基于预知OD的城市路网交通流路径优化研究

针对城市路网交通流分布不均引起的交通拥堵问题,提出了在预约出行交通背景下基于预知OD的交通流路径优化方法。首先,分析了预约出行交通背景下预知OD的数据环境;其次,根据动态用户均衡准则,对预知的OD进行流量分配,给出预约出行车辆的路径;接着,使用预测控制的方法,结合路网上预约车辆的状态,以路网上路段的饱和度和未预约车辆的行程时间最小化为目标,从系统和用户两个角度对未预约车辆的路径进行实时的诱导,通过连续时域的滚动优化控制,优化交通流的路径;最后,对本方法的实现和应用做了思考和探索,对本研究做了总结。     

基于TransCAD的BPR路阻函数对OD反推影响分析

随着交通信息采集技术的发展,路段流量的获取变得越来越容易。因此,通过路段观测流量来反推OD矩阵的方法成为一种经济实用的方法。本文介绍了基于TransCAD软件OD矩阵反推的方法,并结合苏州市部分特定路网建立了路网模型。运用单因素敏感性分析法,结合选定的均方根误差、相对误差以及模态置信准则(MAC)等三个评价指标,分析BPR路阻函数参数α和β对OD矩阵反推结果精度的影响。在反推过程中建议使用随机用户平衡分配法(SUE),并给出α和β的建议取值范围,可为提高利用TransCAD软件进行OD矩阵反推精度提供参考。     

不确定OD需求下混合交通网络设计的鲁棒优化模型

假定OD需求是不确定的,但它属于一个有界多面体,应用鲁棒优化的方法对不确定OD需求下混合网络设计问题进行了研究,建立了基于用户均衡的混合网络设计的极小极大模型,并采用需求生成的算法求解不确定OD需求下混合网络设计的鲁棒对应模型。数值算例的结果表明应用鲁棒优化方法得到的混合网络设计方案不仅更加符合实际,而且较传统确定性的混合网络设计方案具有更高的可靠性。     

城市OD区间道路总容量的模型及研究

城市道路交通是城市社会赖以生存和发展的基础,因此估算城市道路网容量是一个迫切需要解决的问题。而城市OD区间路网总容量的估算对解决城市区间交通问题意义重大。本文定义了城市OD间路网总容量,并在交通流平衡分配的原理和路径走行时间与路径上交通流量之间的关系的基础上,建立了利用路段观测交通量和OD区路径走行时间推算城市OD间道路网容量的数学模型,该模型克服了以往模型的数据不好挖掘等的特点。通过对模型的解的存在唯一性的严格证明及对比算例应用,表明模型能逼近实际。     

基于模拟退火的OD矩阵估计研究

由路段交通量估计交通起止点矩阵OD时,一般都要求解非线性的目标函数,使用通常的随机搜索算法容易陷入局部最优的陷阱。本文将模拟退火算法应用于OD估计问题,使用双层规划的OD估计模型,并给出了启发性算法。     

基于交通影响分析的物流园区规模定位研究

由于现有研究未考虑物流园区与周边交通环境的关系而存在局限性,提出了基于交通影响分析的研究方法.以物流园区不能使路段流量超过其上限值为条件,建立了路网达到用户均衡状态时的物流园区交通量的最优化模型,并采用改进的遗传算法求解,最后用经验公式计算出物流园区的规模.经算例验证,该方法对物流园区受周边交通环境制约时的规模定位研究是可行、有效的.     

