between high and low frequencies in order to minimize the total delays for all road users.It is critical to formulate the impacts of bus frequency on congestion dynamics and mode choices.However,as far as the authors know,most proposed bus frequency optimization formulations are based on static demand and the Bureau of Public Roads function,and do not properly consider the congestion dynamics and their impacts on mode choices.To fill this gap,this paper proposes a bi-level optimization model.A three-dimensional Macroscopic Fundamental Diagram based modeling approach is developed to capture the bi-modal congestion dynamics.A variational inequality model for the user equilibrium in mode choices is presented and solved using a double projection algorithm.A surrogate model-based algorithm is used to solve the bi-level programming problem.

基于宏观基本图的道路交通网络边界控制方法研究

为了缓解路网中心区域因车辆不断积累而引发的大面积堵塞问题,本研究通过考虑路网的宏观基本图特有属性,提出一种拥堵状态下路网边界控制方法,以维持路网中心区域总车辆数在最佳累计值附近为目标,进而保证路网的运行效率。首先,建立车辆守恒方程,确定车辆最佳累计值的阈值,实时控制外部进入路网中心区域的车辆;其次,考虑边界控制外围路段的排队车辆累积数,为了避免排队溢出,建立控制外围排队车辆模型;最后,将路网中心区域的车辆数与外围排队车辆整合到一个模型中,共同作为边界控制的条件,使路网中的车辆总数处于一个最佳的范围内,提高控制区域整体运行效率。为了验证该方法的有效性,通过VISSIM二次开发进行仿真,实时获取路网中车辆的数据,通过计算相关参数,获取对应的绿灯时间,并且对实施边界控制与无边界控制的路网运行效果进行对比分析。仿真结果表明排队长度降低20.0%,路网内部车辆累积量降低4.1%,停车次数降低3.4%。

城市交通系统双区域边界控制的模型预测控制方法

交通系统区域控制可高效缓解交通拥堵并提高交通效率。本文考虑了城市交通系统区域累积量的平衡性和稳定性,建立了双区域边界控制模型,且采用模型预测控制方法对该模型进行控制,从而有效实现交通系统在有限时域内累积量和控制量的闭环稳定。同时,仿真模拟了交通需求量为常数和交通需求量变化情况下的交通性能,结果表明模型预测控制方法能根据实时交通需求量和累积量来调整控制状态,发现区域累积量的稳定性可使区域累积量尽量接近稳定状态,从而避免交通拥堵并提高交通效率,且控制变量的稳定性可使其尽快稳定并降低控制成本。

基于MFD的路网宏观交通状态及影响因素研究

从城市路网交通管理与控制的需求出发,引入交通流宏观基本图(MFD)模型,基于实测和仿真数据,开展对北京市西三环实际路网的宏观交通状态、时变特征以及影响因素研究.文中首先介绍了MFD模型及其矢量算法,利用实测数据建立西三环路网的MFD,基于Van Aerde模型标定路网交通流特征参数,对比分析路网平均流量-平均密度关系的时段分布差异,并得到宏观交通流的"磁滞现象";其次,证明了交通密度分布的不均衡性是影响路网宏观交通状态的根本因素;最后,利用Integration仿真研究了路网结构、交通需求以及出行路径对路网车流密度分布、宏观交通状态及其变化趋势的影响,以期为宏观交通控制、拥堵治理措施的制定提供决策支持.

北京市快速环路宏观基本图特征研究

对应于整个路网的宏观基本图反映了路网宏观变量间一种可再现的稳定的函数关系,该关系仅取决于路网属性和控制策略本身,而不依赖于具体交通需求.而作为世界上最大的城市之一,北京市的道路交通有着独一无二的特征.利用现有的高密度检测器数据,绘制了北京市快速环路的宏观基本图,在宏观上分析了北京市的交通特征;发现了北京市快速环路宏观基本图中不同于现有理论的特征,即在网络占有率方差与网络流量的对应关系中,二者亦可表现出相同的趋势,如较低占有率方差与较低网络流量间的对应关系.通过分析各环路交通拥堵的演化过程,认为北京市由中心向外扩散的放射形拥堵过程是形成这种特殊关系的内在因素.

城市交通信号的迭代学习控制及其对路网宏观基本图的影响

针对在城市交通信号控制中存在对交通流难以精确建模的问题,首先利用交通流的重复性特点,提出了一种基于迭代学习的城市交通信号控制方法,并证明了在不确定初态下迭代学习控制算法的收敛性.其次,结合路网宏观基本图的特性分析了基于迭代学习的交通信号控制策略对路网交通态势的影响.结果表明,当迭代的初始状态在期望初态值的小范围内波动时,系统的跟踪误差仍能收敛到一个界内;通过对交通信号的迭代学习控制,路段的实际占有率能够逐步逼近期望占有率,从而使路网内的车辆密度分布更加均匀,确保交通流在更优的宏观基本图下运行,防止因车辆密度分布不均引起的通行效率下降及交通拥堵的发生.最后,通过仿真实验对所提方法的有效性进行了验证.

基于宏观基本图的区域交通总量动态调控技术

城市经济的快速发展造成了诸多交通问题.在过饱和状态下,单纯的被动型信号控制所起的作用是很有限的.因此,有必要把交通控制与交通诱导相结合形成一个反馈式系统.本文提出了以基于宏观基本图及反馈门的区域总量动态调控为主、传统优化为辅的交通管理新手段,通过区域边界设置的'反馈门'控制网络流入量,将网络车辆总数维持在其合理可行范围内,以提高或维持网络流量.以北京市西二环区域为例,利用交通仿真软件对动态调控的效果进行了评估.结果证明,区域总量动态调控能够保障区域交通流的稳定、有序,提高区域交通流通行效率.

基于宏观基本图的相邻子区协调控制方法

为了提升道路网整体运行效益,克服针对单个控制子区的最优化控制可能造成的拥堵转移,本研究基于宏观基本图的概念,建立控制子区间驶入驶出交通量的协调控制模型.该模型以两个相邻控制子区为对象,考虑各子区自身宏观基本图特征及交通量流入流出关系.在运用博弈论对其相互作用进行描述的基础上,提出了一种以两个子区整体运行效益最大化为目标的博弈控制逻辑及其求解流程.通过VS2010对所建立的博弈进行仿真,验证了模型的可行性及控制效果.研究表明,不同的控制策略对相邻小区的运行水平(收益)会造成不同的影响,但经多次博弈后,两相邻控制子区整体运行状况可稳定在一个最佳水平.博弈结果显示路网容量相对较小的控制子区更应受到保护,当内部车辆数达到最佳车辆数时应对其进行流入限制.