基于多维网络的增开列车条件下高速铁路列车运行图调整

研究增开列车条件下高速铁路列车运行图的调整问题,并综合考虑列车车站进路的影响。通过构建Time-Station-Track三维时空扩展网络,刻画列车对铁路时空资源的占用。将原多目标优化问题转化为求解列车占用网络弧段最小费用单目标问题,并构建基于Time-Station-Track网络的0-1整数规划模型。针对模型特点,设计拉格朗日松弛算法,将问题进一步分解为求解单列车网络最短路径子问题,由于问题被松弛后求得的解可能不可行。因此,提出基于列车优先序列的启发式策略对对偶解进行可行化。最后以宝兰客运专线为例,验证模型的正确性和算法的可行性。     

A flexible traffic stream model and its three representations of traffic flow

To connect microscopic driving behaviors with the macro-correspondence (i.e., the fundamental diagram), this study proposes a flexible traffic stream model, which is derived from a novel car-following model under steady-state conditions. Its four driving behavior-related parameters, i.e., reaction time, calmness parameter, speed- and spacing-related sensitivities, have an apparent effect in shaping the fundamental diagram. Its boundary conditions and homogenous case are also analyzed in detail and compared with other two models (i.e., Longitudinal Control Model and Intelligent Driver Model). Especially, these model formulations and properties under Lagrangian coordinates provide a new perspective to revisit the traffic flow and complement with those under Eulerian coordinate. One calibration methodology that incorporates the monkey algorithm with dynamic adaptation is employed to calibrate this model, based on real-field data from a wide range of locations. Results show that this model exhibits the well flexibility to fit these traffic data and performs better than other nine models. Finally, a concrete example of transportation application is designed, in which the impact of three critical parameters on vehicle trajectories and shock waves with three representations (i.e., respectively defined in x-t, n-t and x-n coordinates) is tested, and macro- and micro-solutions on shock waves well agree with each other. In summary, this traffic stream model with the advantages of flexibility and efficiency has the good potential in level of service analysis and transportation planning.     

汽车雨水管理的数值仿真与评价

汽车在雨天行驶时,落到侧窗表面的雨水会影响驾驶员的侧向视野和后视野,从而危及行车安全,故侧窗雨水管理对于整车安全非常重要。但迄今为止对于侧窗雨水管理问题尚未有一个统一而有效的评价方法。为此,本文中应用液膜模型和拉格朗日粒子模型对某款SUV进行了雨水仿真,基于人机工程学和粒子束轨迹技术提出了侧窗雨水管理的评价方法,并对仿真结果进行了相应的分析。     

Lagrangian flow in the California Undercurrent, an observation and model comparison

During the period 1992–1998, 38 isobaric RAFOS floats were deployed to sample the subsurface flow of the California Undercurrent. The deployments, released over the California continental slope west of San Francisco, have sampled robust year-round poleward subsurface flow associated with the Undercurrent most seasons and the combined inshore current and Undercurrent in winter. Two other types of flow have been seen: a region of weak flow with little net displacement just west of the California Undercurrent, and an active westward propagating eddy field. This eddy field appears to be the primary mechanism for moving floats from the Undercurrent into the ocean interior. The observations and statistics from the RAFOS floats are compared with Lagrangian estimates of particles tracked in a global high resolution ocean simulation in order to evaluate the fidelity of the model along an eastern boundary. The results show that the model reproduces the general character of the flow reasonably well, but underestimates both the mean and eddy energies by a substantial amount.     

基于CFD的船舶货舱通风数值模拟

以某集装箱船的货舱通风系统为研究对象,根据船舶舱室的通风系统的特点,采用合理的数值模拟方法,并利用拉格朗日粒子示踪的方法描述舱室中的气体流动状况.在此基础上,分析比较3种不同的通风设计方案,通过对比分析研究送风管上开孔朝向和数目对通风效果的影响,确定对通风最有利的方案.模拟结果表明,应用CFD技术进行通风系统分析,可以很好地从流场的分布特性以及空气粒子的运动追踪等方面来评估设计方案的优劣,为通风系统的设计、优化提供有力的工具.     

