Quasi-dynamic estimation of o–d flows from traffic counts: Formulation,statistical validation and performance analysis on real data

The paper proposes a “quasi-dynamic” framework for estimation of origin–destination (o–d) flow from traffic counts, under the assumption that o–d shares are constant across a reference period, whilst total flows leaving each origin vary for each sub-period within the reference period. The advantage of this approach over conventional within-day dynamic estimators is that of reducing drastically the number of unknowns given the same set of observed time-varying traffic counts. Obviously, the gain in accuracy depends on how realistic is the underlying assumption that total demand levels vary more rapidly over time than o–d shares. Firstly, the paper proposes a theoretical specification of the quasi-dynamic estimator. Subsequently, it proposes empirical and statistical tests to check the quasi-dynamic assumption and then compares the performances of the quasi-dynamic estimator of o–d flows with both classical off-line simultaneous dynamic estimators and on-line recursive Kalman filter-based estimators. Experiments are carried out on the real test site of A4–A23 motorways in North-Eastern Italy. Results confirm the acceptability of the assumption of quasi-dynamic o–d flows, even under the hypothesis of constant distribution shares for the whole day and show that the quasi-dynamic estimator outperforms significantly the simultaneous estimator. Data also suggest that using the quasi-dynamic estimates instead of the simultaneous estimates as historical o–d flows improves significantly the performances of the Kalman filter, which strongly depends of the quality of the seed o–d flows. In addition, it is shown that the aggregation of quasi-dynamic o–d estimates across subsequent time slices represents also the most effective way to obtain o–d estimates for larger time horizons (e.g. hourly estimates). Finally, a validation based on an hold-out sample of link flows (i.e. counts not used as inputs in the o–d estimation/updating process) revealed the quasi-dynamic estimator to be overall more robust and effective with respect to the other tested estimators.     

Dual extended Kalman filter for vehicle state and parameter estimation

The article demonstrates the implementation of a model-based vehicle estimator, which can be used for combined estimation of vehicle states and parameters. The estimator is realised using the dual extended Kalman filter (DEKF) technique, which makes use of two Kalman filters running in parallel, thus 'splitting' the state and parameter estimation problems. Note that the two problems cannot be entirely separated due to their inherent interdependencies. This technique provides several advantages, such as the possibility to switch off the parameter estimator, once a sufficiently good set of estimates has been obtained. The estimator is based on a four-wheel vehicle model with four degrees of freedom, which accommodates the dominant modes only, and is designed to make use of several interchangeable tyre models. The paper demonstrates the appropriateness of the DEKF. Results to date indicate that this is an effective approach, which is considered to be of potential benefit to the automotive industry.     

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.     

机车车辆用新型空气过滤器概述

对机车车辆用传统空气过滤器存在的问题进行分析,介绍一种适合机车车辆用新型空气过滤器的结构特点、过滤原理、主要性能及试验情况等。     

Efficient multiple model particle filtering for joint traffic state estimation and incident detection

This article proposes an efficient multiple model particle filter (EMMPF) to solve the problems of traffic state estimation and incident detection, which requires significantly less computation time compared to existing multiple model nonlinear filters. To incorporate the on ramps and off ramps on the highway, junction solvers for a traffic flow model with incident dynamics are developed. The effectiveness of the proposed EMMPF is assessed using a benchmark hybrid state estimation problem, and using synthetic traffic data generated by a micro-simulation software. Then, the traffic estimation framework is implemented using field data collected on Interstate 880 in California. The results show the EMMPF is capable of estimating the traffic state and detecting incidents and requires an order of magnitude less computation time compared to existing algorithms, especially when the hybrid system has a large number of rare models.     

关于剩余格的正则滤子

基于一般的剩余格,引进了正则滤子的概念,给出了正则滤子的一些特征刻画,并且建立了正则滤子与其它一些特殊滤子(G-滤子、MV-滤子、Boolean滤子)之间的内在联系.证明了一个剩余格为正则剩余格当且仅当它的每个MP滤子是正则滤子.     

低路基桥涵优化设计

对濮阳至信阳高速公路濮阳段路基高改低设计中桥涵设计要点加以简述．并通过增设天桥和下挖通道降低路基填土高度，解决由此引起的通道积水问题，从而实现了降低路基高度的设计目标。     

地铁转向架构架动应力测试滤波频率的确定

文章结合上海地铁某转向架线路试验动应力测试结果,分析了典型信号的频率特性,对转向架动应力数据采用不同频率滤波,对滤波后的信号数据进行了比较,并结合采样定理提出了适用于地铁转向架荷载测试的滤波和采样频率。     

不同渗透系数地层中泥浆渗透成膜试验研究

为了改善泥浆在高渗透性地层中难以成膜的问题,给泥水盾构工程中泥浆的配制提供参考,针对膨润土泥浆在砂土地层中渗透成膜的过程,以某高铁隧道砂卵石地层中泥水盾构施工为背景,开展了泥浆在不同渗透系数地层中的成膜试验。试验采用自行设计的内径为300 mm的泥浆渗透装置,利用分级加压的方式使泥浆压力转化为地层的有效支护压力,分析了地层渗透系数、泥皮厚度、泥浆滤失量三者的关系以及成膜的判断方法。研究结果表明:泥皮厚度随着地层渗透系数的变大表现为先增大后减小,而泥浆滤失量随之不断增大,在泥皮厚度增大阶段厚度与滤失量成正相关,在泥皮厚度减小阶段厚度与滤失量成负相关,泥皮厚度最大值点是泥浆渗透有效成膜的转折点;过泥皮厚度最大值点的k线可为泥浆适应性判断提供参考,k线左侧是泥浆渗透成膜的稳定区域,而在k线右侧区域,泥浆颗粒的消耗量与滞留量呈负相关,泥浆的适应性较差;采用D₁₅/d₈₅的值能大致地划分泥浆的渗透成膜类型,D₁₅/d₈₅在10附近是成膜是否有效的过渡区,该区域对应k线右侧临近区域,泥浆渗透可以形成泥皮,但稳定性较差,故泥皮不能作为有效泥膜形成的标志;增大泥浆中颗粒的粒径能提高泥浆的成膜能力,使泥浆k线向右移动,能有效解决泥浆在高渗透性地层中成膜难的问题。     

基于多电平变频器的有源电力滤波器

含独立电源的级联H桥多电平变频器具有每个H桥单元结构相同、易于实现模块化设计等优点，因而在无功补偿和有源电力滤波器等领域有广泛的应用前景。在并联有源电力滤波器（APF）系统中，由于直流侧不需要提供有功功率，可充分利用级联多电平变频器的优势及载波相移PWM技术良好的谐波传输特性。提出了一种基于多电平变流器的并联APF系统的电路拓扑结构，并在交直流控制策略和系统参数设计方面进行了分析。仿真和实验结果表明，此系统动态响应速度快、补偿性能良好，验证了理论分析的正确性和实验系统的可行性。