固定费率下城市出租车拥挤收费模型与算法

针对出租车自身的特殊性, 研究了实施拥挤收费政策过程中出租车是否也应进行拥挤收费。在收费费率已知条件下, 采用组合网络均衡模型描述了出租车拥挤收费前后对出行产生、模式划分、流量分配以及出行分布的影响, 构建了与之等价的最优化模型, 设计了求解模型的启发式算法, 比较了对出租车征收拥挤费前后的社会福利变化。算例表明, 收费前的社会福利总是明显大于收费后的, 并且二者之间的差距随着出行者时间价值(VOT)的增加而减小, 随着弹性灵敏参数的增加而增大。这一研究有助于为拥挤收费政策制定者提供科学的决策依据。     

Analysis of two-tier public service systems under a government subsidy policy

Some public service systems such as healthcare systems consist of both free public service provider with a long wait time and paid private service provider with a short wait time. Such service systems are often called a two-tier service system. In general, more customers will choose the free service provider (SP). To reduce the congestion in the free system, the government may encourage customers to use the pay system by offering them a subsidy. This paper studies whether such a subsidy can reduce the free system’s waiting time and improves the social welfare. While the objective of the free system is to maximize its own total customers’ utility, the objective of the pay system is to maximize its profit. We develop a mixed duopoly game to analyze the Nash equilibrium for the competition between the free and toll systems. Two scenarios with unregulated and regulated prices are considered. When the pay system price is unregulated (the private SP can set prices freely), we find that if customers are less sensitive to the service delay, the subsidy policy can effectively reduce the expected waiting time for the free system and increase the customer utility surplus of the entire two-tier system. However, if customers are more sensitive to the service delay, the subsidy policy may have the opposite effect. When the pay system price is regulated (the price determined by government), the subsidy policy can effectively reduce the expected waiting time for the free system and improve the social welfare of the two-tier system. And there exists an optimal regulated price to maximize the social welfare of the entire public service system.     

Urban traffic congestion propagation and bottleneck identification

Bottlenecks in urban traffic network are sticking points in restricting network collectivity traffic efficiency. To identify network bottlenecks effectively is a foundational work for improving network traffic condition and preventing traffic congestion. In this paper, a congestion propagation model of urban network traffic is proposed based on the cell transmission model （CTM）. The proposed model includes a link model, which describes flow propagation on links, and a node model, which represents link-to-link flow propagation. A new method of estimating average journey velocity （AJV） of both link and network is developed to identify network congestion bottlenecks. A numerical example is studied in Sioux Falls urban traffic network. The proposed model is employed in simulating network traffic propagation and congestion bottleneck identification under different traffic demands. The simulation results show that continual increase of traffic demand is an immediate factor in network congestion bottleneck emergence and increase as well as reducing network collectivity capability. Whether a particular link will become a bottleneck is mainly determined by its position in network, its traffic flow （attributed to different OD pairs） component, and network traffic demand.     

基于延迟函数次梯度启发式道路交通补偿策略

拥挤收费被认为是解决交通拥挤的有效方法,解决道路交通拥堵的主要想法是,对于有些容易造成拥堵的道路进行收费,而对于其他未充分利用的道路进行适当补偿,对此提出一种基于延迟函数的次梯度启发式道路交通补偿策略。首先,给出道路集的收费/补贴的非线性规划模型,主要是基于Beckmann最小化目标函数实现,然后利用库恩-希尔斯条件和拉格朗日乘子建立模型的条件约束;其次,基于启发式算法建立道路交通的定价补偿策略,利用边际成本建立延迟函数分析模型,然后基于次梯度法进行模型的优化;最后,通过在真实道路网络上的仿真实验,显示所提算法在旅行时间、交通流量、收敛性等指标上均具有较好的性能,验证了算法的有效性。     

交叉路口智能图像管理系统的设计与实现

针对城市道路交叉路口上下班拥挤问题,提出了设计基于工控机与单片机构建智能交通图像管理系统必要性;文中给出了,介绍了系统的硬件组成与设计原理,详细论述了各模块实现的功能及电路实现,给出了系统上、下位机的总线接口协调以及控制软件与管理软件设计方案,特别是针对系统工作环境提出的可靠性设计方法,使系统在具备了可扩展性同时,进一步提高了系统工作的稳定性。     

Modeling traffic operations at electronic toll collection and traffic management systems

Automatic Vehicle Identification (AVI) technology is one possible solution to traffic congestion at existing transportation facilities. This paper presents a mathematical model of traffic conditions for toll plaza facilities that includes AVI toll collection services among other conventional services.

