ATIS下多用户混合均衡相对于随机社会最优的效率损失

在ATIS与道路收费共同作用的交通网络中,用户不仅在接受的交通信息上具有异质性,同时在时间价值上也具有异质性.文章基于这两类异质性,将用户分为安装ATIS并遵从信息、安装但不遵从、不安装的三类用户,所有用户均按照随机用户均衡的方式进行择路.文章构建了多用户随机均衡模型及其等价的变分不等式,并以用户感知总成本作为系统性能指标,分别建立了时间准则与费用准则下多用户随机社会最优模型.当收费不作为总成本的一部分时,研究了多用户均衡相对于随机社会最优的绝对效率损失问题.研究结论表明,无论采用何种度量准则,绝对效率损失上界与路段特性函数、出行者的社会经济特性、道路收费以及两准则下多用户均衡与随机社会最优时系统实际总出行成本均有关.     

ATIS和道路收费下的混合随机用户均衡的效率损失

在ATIS作用下的交通网络中,用户在交通信息的接受程度上是异质的;考虑到装有ATIS的用户并不总是遵循ATIS的建议,因此,引入信息遵从率这一参数,将所有用户分为三类:安装并遵从信息、安装但不遵从信息和不安装的用户;均按照随机用户均衡的方式进行择路,但对出行时间有不同的感知。同时考虑存在道路收费的情形下,用户在时间价值上是异质的。综合考虑交通信息与道路收费的影响,基于用户两方面的异质性,对其进行合理分类,构建了多用户多准则的混合随机均衡模型及其等价的变分不等式;当收费不作为系统总成本的一部分时,建立了时间准则与费用准则下的系统最优模型;在此基础之上,分别研究了两种准则下混合均衡相对于系统最优的效率损失,给出了效率损失上界,并进一步分析了效率损失上界与各参数间的关系;交通管理者可以从道路收费策略的实施、信息诱导系统的完善等角度进行路网的改造和优化设计。     

随机需求下UE-CN混合交通均衡分配的效率损失

在交通网络中,用户的出行需求通常是随机的,而且不同类型用户的路径选择原则存在着差异.基于UE用户和CN用户路径选择原则的异质性,对随机需求下该类混合交通均衡分配的效率损失进行研究.构建了随机需求下UE-CN混合交通均衡分配的变分不等式模型;其次,运用非线性规划方法得到了路段出行时间成本为单项式函数时的效率损失上界表达式,进而探讨了需求还服从对数正态分布时的效率损失上界情况;最后,给出了数值算例.研究结果表明,单项式成本函数时的效率损失上界依赖于其最高次幂和CN用户的数目;当需求为对数正态分布时还和最大变异系数相关.数值算例表明解析方法是可行的.     

收费机制下利己-利他混合交通均衡分配的效率损失

运用解析推导方法对收费机制下利己-利他混合交通均衡分配问题的效率损失进行研究.首先,构建了收费机制下利己-利他混合交通均衡分配问题的等价变分不等式模型;然后,通过解析推导方法得到了收费不作为系统总出行时间成本一部分时的效率损失上界;最后,给出了路段出行时间成本函数为多项式函数时的上界表达式.研究结果表明,效率损失上界与路段出行时间成本函数类、利他系数以及出行需求划分系数相关,结论以现有文献有关结论为特例.     

多用户多准则随机系统最优与最优收费

针对固定交通需求量和出行者的时间价值为离散分布的多准则随机交通均衡,分别研究了依费用度量和依时间度量的多用户多准则随机系统最优和最优收费问题.分别建立了基于费用和基于时间的随机系统最优的最优化模型,阐述了该模型解的唯一性条件及等价的变分不等式问题.运用变分不等式方法,研究了一阶最优收费的可行性,即能否依边际定价原则,通过收取与出行者类别无关的道路收费使多用户多准则随机均衡流与随机系统最优流一致.一阶最优收费不适用于依时间度量的随机系统最优情况,因而建立了一个最优化模型来得到此时的非歧视性道路收费.最后给出了具体算例.     

收费机制下一类随机需求混合交通均衡分配的非合作代价

运用算法博弈论探讨一类随机需求混合交通均衡分配在收费机制下的非合作代价.首先,构建了收费机制下随机需求UE-CN混合交通均衡分配的变分不等式模型.其次,运用解析推导法分别得到单项式出行成本函数下是否将收费作为系统总成本一部分时,该类混合交通均衡分配的非合作代价上界表达式.在此基础上,探讨了出行需求服从对数正态分布时的非合作代价上界表达式.并以数值算例验证所得结论.     

