城市交通拥堵传播机理及其控制策略研究
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摘要
交通拥堵是城市交通的常见现象并且具有传播特性，即交通拥堵会打破城市交通网络原有的交通稳态，由拥堵发生路段蔓延到交通网络中的局部区域甚至整个网络。对拥堵传播机理进行研究，目的就是为了描述拥堵传播的规律，深化城市交通流动态特性认识，并利用它进行交通拥堵的控制。
对拥堵传播机理的研究立足于宏观交通流，用时间离散化的方式，以当量车流量作为车辆在交通网络中演进的基本单位，从路段、交叉口、驾驶员、交通网络四个角度展开，具体内容如下：
1．提出了一般道路交通流离散模型来表达交通拥堵在路段上的传播机理。模型将路段划分为合流、基本路段、排队三个部分，车辆在合流以及排队分流区域的演进特性由路段两端的交叉口特性决定。基本路段区域的交通状态则划分为四个交通相，交通相变由路段交通量决定，而流入路段车流量在基本路段上的演进由交通相、流量守恒和车辆先入先出规则来决定。模型据此可表达车辆在路段上的拥堵传播过程特性。
2．提出了交叉口时刻通行能力分配离散模型来表达交叉口去向路段对来向路段的拥堵传播机理。首先，模型考虑了交叉口诸多要素的相互作用来计算交叉口来向路段驶向去向路段的车流量，如去向路段交通流特性、相位配时、来向路段交通流特性。其次，基于第一点，定义了拥堵传播强度以及拥堵传播效应指标，发现了信号设置会使路段成为城市交通网络拥堵的瓶颈因素。
3．提出了基于用户均衡理论的驾驶员随机用户均衡择路分流离散模型来表达交叉口来向路段对去向路段的拥堵传播机理。模型能对城市交通网络环境中驾驶员择路分流发生条件及分流量进行刻画。仿真结果表明驾驶员择路分流对来向路段上的拥堵传播具有缓冲抑制作用，对分流去向路段有交通量负荷增益作用。
4．根据路段以及交叉口传播机理，借助于传染病模型，得到交通网络拥堵传播机理。给出了拥堵传播源、拥堵传播方向、路段拥堵免疫力,列举了一些拥堵瓶颈，定义了拥堵在交通网络内的传播范围指标，从网络拥堵传播的角度给出了路段从非拥堵状态到拥堵感染路段状态的状态转化关系。
基于交通拥堵传播机理，提出了实时性拥堵控制策略和适应交通流时空演变带有预测性的拥堵控制策略。两种控制策略都采用遗传变异算法搜索控制路段汇入车流的优化相位时序组合来实现控制目的。同时，以拥堵传播为策略间的通讯媒介，构建了交通网络拥堵的多种控制模式。
最后，建立了城市交通拥堵传播模型综合表达拥堵传播机理和拥堵控制策略，并通过对应的仿真平台对交通拥堵传播机理和控制策略进行了验证。
Traffic congestion, a common phenomenon of urban traffic, has a propagationcharacteristic, that is, breaking the original traffic steady state of an urban traffic network andspreading from a congestion road to its local area or even entire network. With the aim todepict the law of congestion propagation, research on the mechanism of congestionpropagation will greatly help deepen the understanding of dynamic characteristics of urbantraffic flow and manage traffic congestion.
With the equivalent flow volume for the vehicle evolution travel in the traffic networkand based on the macroscopic traffic flow and time discretization, research on the mechanismof congestion propagation is carried out in four aspects-road segments, intersections, drivers,and traffic network. The details are as follows:
1. A discrete model for traffic flow on a generic road is developed to represent themechanism of congestion propagation on a road segment. The model regards the roadsegment as three logical parts, that is, the merging section, the basic section, and the queuingsection. The evolutional travel characteristics of vehicles on the merging section and queuingsection are determined by the characteristics of intersections on two ends of the road segment.The dynamic vehicle states of the basic section are classified into four-phase traffic, whosetransitions are determined by the number of vehicles on the section, whereas the evolutionaltravel characteristics of the inflows traffic on the basic section are dominated by the trafficphase, the vehicle conservation law, and the rule of vehicle FIFO(First In First Out). Themodel is used to represent the characteristics of congestion propagation of the vehicles on aroad segment.