Three types of services are available: manual toll service, in which transactions are handled by a toll collector, automatic toll service, in which coin machines are utilized, and AVI toll collection service. In addition, mixed lanes, which provide more than one of the above services, are considered by the model.

For a given rush hour, queue lengths and delays can be calculated for different toll plaza configurations. Comparison of their performance may aid operators in the management of the lane configurations until all users of the facility become AVI patrons.     

城市区域交通信号迭代学习控制策略

城市交通流具有复杂的非线性动态特性, 在交通控制中难以对其进行精确的数学建模; 同时, 以天为周期, 宏观交通流又呈现出明显的周期性特征. 鉴于此, 提出一种基于迭代学习的城市区域交通信号控制策略, 通过对交通信号的迭代控制, 使路段的平均占有率收敛于期望占有率, 从而使绿灯时间得到充分利用并防止交通拥堵的发生, 保证了交通流在路网中的高效平稳运行. 严格的理论推导证明了该方法的收敛性, 仿真结果验证了该方法的有效性.

     

A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

Advanced information and communication technologies can be used to facilitate traffic incident management. If an incident is detected and blocks a road link, in order to reduce the incident-induced traffic congestion, a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this work. Time-dependent shortest path algorithms are used to generate a subnetwork where vehicles should receive such information. A simulation approach based on an extended cell transmission model is used to describe traffic flow in urban networks where path information and traffic flow at downstream road links are well modeled. Simulation results reveal the influences of some major parameters of an incident-induced congestion dissipation process such as the ratio of route-changing vehicles to the total vehicles, operation time interval of the proposed strategy, traffic density in the traffic network, and the scope of the area where traffic incident information is delivered. The results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents.      

基于知识的城市交通拥挤疏导决策支持系统的构造

本文首先分析了当发生交通拥挤时，城市道路 交通状况的特点，表明建立智能化城市交通拥挤疏导决策支持系统的重要性．在此基础上， 提出了系统的设计思想，系统结构、功能及其实现方法．该系统融合了丰富的交通拥挤管理 知识，采用定性推理和定量计算相结合的工作方式进行决策问题的求解，最终实现一个基于 知识的决策系统，并且遵照本文提出的系统构造，在苏南某城市开发的实际系统已投入运行 ，实践表明系统构造是有效的．     

Design of Regulatory Traffic Light Control Systems with Synchronized Timed Petri Nets

Fixing the phases is one of the common methods to control an urban traffic network. Once a road is filled with a high traffic flow approaching its capacity, the conventional traffic light controller is not able to handle this traffic congestion phenomenon well. In this paper, we propose a novel regulatory traffic light control system to handle such traffic congestion by using synchronized timed Petri nets (STPNs). Three kinds of intersections in an urban traffic network are defined and employed to demonstrate our new regulatory traffic light control system models. Finally, the liveness and reversibility of the proposed STPN models are proven through the reachability graph analysis method. To our knowledge, this is the first work that solves a traffic congestion problem with a regulatory traffic light control technique that is effective in preventing vehicles from entering traffic congestion zones.     

Models and a relaxation algorithm for continuous network design problem with a tradable credit scheme and equity constraints

The sustainable problems of transportation have become noticeable in the majority of cities worldwide. Many researchers are devoted themselves into traffic congestion. Generally, traffic congestion could be alleviated via increasing road capacity (supply) or reducing traffic (demand). In this paper, we model CNDP which has a tradable credit scheme and equity constraints in order to research on the way of releasing congestion by combining increasing supply and reducing demand. Firstly, the bilevel programming problem is proposed to model the CNDP with a tradable credit scheme. The upper level (the government) chooses optimal capacity enhancement for some existing links to minimize the total system costs under a budget constraint. The lower level chooses the optimal route based on considering the generalized travel cost in which both travel time and credit charging for using the link are involved. And then, considering the inequity problem in terms of equilibrium O–D travel cost and link travel time, the model is proposed by incorporating equity constraints into CNDP with a tradable credit scheme. After presenting a relaxation algorithm, the experiments on Sioux Falls network are illustrated. Finally, conclusion and some future research directions are presented.     