界定Stackelberg博弈下的混合平衡交通网络效率损失

考虑一个受控制的交通网络,一类用户属于领导者,按照系统最优原则选择出行路径;另一类用户属于跟随者且具有不完全信息,按照Logit型随机用户平衡原则选择出行路径.建立了描述这种Stackelberg博弈下的混合平衡出行行为的变分不等式模型,给出了满足此种混合平衡的交通网络的效率损失上界,结果表明,效率损失上界与被研究的交通网络拓扑结构,交通需求及控制系数有关.     

界定用户平衡及Logit型随机用户平衡下的混合平衡交通网络效率损失

考虑一个具有两类用户的交通网络,一类用户按照用户平衡原则选择出行路径,另一类用户按照Logit型随机用户平衡原则选择出行路径.建立了描述这种混合平衡出行行为的变分不等式模型,给出了满足此种混合平衡的交通网络效率损失上界,结果表明,效率损失上界与被研究的交通网络拓扑结构,交通需求及两类用户的划分比例系数有关.     

基于经典BPR阻抗函数的随机交通网络主从博弈的效率损失

现代大城市交通愈发拥堵和智能交通系统广泛应用背景下,拥堵收费、智能诱导和主从博弈、随机均衡分别是重要的管理手段和客观现象.考虑对交通网络中各路段实施收费策略,利用随机用户均衡(SUE)交通流模式研究了效率损失的上界,该交通流模式是由一部分受控于Stackelberg策略的用户所诱导产生的.假设路段时间函数是可分离的单调增的凸函数,并固定交通网络起讫点(OD)需求,在建立Logit-SUE的等价变分不等式(VI)的基础上推导出SUE和Stackelberg策略条件下交通网络的效率损失表达式.这对城市交通管理的系统决策具有重要参考价值.     

方格网络上用户均衡行为效率损失研究

针对用户出行时追求费用最短的路径,而不考虑其它用户如何选择路径,在一般网络中导致系统费用较高的问题,从实际出发,本文重点讨论特殊网络-方格网络上纳什均衡流与系统最优流之间的关系,研究了用户均衡行为的效率损失.研究结果表明,在方格网络上,当路阻函数是系数非负的线性函数和二次函数时,用户均衡行为的效率损失分别是0和0.35,而一般网络中用户均衡行为的效率损失分别是1/3和0.626,说明方格网络具有较好传送流量的功能.该研究为道路建设部门进行道路改造和增加新道路设计提供理论依据.     

Bounding the inefficiency of logit-based stochastic user equilibrium

Bounding the inefficiency of selfish routing has become an emerging research subject. A central result obtained in the literature is that the inefficiency of deterministic User Equilibrium (UE) is bounded and the bound is independent of network topology. This paper makes a contribution to the literature by bounding the inefficiency of the logit-based Stochastic User Equilibrium (SUE). In a stochastic environment there are two different definitions of system optimization: one is the traditional System Optimum (SO) which minimizes the total actual system travel time, and the other is the Stochastic System Optimum (SSO) which minimizes the total perceived travel time of all users. Thus there are two ways to define the inefficiency of SUE, i.e. to compare SUE with SO in terms of total actual system travel time, or to compare SUE with SSO in terms of total perceived travel time. We establish upper bounds on the inefficiency of SUE in both situations.     

A multiclass,multicriteria logit-based traffic equilibrium assignment model under ATIS

This paper presents a multiclass, multicriteria (cost versus time) logit-based traffic equilibrium assignment model in road networks served by advanced traveler information systems (ATIS). All users are differentiated by their own value of time (VOT) that follows some probability distribution. Users of each class, having their own VOT, are further divided into two groups, equipped and unequipped with ATIS respectively. The travel disutility received by each user is defined as a linear bi-criteria combination of travel time and monetary travel cost. It is assumed that all users make their route choices in a logit-based stochastic manner, but the equipped users have lower perception variation on the travel disutility than the unequipped due to the ATIS service. The model is formulated as a fixed-point problem and solved by the method of successive averages in conjunction with logit assignment. Numerical results show that the traditional single-class and/or single-criterion models may overestimate or underestimate the benefit from ATIS services.     

多用户类多准则交通分配的势博弈与拥挤定价

交通管理者在解决路网拥挤问题时,并不知道出行者的出行效用,同时管理者难以对出行者的路径选择行为做出准确的观测.运用势博弈理论分析多用户类多准则交通行为的演化过程,得到了固定需求和弹性需求情形下的可容许动态(一种刻画出行者通过转换路径增加当前效用的近似调整行为的演化动态),证明当路段时间函数和逆需求函数为严格单调、连续、可微时,所对应的交通分配是势博弈问题的惟一Nash均衡点.进一步研究了固定需求下的可变拥挤道路收费问题,得到了在当前系统状态下实现系统最优交通分配的拥挤收费水平.     