基于出租车GPS数据聚类分析醮交通小区动态划分方法研究

对交通出行数据进行优化，抽取出租车载客过程中乘客上下车的GPS位置坐标。基于聚类与交通小区划分的相似性，采用K-Means聚类法进行交通小区的划分。首先，通过聚类得到交通出行OD矩阵，然后据此划分出交通小区。基于Google Maps API，搭建了软件平台。通过试验可以看出，这种动态划分方法得到的区域能够与现有的交通小区相吻合。这种高实时的交通小区划分方法将对动态的OD估计有着极大的参考价值。     

福建省经济增长因素的研究

本文研究福建经济增长因素的相关问题,利用协整理论与Granger因果关系检验方法,分析了福建省出口总量、进口总量、全社会固定投资、全民消费水平与经济增长之间的关系。研究表明,福建省的经济增长与出口总量、进口总量、全社会固定投资、全民消费水平之间存在着长期均衡关系,出口总量、进口总量的扩张是经济增长的原因;而经济增长带动了全社会固定投资以及全民消费水平的提高。因此,福建省的经济增长是出口导向型的,应在加大出口的同时,重视进口的作用。     

实时OD估计中卡尔曼滤波算法研究

ITS研究中，动态OD矩阵估计是交通动态分配的关键因素。针对OD矩阵难以获得的问题，回顾动态OD矩阵估计理论的发展历程，明确该领域研究中的三个关键问题：状态变量的选择、系统方程的确定、OD量与路段流量的关系（分配矩阵）。在此基础上介绍一种基于历史OD矩阵数据的估计方法，卡尔曼滤波算法，为动态OD矩阵估计理论的进一步的研究奠定基础。     

城际交通联系对城市住宅地价差距的影响研究——以中国巨型城市区域为例

研究交通对住宅地价区域差距的影响对深刻理解交通对于区域发展差距及要素分布的关系以及促进区域均衡发展具有重要意义。采用2004—2020年间偶数年中国11个巨型城市区域内部城际列车联系数据与城市住宅地价数据研究城际交通对区域内住宅地价差距的影响，回归结果显示，城际列车联系与巨型城市区域内住宅地价差距之间总体呈“U”型关系，即城际列车联系缩小了多数巨型城市区域的住宅地价差距，但却开始扩大东部巨型城市区域的住宅地价差距；人口分布均衡化是其中缩小效应的重要机制，而高端生产要素在核心城市的集聚则是扩大东部巨型城市区域住宅地价差距的主要原因。这些发现为交通与要素分布的关系等经典问题提供了新的证据，拓展了以往关于区域发展阶段与区域均衡的认知。     

爱尔朗排队模型在配送中心车辆调度中的应用研究

利用随机过程和排队论的相关知识,通过对爱尔朗排队模型进行性能分析以及参数求解,给出其在配送中心中的具体应用,并通过实例求解。通过求解系统空闲的概率、系统平均队长、排队等候平均队长、车辆在配送中心中的逗留时间、平均排队时间,比较单路排队和多路排队的区别,以此判断配送中心的车辆调度系统建设是否合理。     

Econometric analysis of linearized singular dynamic stochastic general equilibrium models

In this paper I propose an alternative to calibration of linearized singular dynamic stochastic general equilibrium models. Given an a-theoretical econometric model as a representative of the data generating process, I will construct an information measure which compares the conditional distribution of the econometric model variables with the corresponding singular conditional distribution of the theoretical model variables. The singularity problem will be solved by using convolutions of both distributions with a non-singular distribution. This information measure will then be maximized to the deep parameters of the theoretical model, which links these parameters to the parameters of the econometric model and provides an alternative to calibration. This approach will be illustrated by an application to a linearized version of the stochastic growth model of King, Plosser and Rebelo.     

Stochastic Route Choice Equilibrium Assignment for Travelers with Heterogeneous Regret Aversions

Most route choice models assume that people are completely rational. Recently, regret theory has attracted researchers’ attentions because of its power to depict real travel behavior. This paper proposes a multiclass stochastic user equilibrium assignment model by using regret theory. All users are differentiated by their own regret aversion. The route travel disutility for users of each class is defined as a linear combination of the travel time and anticipated regret. The proposed model is formulated as a variational inequality problem and solved by using the self-regulated averaging method. The numerical results show that users’ regret aversion indeed influences their route choice behavior and that users with high regret aversion are more inclined to change route choice when the traffic congestion degree varies.     

