基于内生参考点的交通网络均衡模型

应用累积前景理论研究了随机交通网络中出行者有限理性的路径选择行为,选择期望 超额出行时间作为参考点,反映出行者同时考虑出行时间的可靠性和不可靠性,建立了基于累积前景理论的随机网络均衡及其等价的变分不等式模型,运用基于连续平均法的启发式算法求解,并给出算例验证了该模型和算法,最后分析了有限理性的假设和内生的参考点对出行者路径选择行为和随机网络均衡的影响．     

城市交通多类型随机用户出行决策模型研究

考虑城市交通中有多类出行者的一般情况,在ATIS等交通信息系统的影响下,不同类型的出行者对路径出行时间有不同理解,用不同的参数来反映.在此基础上,给出考虑路径选择、方式选择、讫点选择及是否出行的多类型随机用户出行决策模型,证明了模型的一阶条件满足路径选择、方式选择、讫点选择及是否出行的条件,最后给出模型算法.     

Doubly uncertain transportation network: Degradable capacity and stochastic demand

This study developed a methodology to model doubly uncertain transportation network with stochastic link capacity degradation and stochastic demand. We consider that the total travel demand comprises of two parts, infrequent travelers and commuters. The traffic volume of infrequent travelers is stochastic, which adds to the network traffic in a random manner based on fixed route choice proportions. On the other hand, the traffic volume of commuters is stable or deterministic. Commuters acquire the network travel time variability from past experiences, factor them into their route choice considerations, and settle into a long-term habitual route choice equilibrium in which they have no incentive of switching away. To define this equilibrium, we introduce the notion of “travel time budget” to relate commuters’ risk aversion on route choices in the presence of travel time variability. The travel time budget varies among commuters according to their degrees of risk aversion and requirements on punctual arrivals. We then developed a mixed-equilibrium formulation to capture these stochastic considerations and illustrated its properties through some numerical studies.     

Macroscopic attraction-based simulation of pedestrian mobility: A dynamic individual route-choice approach

This paper presents a dynamic distribution and assignment simulation model based on discrete time simulation techniques and dynamic route assignment for planning, engineering design, and operation analysis of big exhibition events from a pedestrian circulation perspective. Both, the distribution and assignment stages are incorporated in an interlaced way with a dynamic behavior along a specific time horizon. In the proposed model, the individual route choice is dynamically determined as consequence of facilities attractiveness and network congestion. Therefore, in contrast with other simulation approaches, it does not require the usual origin–destination trip matrices to describe the transportation demand or the specification of different paths to be followed by visitors. This modeling approach turns out to be very appropriate for the simulation of these big exhibition events where each visitor usually has multiple and a priori unordered destination choices after entering the scenario.     

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.     

Ranking paths in stochastic time-dependent networks

In this paper we address optimal routing problems in networks where travel times are both stochastic and time-dependent. In these networks, the best route choice is not necessarily a path, but rather a time-adaptive strategy that assigns successors to nodes as a function of time. Nevertheless, in some particular cases an origin–destination path must be chosen a priori, since time-adaptive choices are not allowed. Unfortunately, finding the a priori shortest path is an NP-hard problem.     

考虑路网可靠性和空间公平性的次优拥挤收费模型

根据随机路网环境下出行者规避风险的路径选择行为,提出了一种考虑路网可靠性和空间公平性的次优拥挤收费双层规划模型。其中,上层模型以具有空间公平性约束条件下最大化路网的社会福利为目标,下层模型是实施拥挤收费条件下考虑行程时间可靠性的弹性需求用户平衡模型。鉴于双层规划模型的复杂性,设计了基于遗传算法和FrankWolfe算法的组合式算法来求解提出的模型。算例结果表明:考虑行程时间可靠性的次优拥挤收费会产生不同于传统次优拥挤收费的平衡流量分布模式,表明出行者的路径选择行为对拥挤收费结果会产生直接影响;此外,算例结果还说明遗传算法对参数设置具有很强的鲁棒性。     