多重处理的道路拥堵识别可视化融合分析

目的 随着城市交通拥堵问题的日益严重,建立有效的道路拥堵可视化系统,对智慧城市建设起着重要作用。针对目前基于车辆密度分析法、车速判定法、行驶时间判定法等模式单一,可信度低的问题,提出了一种基于DBSCAN+（density-based spatial clustering of applications with noise plus）的道路拥堵识别可视化方法。方法 引入分块并行计算,相较于传统密度算法,可以适应大规模轨迹数据,并行降维聚类速度快。对结果中缓行区类簇判别路段起始点和终止点,通过曲线拟合和拓扑网络纠偏算法,将类簇中轨迹样本点所表征的路段通过地图匹配算法匹配在电子地图中,并结合各类簇中浮动车平均行驶速度判别道路拥堵程度,以颜色深浅程度进行区分可视化。结果 实验结果表明,DBSCAN+算法相较现有改进的DBSCAN算法时间复杂度具有优势,由指数降为线性,可适应海量轨迹点。相较主流地图产品,利用城市出租车车载OBD（on board diagnostics）数据进行城区道路拥堵识别,提取非畅通路段总检出长度相较最优产品提高28.9%,拥堵识别命中率高达91%,较主流产品城区拥堵识别平均命中率提高15%。结论 在城市路网中,基于DBSCAN+密度聚类和缓行区平均移动速度的多表征道路拥堵识别算法与主流地图产品相比,对拥堵识别率、通勤程度划分更具代表性,可信度更高,可以为道路拥堵识别的实时性提供保障。     

Cloud Computing System Management Under Flat Rate Pricing

Success of cloud computing service depends on an acceptable pricing mechanism both by users and the service provider. Piece rate pricing by counting work load should be favorable for the service provider due to the QoS control and finite resource, such as computing and, communication powers. Though the pricing mechanism based on counting work load is reasonable and fair, the experiences learned from ADSL, 3G and Wi-Fi show a different story. The flat rate pricing mechanism is the winner all the way. This study proposes a flat rate pricing mechanism with congestion control, called FRPCC. In the cloud computing system, allocation of resources can be formulated as an optimization problem seeking to maximize the sum of the utility function of each user under the constraints of fairness. The piece rate pricing mechanism is easy to achieve the social welfare but is not easy to be acceptable for customers. Consequently, we propose a congestion control scheme to reach the same goal with a flat rate pricing mechanism. The proposed FRPCC approach can achieve social welfare in the cloud computing environment. Performance evaluations show efficacy of, FRPCC approach in providing social welfare under fairness and preventing congestion.     

Urban traffic congestion estimation and prediction based on floating car trajectory data

Traffic flow prediction is an important precondition to alleviate traffic congestion in large-scale urban areas. Recently, some estimation and prediction methods have been proposed to predict the traffic congestion with respect to different metrics such as accuracy, instantaneity and stability. Nevertheless, there is a lack of unified method to address the three performance aspects systematically. In this paper, we propose a novel approach to estimate and predict the urban traffic congestion using floating car trajectory data efficiently. In this method, floating cars are regarded as mobile sensors, which can probe a large scale of urban traffic flows in real time. In order to estimate the traffic congestion, we make use of a new fuzzy comprehensive evaluation method in which the weights of multi-indexes are assigned according to the traffic flows. To predict the traffic congestion, an innovative traffic flow prediction method using particle swarm optimization algorithm is responsible for calculating the traffic flow parameters. Then, a congestion state fuzzy division module is applied to convert the predicted flow parameters to citizens’ cognitive congestion state. Experimental results show that our proposed method has advantage in terms of accuracy, instantaneity and stability.     

城市交通多线路协调优化仿真模型研究

为缓解城市交通拥堵,提高道路利用率,提出一种新的简单实用的城市交通多线路协调优化控制模型及时空相位演化方法,并给出了改进的遗传优化算法。通过仿真系统的开发,实现了城市交通的多线路优化控制仿真并获得了满意的效果。对比优化前后的数据,优化后调度线路上的车流以最少平均停车次数和最短平均延迟时间到达目的地。利用本优化模型可以实现以较小的代价成本疏导城市交通,提高城市道路通行能力。     

Optimal mixed charging schemes for traffic congestion management with subsidy to new energy vehicle users