2. A discrete model for the assignment of instant time traffic capacity of intersections isdeveloped to represent the mechanism of congestion propagation from outgoing roadsegments to incoming road segments. Firstly, the model formulates the rate of traffic goingfrom the incoming road segments to the outgoing road segments with taking account ofelement interactions, such as the characteristics of traffic on the outgoing road segments, thephase timing, and the characteristics of traffic on the incoming road segments. Secondly, anintensity indicator and an effect indicator of congestion propagation are defined. It is discovered that intersection signal settings may turn a road segment into a congestionbottleneck in the urban traffic network.
3. A discrete model for the driver’s route choice on stochastic user equilibrium isdeveloped to represent the mechanism of congestion propagation from incoming roadsegments to outgoing road segments. The model simulates the occurrence conditions and thetraffic volume of the driver’s route choice in the urban traffic network. The simulation resultsshow that the driver’s route choice has buffering effects on the congestion propagation on theincoming road segments, and has gain effects on the traffic load of the routed outgoing roadsegments.
4. Based on the two mechanisms above and referring to epidemic models, the mechanismof congestion propagation in a traffic network is deduced. Some conceptions are given such asthe sources of congestion propagation, the direction of congestion propagation, and the roadcongestion immunity. Some bottlenecks of the network congestion are identified and thecongestion propagation range within the traffic network is defined. In addition, with respect tothe congestion propagation in the traffic network, transition relationship from a non-congestedroad segment to a congested road segment is discovered.
Based on the mechanism of traffic congestion propagation, real-time congestion controlstrategies and predictable congestion control strategies, adapting to the traffic flowevolutional spatialtemporal travel, are proposed, in which the Genetic Algorithm is adopted tosearch optimal phase timing corresponding to the inflow traffic on the controlled roadsegment in order to achieve the control goal. Meanwhile, using the congestion propagation asthe communication medium between the strategies, diverse control patterns of congestion inthe traffic network are built, too.
In summary, models for the congestion propagation in urban traffic are developed tocomprehensively represent the congestion propagation mechanism and control strategies,which are verified by the corresponding simulation platform.
对拥堵传播机理的研究立足于宏观交通流，用时间离散化的方式，以当量车流量作为车辆在交通网络中演进的基本单位，从路段、交叉口、驾驶员、交通网络四个角度展开，具体内容如下：
1．提出了一般道路交通流离散模型来表达交通拥堵在路段上的传播机理。模型将路段划分为合流、基本路段、排队三个部分，车辆在合流以及排队分流区域的演进特性由路段两端的交叉口特性决定。基本路段区域的交通状态则划分为四个交通相，交通相变由路段交通量决定，而流入路段车流量在基本路段上的演进由交通相、流量守恒和车辆先入先出规则来决定。模型据此可表达车辆在路段上的拥堵传播过程特性。
2．提出了交叉口时刻通行能力分配离散模型来表达交叉口去向路段对来向路段的拥堵传播机理。首先，模型考虑了交叉口诸多要素的相互作用来计算交叉口来向路段驶向去向路段的车流量，如去向路段交通流特性、相位配时、来向路段交通流特性。其次，基于第一点，定义了拥堵传播强度以及拥堵传播效应指标，发现了信号设置会使路段成为城市交通网络拥堵的瓶颈因素。
3．提出了基于用户均衡理论的驾驶员随机用户均衡择路分流离散模型来表达交叉口来向路段对去向路段的拥堵传播机理。模型能对城市交通网络环境中驾驶员择路分流发生条件及分流量进行刻画。仿真结果表明驾驶员择路分流对来向路段上的拥堵传播具有缓冲抑制作用，对分流去向路段有交通量负荷增益作用。
4．根据路段以及交叉口传播机理，借助于传染病模型，得到交通网络拥堵传播机理。给出了拥堵传播源、拥堵传播方向、路段拥堵免疫力,列举了一些拥堵瓶颈，定义了拥堵在交通网络内的传播范围指标，从网络拥堵传播的角度给出了路段从非拥堵状态到拥堵感染路段状态的状态转化关系。
基于交通拥堵传播机理，提出了实时性拥堵控制策略和适应交通流时空演变带有预测性的拥堵控制策略。两种控制策略都采用遗传变异算法搜索控制路段汇入车流的优化相位时序组合来实现控制目的。同时，以拥堵传播为策略间的通讯媒介，构建了交通网络拥堵的多种控制模式。
最后，建立了城市交通拥堵传播模型综合表达拥堵传播机理和拥堵控制策略，并通过对应的仿真平台对交通拥堵传播机理和控制策略进行了验证。
Traffic congestion, a common phenomenon of urban traffic, has a propagationcharacteristic, that is, breaking the original traffic steady state of an urban traffic network andspreading from a congestion road to its local area or even entire network. With the aim todepict the law of congestion propagation, research on the mechanism of congestionpropagation will greatly help deepen the understanding of dynamic characteristics of urbantraffic flow and manage traffic congestion.