A turning restriction design problem in urban road networks

Turning restriction is one of the commonest traffic management techniques and an effective low cost traffic improvement strategy in urban road networks. However, the literature has not paid much attention to the turning restriction design problem (TRDP), which aims to determine a set of intersections where turning restrictions should be implemented. In this paper, a bi-level programming model is proposed to formulate the TRDP. The upper level problem is to minimize the total travel cost from the viewpoint of traffic managers, and the lower level problem is to depict travelers’ route choice behavior based on stochastic user equilibrium (SUE) theory. We propose a branch and bound method (BBM), based on the sensitivity analysis algorithm (SAA), to find the optimal turning restriction strategy. A branch strategy and a bound strategy are applied to accelerate the solution process of the TRDP. The computational experiments give promising results, showing that the optimal turning restriction strategy can obviously reduce system congestion and are robust to the variations of both the dispersion parameter of the SUE problem and the level of demand.     

A Multi-Class Dynamic User Equilibrium Model for Queuing Networks with Advanced Traveler Information Systems

This paper presents a formulation and solution algorithm for a composite dynamic user-equilibrium assignment problem with multi-user classes, in order to assess the impacts of Advanced Traveler Information Systems (ATIS) in general networks with queues. Suppose that users equipped with ATIS will receive complete information and hence be able to choose the best departure times and routes in a deterministic manner, while users not equipped with ATIS will have incomplete information and hence may make decisions on departure times and routes in a stochastic manner. This paper proposes a discrete-time, finite-dimensional variational inequality formulation that involves two criteria regarding the route and departure time choice behaviors, i.e., the deterministic dynamic user equilibrium and the nested logit-based stochastic dynamic user equilibrium. The formulation is then converted to an equivalent “zero-extreme value” minimization problem. A heuristic algorithm based on route/time-swapping process is proposed, which iteratively adjusts the route and departure time choices to reach closely to an extreme point of the minimization problem. A numerical example is used to demonstrate the effectiveness of the proposed approach for assessing the ATIS impacts such as changes in individual travel costs, departure times, route inflows, queuing peaks and total network travel cost. This revised version was published online in July 2006 with corrections to the Cover Date.     

基于鲁棒优化的随机时变网络最优路径研究

交通事故、恶劣天气以及偶发的交通拥堵等都会导致道路交通网络中行程时间的不确定性,极大地影响了道路交通系统的可靠性,同时给日常生活中出行计划的制定以及出行路径的选择带来了不便。因此,本次研究将综合考虑道路交通网络中由于交通流量的全天变化所导致的路径行程时间的时变特征,以及由于事故、天气等不确定因素所导致的路径行程时间的随机特征,并以此作为路网环境的假设条件,对出行路径选择问题进行研究。具体地,首先建立行程时间的动态随机变量,并在此基础上模拟构建了随机时变网络。随后,定义了该网络环境下路径选择过程中所考虑的成本费用,并通过鲁棒优化的方法,将成本费用鲁棒性最强的路径视为最优路径。随后,在随机一致性条件下,通过数学推导证明了该模型可以简化为解决一个确定性时变网络中的最短路径问题。最终,具有多项式时间计算复杂度的改进Dijkstra算法被应用到模型的求解中,并通过小型算例验证模型及算法的有效性。结果表明,本研究中所提出的方法可以被高效率算法所求解,并且不依赖于先验行程时间概率分布的获取,因此对后续的大规模实际城市道路网络应用提供了良好的理论基础。此外,由于具有行程时间随机时变特征的交通网络更接近实际道路情况,因此本次研究的研究成果具有较高的实际意义和应用价值。     

Cost minimization and the stochastic discount factor

It is shown that a cost function subject to internal costs of adjustment induces a stochastic discount factor (pricing kernel) that is a function of random output, input and output prices, existing capital stock, and investment. The only assumption on firm preferences is that they are increasing in current period consumption and future stochastic consumption. This ensures that the firm will always act to minimize current period cost of providing future consumption, and it is the first-order conditions for this cost minimization problem that generate the stochastic discount factor, which itself can be interpreted as the marginal variable cost of varying stochastic output. A cost-based pricing kernel is estimated using annual time-series data on macroeconomic variables and returns data for the S&P 500 and commercial paper.     

A dynamic route guidance system based on real traffic data

Mobility is one of the vital goods of modern societies. One way to alleviate congestion and to utilise the existing infrastructure more efficiently are Advanced Traveller Information Systems (ATIS). To provide the road user with optimal travel routes, we propose a procedure in two steps. First on-line simulations supplemented by real traffic data are performed to calculate actual travel times and traffic loads. Afterwards these data are processed in a route guidance system which allows the road user an optimisation with regard to individual preferences. To solve this multiple criteria optimisation problem fuzzy set theory is applied to the dynamic routing problem.