多方式弹性需求下公交定价双层规划模型

为描述多方式城市交通网络下公交定价与出行选择行为的相互作用与影响,将出行方式选择与路径选择涵盖于同一网络,建立了上层模型分别以企业利润最大化、乘客出行成本最小化和社会福利最大化为目标函数,下层模型为多方式弹性需求随机用户配流模型的公交定价双层规划模型。运用改进遗传算法对模型整体进行求解,下层模型采用综合对角化算法和MSA算法的组合求解算法。最后,设计了一个算例以说明模型应用。结果表明:运用双层规划模型所确定的公交票价较传统静态票价可使政府、企业及出行者三方都获得更高收益,且上层模型以社会福利最大化为目标函数能代表社会群体中多数人利益,优化效果最为理想。     

基于畅通可靠性的开放小区交通流分配及优化决策

开放小区内部道路可增加城市道路网的密度和可达性,从而达到缓解城市道路拥堵的目的。通过对出行者进行问卷调查,得知其路径选择行为主要考虑出行时间及时间波动性两方面因素,基于此对CONTRAM费用函数进行改进,得到适用于小区开放后的广义出行费用,该费用考虑了畅通可靠性对路径选择的影响;结合小区开放后出行者选择准则,建立考虑广义出行费用的随机用户最优模型(SUO),并采用逐次平均算法(MSA)进行求解,从而得到更为精确的路段交通流量;基于小区道路开放后需承担的交通量,结合城市道路规划相关规范,对横断面、出入口等方面提出开放小区内部道路规划的建议。     

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.     

Dynamic capacitated user-optimal departure time/route choice problem with time-window

A discrete-time predictive dynamic user-optimal departure time/route choice problem has been formulated and solved with the nested diagonalization method by Chen, H.K., Hsueh, C.F. (1998a. A discrete-time dynamic user-optimal departure time/route choice model. Transportation Engineering, ASCE 124 (3), 246–254). That model did not impose constraints on either departure times at origin or arrival times at destination, which are typically required for regular work trips. However, for better representing practical situations, the time-window constraints associated with both the departure times and arrival times, along with link capacity side constraints, need to be incorporated into the aforementioned model. The resulting dynamic capacitated user-optimal departure time/route choice model with time-window can appropriately model the queuing delay associated with each capacitated time–space link and also can properly differentiate off-peak and peak phenomena within the analysis period. A numerical example is provided for demonstration.     

基于网络等级特征与VMS的交叉巢式Logit模型

基于等级特征与可变信息板(VMS)研究了交叉巢式Logit(CNL)模型及网络交通流分配。综合幂函数与指数函数表示方法给出新的信息效用衰减因子,结合道路等级特征表示VMS对车流的影响系数及CNL模型的分配系数;给出等级结构道路网络的随机用户均衡条件下的交叉巢式Logit路径选择模型及其等价数学规划,并设计网络流分配算法。通过实例网络的计算与分析,得到一些有意义的结论:等级结构越显著的路网总出行时间费用越低且其分散参数(θ)弹性绝对值越大;对具有较强随机性的实际路网,若增加一定的确定性则节省更多网络总出行时间;道路网络中设置了VMS时总出行时间受分散参数的影响更小。     

Incorporating transfer reliability into equilibrium analysis of railway passenger flow

Passenger’s transfer route choice behavior is one of the prominent research topics in the field of railway transportation. Existing traffic assignment approaches do not properly account for passenger’s expectation for transfer reliability. In this study, the transfer reliability is explicitly defined and a multi-class user equilibrium model is established, given which passengers choose the minimal-cost path based on their expected reliability thresholds. In particular, a path-based traffic assignment algorithm which combines a k-shortest path algorithm and the method of successive averages is proposed. The validity of the proposed approach is verified by an illustrative example. Using the proposed modeling approach, it is possible to determine the passenger’s collective route choice behavior based on the user equilibrium pattern. Moreover, the railway timetables can be evaluated and optimized based on the cost-based level of service estimation.     