基于拉格朗日松弛的高速铁路列车运行图新增运行线局部调整模型

给定新增列车理想始发时刻及初始利润,考虑始发时刻调整及全程停时延长造成的罚数,基于时空网络构建以全图运行线总利润最大为目标的整数规划模型,进行拉格朗日松弛,根据松弛解对偶信息设计启发式算法求解各运行线可行解,并通过更新拉格朗日乘子进行迭代优化.以京沪高铁为例进行了验证,结果表明：在算例条件下,相较以理想始发时刻推线求解,该方法能够多增铺6条运行线;随着始发时刻可调整度由10min增加至60min,CPLEX的求解时间快速增长,而拉格朗日松弛启发式算法能快速求得高质量的解,除始发时刻可调整度10min情景,求解效率均高于CPLEX;延长始发时刻可调整度至4h,最多增铺18条运行线,说明现有框架下京沪高铁能力已接近饱和.     

Reliable sensor deployment for network traffic surveillance

New sensor technologies enable synthesis of disaggregated vehicle information from multiple locations. This paper proposes a reliable facility location model to optimize traffic surveillance benefit from synthesized sensor pairs (e.g., for travel time estimation) in addition to individual sensor flow coverage (e.g., for traffic volume statistics), while considering probabilistic sensor failures. Customized greedy and Lagrangian relaxation algorithms are proposed to solve this problem, and their performance is discussed. Numerical results show that the proposed algorithms solve the problem efficiently. We also discuss managerial insights on how optimal sensor deployment and surveillance benefits vary with surveillance objective and system parameters (such as sensor failure probabilities).     

基于接触问题的桩土相互作用机理

采用子结构凝聚自由度法推导出桩土接触问题的非线性有限元平衡方程,引入接触问题的约束条件,并通过增广拉格朗日乘子法对约束条件进行处理,得到数值计算的迭代格式,进而对桩土相互作用进行非线性数值计算,结果表 明：数值计算结果与实测结果吻合较好,接触问题的引入可以合理地解释桩土相互作用的机理问题。     

Scheduling of Intelligent and Autonomous Vehicles under pairing/unpairing collaboration strategy in container terminals

A new class of Intelligent and Autonomous Vehicles (IAVs) has been designed in the framework of Intelligent Transportation for Dynamic Environment (InTraDE) project funded by European Union. This type of vehicles is technologically superior to the existing Automated Guided Vehicles (AGVs), in many respects. They offer more flexibility and intelligence in maneuvering within confined spaces where the logistic operations take place. This includes the ability of pairing/unpairing enabling a pair of 1-TEU (20-foot Equivalent Unit) IAVs dynamically to join, transport containers of any size between 1-TEU and 1-FFE (40-foot Equivalent) and disjoin again. Deploying IAVs helps port operators to remain efficient in coping with the ever increasing volume of container traffic at ports and eliminate the need for deploying more 40-ft transporters in the very confined area of ports. In order to accommodate this new feature of IAVs, we review and extend one of the existing mixed integer programming models of AGV scheduling in order to minimize the makespan of operations for transporting a set of containers of different sizes between quay cranes and yard cranes. In particular, we study the case of Dublin Ferryport Terminal. In order to deal with the complexity of the scheduling model, we develop a Lagrangian relaxation-based decomposition approach equipped with a variable fixing procedure and a primal heuristics to obtain high-quality solution of instances of the problem.     

Activity patterns in space and time: calculating representative Hagerstrand trajectories

Daily activity diaries can be recorded as sequences of characters representing events and their contexts as they unfold during the day. Dynamic programming algorithms as used in bioinformatics have been used by a number of researchers to measure the similarities and differences between travel patterns on the basis of temporal sequencing of events, activity transition, and total activity time. The resultant similarity matrices have been shown to be more effective in classifying sequential patterns than classifications based on alternative similarity indices. The basic algorithms can be amended to include the geographic coordinates of events by a suitable amendment to the definition of distance. This permits quantitative classification of Hagerstrand-type activity trajectories on the basis of both activity and spatial similarity. Such a classification can be used to group similar trajectories and to identify representative trajectories that are analogous to measures of central tendency in univariate statistics, giving more concrete meaning to the concept of the activity pattern than any other method now available. The paper illustrates the effect of considering both events and locations in the classification of daily activity patterns using activity diary data gathered in the town of Reading. The algorithm has been implemented in the Clustal_TXY alignment software package.