Robust Principal Component Test in Gross Error Detection and Identification

Principle component analysis (PCA) based chi-square test is more sensitive to subtle gross errors and has greater power to correctly detect gross errors than classical chi-square test. However, classical principal component test (PCT) is non-robust and can be very sensitive to one or more outliers. In this paper, a Huber function liked robust weight factor was added in the collective chi-square test to eliminate the influence of gross errors on the PCT. Meanwhile, robust chi-square test was applied to modified simultaneous estimation of gross error (MSEGE) strategy to detect and identify multiple gross errors. Simulation results show that the proposed robust test can reduce the possibility of type II errors effectively. Adding robust chi-square test into MSEGE does not obviously improve the power of multiple gross error identification, the proposed approach considers the influence of outliers on hypothesis statistic test and is more reasonable.     

Mobile Robot Hierarchical Simultaneous Localization and Mapping Using Monocular Vision

A hierarchical mobile robot simultaneous localization and mapping (SLAM) method that allows us to obtain accurate maps was presented. The local map level is composed of a set of local metric feature maps that are guaranteed to be statistically independent. The global level is a topological graph whose arcs are labeled with the relative location between local maps. An estimation of these relative locations is maintained with local map alignment algorithm, and more accurate estimation is calculated through a global minimization procedure using the loop closure constraint. The local map is built with Rao-Blackwellised particle filter (RBPF), where the particle filter is used to extending the path posterior by sampling new poses. The landmark position estimation and update is implemented through extended Kalman filter (EKF). Monocular vision mounted on the robot tracks the 3D natural point landmarks, which are structured with matching scale invariant feature transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-tree in the time cost of O(lbN). Experiment results on Pioneer mobile robot in a real indoor environment show the superior performance of our proposed method.     

出租车超速行为道路因素随机系数空间模型构建

为准确揭示道路因素与路段出租车超速行为特征的关联关系，本文以成都市中心城区主 干道路段为研究单元，通过车载GPS设备获取大范围出租车超速行为样本。在筛选出10类典型城市道路特征的基础上，选择路段超速线密度和不同百分位数超速严重度作为研究对象；为减少空间效应对估计的干扰，本文验证了超速特征的空间相关性，并分别构建基于对数-高斯分布的标准线性模型和空间条件自回归模型、空间误差模型及空间滞后模型这3类空间模型，探究不同空间模型与出租车超速行为特征的拟合情况；同时，考虑道路组间异质性，进一步构建随机系数空间模型。结果表明：出租车路段超速线密度和超速严重度均存在显著空间自相关性，空间模型 对其拟合效果普遍优于传统模型；不同超速行为特征适用不同的空间模型，随机系数空间条件自回归模型对超速线密度拟合效果最优，而不同百分位数超速严重度适用的最佳拟合模型差异较大；路段限速、一块板横断面及非机动车车道这3类因素表现出对出租车超速行为特征的组间影响异质性；因素解释方面，路段限速、一块板横断面、非机动车车道、路段施工区与超速线密度显著相关；路段限速、非机动车车道、上下坡匝道、路段施工区及路段长度与超速严重度显著相关。     

车-桥耦合振动的联合方程分析方法

根据d'Alembert原理和有限元理论,分别建立了车辆和桥梁的振动方程;基于车辆密贴理论,轮底接触点位移由桥梁节点位移采用形函数插值得到,接触点作用力等效成桥梁单元的结点力代入桥梁振动方程,将车辆、桥梁振动方程组联立形成了车-桥耦合振动的总体振动方程;采用数值积分的Newmark-β法求解方程组。结果表明:此方法和经典的迭代求解方法是吻合的。     

The VOCO multi-body software in the context of real-time simulation

The railway multi-body software developed for more than 20 years by INRETS (now IFSTTAR), under the name VOCO^®, has been dedicated from the origin to highly nonlinear elements, such as the dry friction dampers of freight bogies and the wheel–rail contact based on measured profiles. A second important step has been the discovery of a particular method in order to simulate on sinuous tracks. In the aim of industrial applications, the specification has always been to reach the goal of real time. Although it is not possible in all the cases, the recent non-Hertzian contact development is allowing real-time simulation to be achieved.     