Stochastic equilibrium assignment with variable demand: Theoretical and implementation issues

Recently, it has been pointed out that transport models should reflect all significant traveler choice behavior. In particular, trip generation, trip distribution, modal split as well as route choice should be modeled in a consistent process based on the equilibrium between transport supply and travel demand. In this paper a general fixed-point approach that allows dealing with multi-user stochastic equilibrium assignment with variable demand is presented. The main focus was on investigating the effectiveness of internal and external approaches and of different algorithmic specifications based on the method of successive averages within the internal approach. The vector demand function was assumed non-separable, non-symmetric cost functions were adopted and implementation issues, such updating step and convergence criterion, were investigated. In particular the aim was threefold: (i) compare the internal and the external approaches; (ii) investigate the effectiveness of different algorithmic specifications to solve the variable demand equilibrium assignment problem through the internal approach; (iii) investigate the incidence of the number of the links with non-separable and/or asymmetrical cost functions. The proposed analyses were carried out with respect to two real-scale urban networks regarding medium-size urban contexts in Italy.     

A framework for solving network revenue management problems with customer choice behavior

Revenue management is the process of understanding, anticipating and influencing consumer behavior in order to maximize revenue. Network revenue management models attempt to maximize revenue when customers buy bundles of multiple resources. The dependence among the resources in such cases is created by customer demand. Network revenue management can be formulated as a stochastic dynamic programming problem whose exact solution is computationally intractable. Solutions are based on approximations of various types. Customer choice behavior modeling has been gaining increasing attention in the revenue management. A framework for solving network revenue management problems with customer choice behavior is proposed. The modeling and solving framework is composed from three inter-related network structures: basic network model, Petri net, and neural net.     

双模式网络停车限制交通需求管理模型与方法研究

在轨道网和公路网并存的双模式交通网络, 合理设计出行终点的停车容量可优化汽车出行需求, 改善路网交通环境。本文通过分析私家车与城市轨道两种交通模式的出行需求, 并考虑私家车模式的终点停车收费服务, 建立了一种带路段环境容量和终点停车需求容量共同约束的交通需求管理模型。模型中路网使用者的出行模式采用二元Logit模型来计算, 而私家车的路线选择行为服从Logit随机用户均衡, 因此该模型是一个带不动点约束的数学规划问题。针对模型求解困难, 文中采用灵敏度分析来获取各路段流量和需求量关于终点容量波动的梯度信息, 进而设计了一种新的灵敏度分析求解算法.最后通过数值仿真实验, 验证了算法的有效性, 同时分析了不同停车收费参数对模型各指标变化趋势的影响。     

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.     

Congested network flows: Time-varying demands and start-time policies

This paper is concerned with modeling departure-time and arrival-time policies for flows on a congested network with time-varying demands. In particular, we are concerned with variation over a peak period, and for application we focus on modeling the morning rush-hour (the journey to work). We treat this as a multiple-origin, single-destination network model, the destination being the central business district. We use a system optimizing model, and allow the travel demands to vary with the cost (or price) of making a trip. The tradeoff between travel time and the cost of being early or late is considered for different work-start time policies, such as fixed work-start time and flex-time. For illustration, we apply the model to a simple network example and compare the congestion patterns and travel costs under each policy.     

Transit passenger origin-destination estimation in congested transit networks with elastic line frequencies

This paper deals with the transit passenger origin-destination (O-D) estimation problem by using updated passenger counts in congested transit networks and outdated prior O-D matrix. A bilevel programming approach is extended for the transit passenger O-D updating problem where the upper-level problem seeks to minimize the sum of error measurements in passenger counts and O-D matrices, while the lower level is the stochastic user equilibrium assignment problem for congested transit networks. The transit assignment framework is based on a frequency-adaptive transit network model in this paper, which can help determine transit line frequencies and the network flow pattern simultaneously in congested transit networks. A heuristic solution algorithm is adapted for solving the transit passenger O-D estimation problem. Finally, a numerical example is used to illustrate the applications of the proposed model and solution algorithm. The work described in this paper was mainly supported by two research grants from the Research Grants Council of the Hong Kong Special Administrative Region (Project No. PolyU 5143/03E and PolyU 5040/02E).