基于入侵野草优化算法的粒子滤波算法

入侵野草优化(IWO)算法是近年来提出的一种简单、有效的基于种群的新颖数值优化算法,在许多领域得到成功运用。将IWO算法与粒子滤波(PF)算法相结合,提出一种基于IWO算法的粒子滤波算法(IWOPF)。该算法将IWO算法运用于粒子滤波的重采样中,以保证粒子的有效性和多样性。最后通过计算仿真验证该算法的有效性和优越性。     

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.     

基于卡尔曼滤波的4WD电动车辆寄生功率的测量技术

根据串励直流电动机工作特性,利用车辆行驶过程中较易测得的驱动电机工作电流及驱动轮转速,运用MATLAB/SIMULINK软件,建立基于卡尔曼滤波的驱动轮滑转率模型和寄生功率模型并进行仿真;通过道路试验对电动机工作电流和驱动轮转速的检测,实时预测驱动轮的滑转率与产生的寄生功率。结果表明,驱动轮滑转率和寄生功率的仿真结果与试验结果非常接近。     

存在车辆干扰的车道线识别

为避免道路上行驶的其它车辆对车道线识别的干扰,提出了一种结合车辆识别的车道线识别方法。融合雷达数据,车辆识别模块首先在图像中识别出车辆占据的区域;对于每一个车道线识别模块挑出的车道线候选点进行判断,去除处于车辆区域的车道线点;如果有效车道线点数目不足,则利用卡尔曼滤波的跟踪结果,确定符合最小风险函数的车道线位置。经过多种工况下的试验验证,该方法能够稳定地对车道线进行识别,准确地提取车道线参数,并且算法对车辆干扰有良好的抵抗能力。     

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。