道路交通量分配建模综述

在道路规划和设计过程中,交通量的预测一般都采用四阶段法。在众多研究者的共同努力下,交通量的分配是研究最为成熟的一个阶段。人们根据不同的交通行为的假设,选择不同的交通抗阻和离散选择模型,推出了不同的交通分配模型,例如全有全无分配模型、按比例分配模型、均衡分配模型等。该文在前人研究的基础上,对不同的交通分配模型进行分析,根据它们不同的机理,阐明了不同分配模型的应用条件。     

沥青搅拌设备骨料称量控制的研究

介绍了沥青搅拌设备骨料称量系统的结构和工作原理,结合实际工程分析知骨料称量系统的称量误差来自静态误差和动态误差,提出了通过控制放料门开度、冲击力和空中“飞料”量来提高沥青搅拌设备骨料称量精度,满足道路施工的需求的措施。     

涡流探伤中数据的实时采集和实时处理

在充分利用采集卡内部缓存的基础上,利用定时器控件进行数据的实时采集显示,实时参数计算和在线存盘,从而避免了利用VB进行析多线程编程。同时介绍了利用窗体的实例来实现多段数据的暂时存储方法。     

出行时间不确定下的公交均衡配流

很多外在因素致使公交出行时间具有高度的不确定性,而已有的公交配流模型对公交车辆运行时间和乘客等车时间的不确定性缺乏考虑．本文综合考虑公交出行时问和出行时间的不确定性,结合公交出行时间与公交出行时间可靠性以描述乘客的路径选择行为,建立公交乘客均衡配流模型并求解分析。案例结果表明换乘线路增加了出行时间的不确定性,人们更愿意...     

基于衰减因子的时变增益KALMAN滤波

常用的卡尔曼滤波器(KF,EKF)一般只适用于平稳的状态过程,当目标处于变化不大的过程时,目标状态突然变化时,KF和EKF将产生较大的估计偏差,甚至丢失目标.文中根据正交性原理,采用时变衰减因子,使得残差达到正交或近似正交,从而使滤波器在不确定模型下保持较好的鲁棒性.通过实时调节增益,促使测量残差近似正交,从而提高对机动目标的跟踪性能.仿真实验表明,应用该方法可以快速、稳定地完成目标运动要素的估计.     

基于公交GPS和IC卡数据的综合交通建模新思路

为给我国交通规划模型的研究和开发提供新的方向和思路,结合郑州市综合交通模型的开发实践,探讨了公交GPS和IC卡数据在其中的应用.主要包括:基于公交GPS和IC卡数据的公交OD生成方法、公交客流量模型、非集计模型与动态公交分配模型以及基于公交GPS数据的需求预测组合模型.重点阐述了公交GPS和IC卡数据在上述几个方面的应...     

城市交通疏散救援的元胞自动机模型

分析了城市内部各向车流冲突造成的车辆延误对疏散与救援决策的影响, 将交叉口控制参数引入到现有的基于元胞传输模型的应急疏散救援仿真模型中, 建立灾时交叉口紧急控制下的应急疏散救援仿真模型。改进后的模型以规划周期内疏散与救援加权行程时间最小为目标, 并引入反流策略。仿真结果表明: 由于低优先级的车流G1和G2让行高优先级车流G3和G4而产生延误, 其平均行程时间分别增加了10.0、11.1 s, 符合城市内部疏散与救援的实际情况; 反流策略实施后, 受益的车流G2和G4行程时间分别下降了6.5、6.0 s。可见, 提出的模型及反流策略有效。     

优化空车调配问题

首先阐述了车站空车调配问题对编制车站日班工作计划的意义，通过利用卸后空车对配空车问题进行优化研究，给出配空车问题的数学模型。     

Optimisation and heuristic approaches for assigning inbound containers to outbound carriers

Due to economical and/or geographical constraints, most of the time overseas containers cannot be directly shipped to their destinations. These containers visit transhipment ports where they are first unloaded and temporarily stored and then loaded onto smaller vessels (feeders) to be transported to their final destinations. The assignment of these containers to outbound vessels necessitates several factors to be taken into account simultaneously. In this paper, we develop a mathematical model to reflect multiple objectives with priorities and to assign these containers to different vessels at the transit container port terminal. Although we solve a single-objective (with the weighted sum of objectives) mathematical model to optimality, we also propose two heuristic approaches to solve this complex problem for a transit agency. The first heuristic is shipment based and has four variants differing in how the opportunity costs of the assignments are calculated. The second greedy heuristic is trip based, where the goal is to maximise the capacity utilisation of the vessels. The heuristics return very promising solutions in ignorable computational times. We also provide real-life cases and present our conclusions.     

A family of macroscopic node models

The family of macroscopic node models which comply to a set of basic requirements is presented and analysed. Such models are required in macro-, mesoscopic traffic flow models, including dynamic network loading models for dynamic traffic assignment. Based on the behaviour of drivers approaching and passing through intersections, the model family is presented. The headway and the turn delay of vehicles are key variables. Having demand and supply as input creates a natural connection to macroscopic link models. Properties like the invariance principle and the conservation of turning fractions are satisfied. The inherent non-uniqueness is analysed by providing the complete set of feasible solutions. The node models proposed by Tampère et al. (2011), Flötteröd and Rohde (2011) and Gibb (2011) are members of the family. Furthermore, two new models are added to the family. Solution methods for all family members are presented, as well as a qualitative and quantitative comparison. Finally, an outlook for the future development of empirically verified models is given.