基于线性叠加的智能船舶经济性评估模型构建

经济性是智能船舶能否实现推广应用的关键,目前国内外有关智能船舶经济性分析的研究较少。本文通过对传统船舶经济性分析方法进行修正优化,提出智能船舶经济性分析计算模型,并根据理论推导结果,得出智能船舶经济性分析的线性叠加简化模型,并利用40万吨级VLOC实际运营数据进行科学性检验。本文提出的模型与方法适用于各类智能模块加装情况下的经济性核算,为相关单位开展智能船舶经济性快速分析提供了理论支持和解决方案。     

面向新型混合交通流的智能交叉口网络布局优化

考虑网联自动驾驶车辆(Connected Autonomous Vehicle, CAV)应用先进的车联网与自动驾驶技术，可以采用智能交叉口的组织形式，大幅提升交叉口的通行效率，为降低CAV与人工驾驶车辆(Human-driven Vehicle, HV)混行条件下城市交通系统的整体出行成本，提出智能交叉口在城 市交通网络中的布局优化问题，建立数学优化模型并求解。首先，基于对两类车辆行驶特性的分析，建立混合用户均衡模型，描述CAV与HV的路径选择行为；其次，从交通规划者的角度，以系统最优为目标，整合混合用户均衡模型，建立面向新型混合交通流的智能交叉口网络布局优化模型，并利用改进的遗传算法求解；最后，选取Sioux-Falls交通网络作为案例分析，验证模型与算法的有效性，并研究CAV渗透率变化对优化结果的影响。研究表明，智能交叉口在城市路网中的合理规划极大地提高了新型混行场景下城市交通系统的出行效率，同时，大幅降低了由于网联自动 驾驶单方面技术优势带来的CAV与HV的出行效率差距，增进了出行公平性。     

Dynamic Simulation of a Smart Crank and Slider Mechanism

In this paper, a smart crank and slider mechanism is analyzed mostly from a dynamic view. By means of dynamic explicit finite element method, 3D nonlinear structure is simulated. It is proved that the mechanism can effectively accomplish smart movement prescribed. And in order to ensure reciprocal movement with higher frequency, measures should be taken to avoid over heating of parts. Compared with internal energy, kinetic energy of total rigid body is dominating, and Y direction equivalent rigid velocity is much higher than X direction velocity. Equivalent rigid velocity of all parts is consistent with respective movement condition. For both energy and velocity, slider effect is dominating. Three direction equivalent inertia force oscillates. Force amplitude in Y -direction is comparitively the greatest.     

一种改进的基于密度和网格的高维聚类算法

提出了一种改进的基于密度和网格的高维聚类算法,并对算法有效性进行了验证.该算法通过减少样本点数量的方法达到减少稠密子空间数量.在发现高维稠密子空间时,对样本库进行精简.这些样本点的求得能有效减少求解最小聚类的时间复杂度.     

地下车站综合接地系统中若干问题探讨

讨论了接地电阻取值、人工接地网设置的必要性及合理性、自然接地极与杂散电流辅助收集网的关系等若干问题。阐述了部分解决方案。提供了一种可行的综合接地系统方案,可为人身安全及地铁运营提供有力保障。     

基于智慧地铁视角的广州地铁AFC系统架构设计

自动售检票(AFC)系统作为城市轨道交通中与乘客接触最为紧密的系统,应基于“以用户为中心”来提升客运服务水平。通过优化系统层级、整合多元化支付平台、引入智能客服功能、对接电子发票系统等措施,规划设计了适用于广州新一轮城市轨道交通线网建设要求的AFC系统架构,以期打造智慧的AFC系统,为乘客提供更为人性化和多元化的服务。     

Optimal design of electric vehicle public charging system in an urban network for Greenhouse Gas Emission and cost minimization

In this paper, we address the optimization problem of allocation of Electric Vehicle (EV) public fast charging stations over an urban grid network. The objective is to minimize Greenhouse Gas Emissions (GHG) under multiple constraints including a limited agency budget, accessibility of charging stations in every possible charging request and charging demands during peak hours. Additionally, we address bi-criteria problems to consider user costs as the second objective. A convex parsimonious model that depends on relatively few assumptions and input parameters is proposed and it is shown to be useful for obtaining conceptual insights for high-level planning. In a parametric study using a hypothetical urban network model generated based on realistic parameters, we show that GHG emissions decrease with agency budget, and that the reductions vary depending on multiple factors related to EV market and EV technologies. The optimal solutions found from the bi-criteria problems are shown to be close to the solution minimizing GHG emissions only, meaning that the emission minimizing policy can also minimize user costs.     

Validating and improving public transport origin–destination estimation algorithm using smart card fare data

Smart card data are increasingly used for transit network planning, passengers’ behaviour analysis and network demand forecasting. Public transport origin–destination (O–D) estimation is a significant product of processing smart card data. In recent years, various O–D estimation methods using the trip-chaining approach have attracted much attention from both researchers and practitioners. However, the validity of these estimation methods has not been extensively investigated. This is mainly because these datasets usually lack data about passengers’ alighting, as passengers are often required to tap their smart cards only when boarding a public transport service. Thus, this paper has two main objectives. First, the paper reports on the implementation and validation of the existing O–D estimation method using the unique smart card dataset of the South-East Queensland public transport network which includes data on both boarding stops and alighting stops. Second, the paper improves the O–D estimation algorithm and empirically examines these improvements, relying on this unique dataset. The evaluation of the last destination assumption of the trip-chaining method shows a significant negative impact on the matching results of the differences between actual boarding/alighting times and the public transport schedules. The proposed changes to the algorithm improve the average distance between the actual and estimated alighting stops, as this distance is reduced from 806 m using the original algorithm to 530 m after applying the suggested improvements.     

一种网格 k-近邻集的边界点识别算法

为了高效识别聚类边界,根据边界周围区域存在密度差异的特征,提出了一种网格 k‐近邻集的边界识别算法（BGN ）。在网格空间中,该算法根据网格单元和它最近邻居单元的 k‐近邻集的质量及其单元间中心距离确定边界度,由边界度和边界阈值判断每个网格单元是否为边界单元或噪声单元。通过从边界单元中提取更靠边缘的数据作为边界点的方式,使得边界更精细。实验结果表明,该算法能有效和快速识别出多密度数据集的聚类边界和噪声。     

智能天线系统中干扰抵消的算法研究

首先分析了智能天线在CDMA系统中应用,理论分析了通过空间特征向量来对其实现“零陷“,提出采用压低基站的上行干扰提升系统的性能的新算法,实验仿真显示:该算法通过空域滤波,能够显著提高系统性能.