A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand

This paper presents a novel reliability-based stochastic user equilibrium traffic assignment model in view of the day-to-day demand fluctuations for multi-class transportation networks. In the model, each class of travelers has a different safety margin for on-time arrival in response to the stochastic travel times raised from demand variations. Travelers' perception errors on travel time are also considered in the model. This model is formulated as an equivalent variational inequality problem, which is solved by the proposed heuristic solution algorithm. Numerical examples are presented to illustrate the applications of the proposed model and the efficiency of solution algorithm.     

Foundations of Dynamic Traffic Assignment: The Past,the Present and the Future

Dynamic Traffic Assignment (DTA) has evolved substantially since the pioneering work of Merchant and Nemhauser. Numerous formulations and solutions approaches have been introduced ranging from mathematical programming, to variational inequality, optimal control, and simulation-based. The aim of this special issue is to document the main existing DTA approaches for future reference. This opening paper will summarize the current understanding of DTA, review the existing literature, make the connection to the approaches presented in this special issue, and attempt to hypothesize about the future.     

我国智能交通控制系统的发展及展望

城市交通问题已经成为现代社会尤其是城市社会面临的最大课题之一。文中阐述了国内外智能交通控制系统的发展现状,重点阐述了我国未来智能交通控制的发展模式,并对这种发展模式的内容、控制方法、特点等进行了较为详细的介绍。     

Modeling of optimal control for urban freeway corridor under incident conditions

Traffic control and management are effective measures to solve the problem of traffic congestion. The optimal control model for freeway corridor is developed under incident conditions, which is in the form of minimization of the sum of the square of the difference between traffic demand and capacity at each intersection and on the freeway bottleneck section. The model optimizes control parameters of phase splits at arterial intersections, off-ramp diversion rates at upstream off-ramps and on-ramp diversion rates at downstream on ramps. Finally, the objective function is discussed and it is showed that the optimal control model is simple and practical.     

A Decomposition Scheme for System Optimal Dynamic Traffic Assignment Models

In this paper, a Dantzig-Wolfe decomposition based solution algorithm is developed for the linear programming formulation introduced by Ziliaskopoulos (2000) for System Optimal Dynamic Traffic Assignment problem. The algorithm takes advantage of the network structure in the constraint set of the formulation: the sub-problem is formulated as a minimum-cost-flow problem and the master as a simpler linear programming problem, which allows DTA to be solved more efficiently on meaningful networks. The algorithm is tested on an example network and its performance is analyzed.     

A systolic parallel simulation system for dynamic traffic assignment: SPSS-DTA

This paper presents a new approach to solve dynamic traffic assignment problems. The approach employs a mixed method of real-time simulation and off-line optimization. The fundamental approach to the simulation is systolic parallel processing based on autonomous agent modeling. Agents continuously act on their own initiatives and access to database to get the status of the simulation world. In particular, existing models and algorithms were incorporated in designing the behavior of relevant agents such as car-following and headway distribution. Simulation is based on predetermined routes between centroids that are computed off-line by a conventional optimal path-finding algorithm such as the Frank-Wolf algorithm. Iterating the cycles of optimization and simulation, the proposed system will provide a practical and valuable traffic assignment. Gangnam-Gu district in Seoul, Korea is selected as the target area for the modeling. It is expected that real-time traffic assignment services can be provided on the Internet soon.     

Some Consistency Conditions for Dynamic Traffic Assignment Problems

This paper explores some critical issues in modeling network traffic flow for predictive user optimal dynamic traffic assignment. They include the role of FIFO (first-in-first-out) in link, path and network traffic dynamics, minimal set representation of link traffic evolution, and consistency conditions for link models. It is found that (1) link FIFO plays a central role in modeling link, path and network traffic flow evolution, and (2) the dimension of a minimal state set that adequately describes link traffic flow under FIFO is two. Moreover, two sufficient FIFO conditions are provided, and pitfalls in using these conditions to enforce FIFO are pointed out. Finally, ramifications of these findings to DTA modeling are also discussed.     

Analytical Models of the Dynamic Traffic Assignment Problem

A review of analytical formulations of the dynamic traffic assignment problem is presented, focusing on the authors' experience with variational inequality approaches. Solution algorithms and computational issues requiring additional study are discussed.     

基于极点配置的网络流量控制研究

应用极点配置方法,讨论了根据网络的现实状态将极点配置在不同区域,使链路具有较高的利用率且解决网络拥塞的问题.由于利用前面时刻的信息,提前通知源端网络的使用情况,从而避免了时延对其性能的破坏性影响.此算法不仅保证了网络缓冲器的不溢出及带宽的公平分配和充分利用,而且使信源速率能快速、动态地响应网络状态的变化.仿真结果验证了极点配置算法能使网络具有良好的动态性能.     

Efficient Discretisation for Link Travel Time Models

In the literature, two different models have been used to compute link travel times in dynamic traffic assignment (DTA), and elsewhere we investigated how these are affected by discretising the link length. Here we consider discretising time as well as space (the link length). We vary the discretising of time with spatial discretisation held fixed, and vice versa, and also vary both together. The results show that coordinated discretisation is usually the most efficient in approximating the limit solution (continuous time, continuous space) and, even when it is not the most efficient, it has other advantages. The results have implications for algorithms for DTA and for the choice of discrete versus continuous time models. For example, refining the discretisation of time (without refining it for space) can make the solution less accurate, so that in the widely used whole-link models (i.e. without spatial discretisation) it is more efficient to use the largest feasible time steps, close to the link travel time.     