Underwater simultaneous localization and mapping based on forward-looking sonar

A method of underwater simultaneous localization and mapping (SLAM) based on forward-looking sonar was proposed in this paper. Positions of objects were obtained by the forward-looking sonar, and an improved association method based on an ant colony algorithm was introduced to estimate the positions.In order to improve the precision of the positions, the extended Kalman filter (EKF) was adopted. The presented algorithm was tested in a tank, and the maximum estimation error of SLAM gained was 0.25 m. The tests verify that this method can maintain better association efficiency and reduce navigation error.     

A fine discrete field cellular automaton for pedestrian dynamics integrating pedestrian heterogeneity,anisotropy, and time-dependent characteristics

This paper proposes a discrete field cellular automaton (CA) model that integrates pedestrian heterogeneity, anisotropy, and time-dependent characteristics. The pedestrian movement direction, moving/staying, and steering are governed by the transfer equations. Compared with existing studies on fine-discretized CA models, the proposed model is advantageous in terms of flexibility, higher spatial accuracy, wider speed range, relatively low computational cost, and elaborated conflict resolution with synchronous update scheme. Three different application scenarios are created by adjusting the definite conditions of the model: (1) The first one is a unidirectional pedestrian movement in a channel, where a complete jam in the high-density region is observed from the proposed model, which is missing from existing floor field CA models. (2) The second one is evacuation from a room, where the evacuation time is independent of the discretization factor, which is different from previous work. (3) The third one is an ascending evacuation through a 21-storey stair system, where pedestrians move with constant speed or with fatigue. The evacuation time in the latter case is nearly twice of that in the former.     

Examining the effects of the built environment and residential self-selection on commuting trips and the related CO2 emissions: An empirical study in Guangzhou,China

Numerous studies have established the link between the built environment and travel behavior. However, fewer studies have focused on environmental costs of travel (such as CO₂ emissions) with respect to residential self-selection. Combined with the application of TIQS (Travel Intelligent Query System), this study develops a structural equations model (SEM) to examine the effects of the built environment and residential self-selection on commuting trips and their related CO₂ emissions using data from 2015 in Guangzhou, China. The results demonstrate that the effect of residential self-selection also exists in Chinese cities, influencing residents’ choice of living environments and ultimately affecting their commute trip CO₂ emissions. After controlling for the effect of residential self-selection, built environment variables still have significant effects on CO₂ emissions from commuting although some are indirect effects that work through mediating variables (car ownership and commuting trip distance). Specifically, CO₂ emissions are negatively affected by land-use mix, residential density, metro station density and road network density. Conversely, bus stop density, distance to city centers and parking availability near the workplace have positive effects on CO₂ emissions. To promote low carbon travel, intervention on the built environment would be effective and necessary.     

迟滞相频特性方法测量方程的一种改进

迟滞相频特性方法经典测量方程由于忽略了测量系统动质量、力传感器刚度及系统支撑刚度的影响,而给阻尼材料动态力学参数测量引入了误差。首先,以试件拉压安装方式为例,推导了考虑上述三方面因素影响的改进测量方程;然后,分别利用经典和改进测量方程对基于某系统获得的测量数据进行了处理,通过对比分析两种方程获得的材料参数,研究了上述因素对阻尼材料动态力学参数测量结果的影响规律。研究成果为迟滞相频特性方法测量系统优化设计及测量数据处理提供了依据。     

基于指数-兰彻斯特方程的岛礁作战效能评估

通过建立指数-兰彻斯特方程模型对海军陆战队兵力夺控珊瑚岛礁兵力编组的作战效能进行评估,分析各战斗阶段的兵力损耗,检验作战方案实施的效果,为优化兵力编组和完善作战方案提供依据.