With the equivalent flow volume for the vehicle evolution travel in the traffic networkand based on the macroscopic traffic flow and time discretization, research on the mechanismof congestion propagation is carried out in four aspects-road segments, intersections, drivers,and traffic network. The details are as follows:
1. A discrete model for traffic flow on a generic road is developed to represent themechanism of congestion propagation on a road segment. The model regards the roadsegment as three logical parts, that is, the merging section, the basic section, and the queuingsection. The evolutional travel characteristics of vehicles on the merging section and queuingsection are determined by the characteristics of intersections on two ends of the road segment.The dynamic vehicle states of the basic section are classified into four-phase traffic, whosetransitions are determined by the number of vehicles on the section, whereas the evolutionaltravel characteristics of the inflows traffic on the basic section are dominated by the trafficphase, the vehicle conservation law, and the rule of vehicle FIFO(First In First Out). Themodel is used to represent the characteristics of congestion propagation of the vehicles on aroad segment.
2. A discrete model for the assignment of instant time traffic capacity of intersections isdeveloped to represent the mechanism of congestion propagation from outgoing roadsegments to incoming road segments. Firstly, the model formulates the rate of traffic goingfrom the incoming road segments to the outgoing road segments with taking account ofelement interactions, such as the characteristics of traffic on the outgoing road segments, thephase timing, and the characteristics of traffic on the incoming road segments. Secondly, anintensity indicator and an effect indicator of congestion propagation are defined. It is discovered that intersection signal settings may turn a road segment into a congestionbottleneck in the urban traffic network.
3. A discrete model for the driver’s route choice on stochastic user equilibrium isdeveloped to represent the mechanism of congestion propagation from incoming roadsegments to outgoing road segments. The model simulates the occurrence conditions and thetraffic volume of the driver’s route choice in the urban traffic network. The simulation resultsshow that the driver’s route choice has buffering effects on the congestion propagation on theincoming road segments, and has gain effects on the traffic load of the routed outgoing roadsegments.
4. Based on the two mechanisms above and referring to epidemic models, the mechanismof congestion propagation in a traffic network is deduced. Some conceptions are given such asthe sources of congestion propagation, the direction of congestion propagation, and the roadcongestion immunity. Some bottlenecks of the network congestion are identified and thecongestion propagation range within the traffic network is defined. In addition, with respect tothe congestion propagation in the traffic network, transition relationship from a non-congestedroad segment to a congested road segment is discovered.
Based on the mechanism of traffic congestion propagation, real-time congestion controlstrategies and predictable congestion control strategies, adapting to the traffic flowevolutional spatialtemporal travel, are proposed, in which the Genetic Algorithm is adopted tosearch optimal phase timing corresponding to the inflow traffic on the controlled roadsegment in order to achieve the control goal. Meanwhile, using the congestion propagation asthe communication medium between the strategies, diverse control patterns of congestion inthe traffic network are built, too.
In summary, models for the congestion propagation in urban traffic are developed tocomprehensively represent the congestion propagation mechanism and control strategies,which are verified by the corresponding simulation platform.
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