Traffic congestion and emissions are two severe and urgent problems in the transportation field. To alleviate congestion and encourage green travel, this paper studies a mixed charging scheme for the multimodal transportation network including conventional vehicles (CV) and new energy vehicles (NEV). We exploit the optimal mixed charging schemes according to the mixed equilibria and system optimum model. The mixed equilibria characterized by the variational inequality system represents that the players follow either the user equilibrium or Cournot–Nash equilibrium principle in routing choice. The proposed mixed scheme comprises a regular tolling plan and a tradable credit plan for the CV and NEV users, respectively, where the tradable credits can be seen as a subsidy to the NEV users since they are issued free by the government. Moreover, the existence of the optimal mixed charging scheme is proved for the multimodal transportation network and demonstrated numerically by a concrete example.     

Robust Stabilization and H∞ Control of Cooperative Driving System with Time Delay in Variable Speed‐Limited Area from Cyber‐Physical Perspective

In order to suppress traffic congestion and reduce traffic accidents, a cooperative driving systems with time‐varying delay and nonlinearity under uncertain external disturbances in a variable speed‐limited area is proposed from a cyber‐physical perspective. Robust stabilization of the cooperative driving system is investigated by using Lyapunov‐Krasovskii functional stability theory. Robust H_∞ control is designed to guarantee that the proposed system is robustly stable. Meanwhile, sufficient conditions for the state feedback controller are proposed to attenuate the external disturbances on the basis of linear matrix inequality. Finally, some useful results are obtained from the comparisons between without control scheme, existing ACC (adaptive cruise control) scheme, and the proposed control scheme, which could suppress traffic congestion and reduce traffic accidents.     

基于拥堵系数的道路交通网络关键路段辨识

城市道路交通的路段信息与车流量信息对道路交通的安全、高效运行至关重要.在交通高峰时期,通过对关键路段加以控制,可实现整个道路交通网络的完全能控.为寻找路网中的关键路段,将道路网络的交叉口-节点模型转化为道路网络的路段-节点模型,基于路段信息与车流量信息提出拥堵系数来衡量道路交通网络的车辆拥堵程度,并将其作为道路网络的路段-节点模型的边权重,最后运用关键路段辨识算法对道路交通网络的关键路段进行辨识.以沈阳市皇姑区主城区道路为例建立以拥堵系数为权重的网络模型, 按照所提方法辨识的关键路段数量为14条,约占道路网络总路段数的14.3%,具有较低的控制成本,且大部分为由北向南方向和由西向东方向.其中8条路段分布在皇姑区道路实时拥堵排行前5名,约占关键路段总数的57.1%,表明所给出的关键路段更多地分布在交通状态较为拥堵的路段上,符合实际情况.     

基于时空势场修正多处理器城市拥堵并行聚类分析

为提升城市城市道路拥堵检测和治理效率,提出一种基于势场修正多处理器并行聚类的城市道路拥堵时空分析方法。首先,利用GIS四维空间时态数据给出城市道路拥堵的时空模型,并通过设置虚拟数据参数实现时间的低密度采样处理,获得城市道路拥堵路段时空规律性的有效检测;其次,基于势场修正法构建多处理器并行聚类方法,分别设计了距离矩阵、邻域半径和密度函数的并行化多处理计算方法,并实现了并行聚类算法设计,同时给出上述并行计算过程的计算复杂度分析定理;最后,以北京市为试验区,对所提城市道路拥堵分析算法性能进行了验证,实验结果表明,所提方法可实现城市城市道路拥堵情况的快速有效检效检测分析,可为城市道路拥堵管理提供数据支撑。     

隐马尔可夫模型的道路拥堵时间预测

道路车辆拥堵问题导致交通事故增加,降低了居民的出行效率,长时间的道路拥堵更是加重了环境污染,造成国家经济损失等诸多问题。为缓解城市道路交通的拥堵问题,提高出行效率,基于隐马尔可夫模型,针对已有道路拥堵时间数据进行采集与建模,并对该隐马尔可夫模型进行训练,通过算法计算与分析,预测未来一段时间的道路拥堵情况,为人们的出行提供拥堵时间预测,而后提出不同时段通过道路用时最短的最优路径。对韦尔奇算法进行改进,在原算法基础上增加考虑前[n]时刻状态。利用改进型韦尔奇算法,使得训练集参数更精确,达到预测精度更高的目的。实验结果表明,预测数据结果与真实数据相比,误差不超过3%,该模型预测结果具有较高准确性。