Characterization of the Walrasian equilibria of the assignment model

We study the assignment model where a collection of indivisible goods are sold to a set of buyers who want to buy at most one good. We characterize the extreme and interior points of the set of Walrasian equilibrium price vectors for this model. Our characterizations are in terms of demand sets of buyers. Using these characterizations, we also give a unique characterization of the minimum and the maximum Walrasian equilibrium price vectors. Also, necessary and sufficient conditions are given under which the interior of the set of Walrasian equilibrium price vectors is non-empty. Several of the results are derived by interpreting Walrasian equilibrium price vectors as potential functions of an appropriate directed graph.     

Frequency domain estimation of temporally aggregated Gaussian cointegrated systems

This paper considers joint estimation of long run equilibrium coefficients and parameters governing the short run dynamics of a fully parametric Gaussian cointegrated system formulated in continuous time. The model allows the stationary disturbances to be generated by a stochastic differential equation system and for the variables to be a mixture of stocks and flows. We derive a precise form for the exact discrete analogue of the continuous time model in triangular error correction form, which acts as the basis for frequency domain estimation of the unknown parameters using discrete time data. We formally establish the order of consistency and the asymptotic sampling properties of such an estimator. The estimator of the cointegrating parameters is shown to converge at the rate of the sample size to a mixed normal distribution, while that of the short run parameters converges at the rate of the square root of the sample size to a limiting normal distribution.     

带交货期限制的物流枢纽站选址问题

研究了在要求每对被服务的O-D能够在规定的交货期内从供给点经过一个或两个枢纽站到达需求点,如何选择P个枢纽站以使被服务的O-D流达到最大的问题。建立了一个多分配枢纽站最大覆盖问题的改进模型,并给出了贪婪相加-替代的启发式算法。     

非高斯随机分布系统研究现状的分析

针对非高斯随机分布系统理论研究的发展问题,从非高斯随机分布系统的研究背景、系统静态模型的建立方法、系统动态模型的建立方法、非高斯随机分布系统的性能指标以及常用的控制算法等方面介绍了非高斯随机分布控制系统的研究现状,使读者对非高斯随机分布系统理论能进一步深入的了解。     

Noisy signaling in discrete time

This paper characterizes the equilibrium set of a dynamic noisy-signaling model in discrete time. A seller privately knows the quality of her asset. She can exert a costly effort to generate stochastic returns. Buyers stochastically arrive over time and, after observing the history of returns, they make price offers. In our model, the equilibrium behavior of the buyers is discontinuous: they only make acceptable (high) offers if the posterior about the quality is above a given threshold. As a result, the recursive nature of the model replicates the discontinuity, giving the equilibrium continuation payoff a complex self-replicating structure that may take the form of a devil’s staircase.     

Spatial barter economies under locational choice

This paper presents a model of spatial barter economy with costly transportation to the CBD and a continuum of households. The notions of competitive equilibrium under spatial choice as well as under fixed assignment of households to their place of residence are introduced. Using a formal framework which allows for a simultaneous treatment of both types, equilibrium results will be derived under natural conditions for household's characteristics and transportation technologies.     

Evaluating Point and Density Forecasts of DSGE Models

This paper investigates the accuracy of forecasts from four dynamic stochastic general equilibrium (DSGE) models for inflation, output growth and the federal funds rate using a real‐time dataset synchronized with the Fed's Greenbook projections. Conditioning the model forecasts on the Greenbook nowcasts leads to forecasts that are as accurate as the Greenbook projections for output growth and the federal funds rate. Only for inflation are the model forecasts dominated by the Greenbook projections. A comparison with forecasts from Bayesian vector autoregressions shows that the economic structure of the DSGE models which is useful for the interpretation of forecasts does not lower the accuracy of forecasts. Combining forecasts of several DSGE models increases precision in comparison to individual model forecasts. Comparing density forecasts with the actual distribution of observations shows that DSGE models overestimate uncertainty around point forecasts. Copyright © 2013 John Wiley & Sons, Ltd.