用于求解路径交通流量的改进Frank-Wolfe算法

Frank-Wolfe算法是用于求解交通流量分配问题的经典算法,但该算法是基于路段（Link-Based）的交通流量分配算法,无法用于求解路径交通流量。针对此问题,提出一种用于求解路径交通量的改进Frank-Wolfe算法。通过在Frank-Wolfe原算法中增加求解路径交通流量的计算步骤,根据原算法中“全有全无”加载方法获得的步长,更新源-目的（OD）间所有已配流的路径的交通流量,在原算法迭代计算路段流量的同时,同步计算路径流量。通过算例表明,改进算法是一个有效的算法,在Frank-Wolfe原算法的基础上增加少量的时间和空间成本即可求解路径交通流量,避免穷举交通网络中的所有路径,可以很好地用于用户均衡交通流量分配中。     

Dynamic Traffic Assignment with More Flexible Modelling within Links

Traffic network models tend to become very large even for medium-size static assignment problems. Adding a time dimension, together with time-varying flows and travel times within links and queues, greatly increases the scale and complexity of the problem. In view of this, to retain tractability in dynamic traffic assignment (DTA) formulations, especially in mathematical programming formulations, additional assumptions are normally introduced. In particular, the time varying flows and travel times within links are formulated as so-called whole-link models. We consider the most commonly used of these whole-link models and some of their limitations.In current whole-link travel-time models, a vehicle's travel time on a link is treated as a function only of the number of vehicles on the link at the moment the vehicle enters. We first relax this by letting a vehicle's travel time depend on the inflow rate when it enters and the outflow rate when it exits. We further relax the dynamic assignment formulation by stating it as a bi-level program, consisting of a network model and a set of link travel time sub-models, one for each link. The former (the network model) takes the link travel times as bounded and assigns flows to links and routes. The latter (the set of link models) does the reverse, that is, takes link inflows as given and finds bounds on link travel times. We solve this combined model by iterating between the network model and link sub-models until a consistent solution is found. This decomposition allows a much wider range of link flow or travel time models to be used. In particular, the link travel time models need not be whole-link models and can be detailed models of flow, speed and density varying along the link. In our numerical examples, algorithms designed to solve this bi-level program converged quickly, but much remains to be done in exploring this approach further. The algorithms for solving the bi-level formulation may be interpreted as traveller learning behaviour, hence as a day-to-day traffic dynamics. Thus, even though in our experiments the algorithms always converged, their behaviour is still of interest even if they cycled rather than converged. Directions for further research are noted. The bi-level model can be extended to handle issues and features similar to those addressed by other DTA models.     

Evacuation Transportation Planning Under Uncertainty: A Robust Optimization Approach

This paper considers evacuation via surface transportation networks in an uncertain environment. We focus on demand uncertainty which can lead to significant infeasibility cost during evacuation, where loss of life or property may appear. We develop a robust linear programming model based on a robust optimization approach where hard constraints are guaranteed within an appropriate uncertainty set. The robust counterpart solutions have been shown tractable. We show that the robustness in evacuation is important and a robust solution outperforms a nominal deterministic solution in both quality and feasibility.     

Continuous and Discrete Trajectory Models for Dynamic Traffic Assignment

A continuous trajectory model is presented in which transportation networks are represented as topological constructs. The general formulation enhances existing analytic dynamic traffic assignment models by incorporating continuous single-link traffic flow models in a general, coherent, and relatively intuitive manner. Specific exact formulation based on a simplified kinematic wave traffic flow model with physical queues is presented as well.A discrete trajectory model is proposed as an approximation of the continuous model. The discrete model provides wide flexibility in choosing the level of aggregation with respect to time intervals, ranging from several hours, as typical in current practice of long-term travel forecasting models, to one second or less, as in microscopic simulations. An algorithm to find discrete approximate solutions is presented as well as accuracy measures to evaluate them. The effect of time resolution on model performance is examined by a numerical example.     

P2P业务流量识别、分析和控制研究

P2P业务流量在对Internet起巨大推动作用的同时,也带来了因资源过度占用而引起的网络拥塞以及安全隐患等问题,妨碍了正常的网络业务的开展。该文通过对P2P业务的有效识别、控制和管理技术的研究,设计出网络业务流量综合识别系统和网络业务流量识别和策略控制系统原型。     

一种基于离散对数和多项式插值的访问控制方案

在这篇文章中,通过对Tzer-Shyong Chen等人和其他访问控制方案的研究,结合方案的实际应用,提出了一种新的层级结构下信息访问控制方案,主要从提高安全性、减少计算量、节省存储空间等方面作为方案设计的主要依据,新方案更加适合现实的应用。对用户类的增加/删除,用户类关系的增加/删除,用户类秘密密钥的变更等动态的存取控制问题也进行了讨论。该方案在实际的应用中更适合用户类对直接下级用户类秘密密钥的获取,同时也提出了对间接下级用户类秘密密钥的获取方式。并且对安全性、计算量和存储等方面进行了分析。     

P2P业务流量识别、分析和控制研究

P2P业务流量在对Internet起巨大推动作用的同时,也带来了因资源过度占用而引起的网络拥塞以及安全隐患等问题,妨碍了正常的网络业务的开展。该文通过对P2P业务的有效识别、控制和管理技术的研究,设计出网络业务流量综合识别系统和网络业务流量识别和策略控制系统原型。