面向智能车辆的现役道路设施行驶适应性研究综述

为了总结面向智能车辆的现役道路设施行驶适应性，即现役道路基础设施承载智能车辆行驶的适宜程度，阐述自主智能驾驶定义与驾驶自动化等级分类，在此基础上剖析不同等级间的人机功能差异，并分别从感知层、感知-决策层、决策-控制层探讨与道路设计要素相关联的人机功能差异，通过归纳总结智能车辆与道路几何要素、路面性能及其他道路要素(如道路标线)的相互作用机制研究，从道路工程角度及其他道路要素方面回顾该领域的研究现状，指出存在的问题和未来发展方向。研究结果表明：相比传统车辆，配置高等级自动驾驶系统的智能车辆对现役道路设施行驶适应性最高，主动安全系统次之，而驾驶辅助及有条件自动驾驶系统适应性不足。而目前研究主要问题包括：难以归纳、标定不同驾驶自动化等级间的人机功能差异及其对于道路设计参数的需求设计值；测试道路场景条件过于理想，考虑的驾驶自动化等级单一，试验规模和样本有限；道路几何、路面性能以及道路标志、标线等道路要素与智能车辆间的相互作用机制研究不足，缺乏与不同道路场景相匹配的智能车辆驾驶特征数据的获取手段。因此建议：重视并推动与道路设计要素相关联的关键人机功能差异指标信息共享；联合高保真且可交互的道路场景、高精度感知传感器物理模型、车辆动力学模型及微观交通流模型，利用测试场景自动化生成、极限工况场景搜寻与泛化等技术开展智能驾驶虚拟测试，突破现有研究的深度和广度；探索反映不同等级智能车辆的道路行驶适应性特征指标与评价标准，精准、有效地评估预测复杂道路场景及不利道路条件下的行驶适应性。     

有轨电车交叉口交通组织及控制方案优化

有轨电车在运行过程中,易在交叉口处产生瓶颈,导致有轨电车通行速度降低、乘客舒适度下降。从有轨电车交叉口信号优先控制、现状交叉口交通管理与控制优化、公共交通组织优化、慢行交通组织优化4个方面提出了相应的优化措施。以武汉市有轨电车作为实例,提出了一系列改善措施,并利用VISSIM软件仿真模拟了实施效果,仿真结果验证了优化方案的科学性和有效性。     

GSM-R中跨SGSN更新时源SGSN域名解析数据的智能生成方案设计

源SGSN域名解析数据是GSM-R网络编号方案数据中重要的需跨局制作的一类数据。由RAI编码构造生成,在跨SGSN路由区更新时,存储于DNS中,以解析源SGSN的IP地址。全路400多条G网线路,错综复杂的基站引用关系,导致数据复杂多样。针对该情况,利用聚类分析和关联规则分析算法,研究源SGSN解析数据的智能生成方案,提高数据的全面性、准确性,从而有效保障GSM-R分组域应用业务的正常运转。     

基于云平台的城市轨道交通能源管理系统

阐述了基于云平台的城市轨道交通能源管理系统架构和建设方式。该系统利用云计算的高效和弹性来部署建设,采用线网-车站二层管理模式,降低了线网和线路服务器等的硬件部署成本和维护成本。通过将能源管理系统内部使用的业务应用转换为基于云平台的能源管理应用软件,能源管理系统可获取云平台提供的共享数据,并将经过业务处理后的数据存储到云平台中,以服务于云平台上其他业务,实现了数据资源的逻辑统一和高效利用。     

基于超融合基础架构的铁路云数据中心建设方案

在充分研究铁路信息化发展现状、演进困境以及云计算平台技术的基础上,结合中国国家铁路集团有限公司对于信息化的总体规划,提出铁路云数据中心的总体技术架构,详细阐述基于云计算技术的铁路数据中心平台优势。对涉及到的关键技术:超融合技术和网络拓扑技术展开说明。立足铁路云数据中心规划建设角度,重点从IaaS层资源规划、云管平台建设、网络架构设计和云平台双活灾备建设4个方面进行详细论述。为铁路云数据中心规划、设计、建设提供理论基础和技术支撑,也为后续工程现场实施提供重要的建设思路支撑和实验室数据支撑。     

Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

Airport capacity increase via the use of braking profiles

Many airports are encountering the problem of insufficient capacity, which is particularly severe in periods of increased traffic. A large number of elements influence airport capacity, but one of the most important is runway occupancy time. This time depends on many factors, including how the landing roll procedure is performed. The procedure usually does not include the objective to minimize the runway occupancy time. This paper presents an analysis which shows that the way of braking during landing roll has an essential impact on runway throughput and thus on airport capacity. For this purpose, the landing roll simulator (named ACPENSIM) was created. It uses Petri nets and is a convenient tool for dynamic analysis of aircraft movement on the runway with given input parameters and a predetermined runway exit. Simulation experiments allowed to create a set of nominal braking profiles that have different objective functions: minimizing the runway occupancy time, minimizing noise, minimizing tire wear, maximizing passenger comfort and maximizing airport capacity as a whole. The experiments show that there is great potential to increase airport capacity by optimizing the braking procedure. It has been shown that by using the proposed braking profiles it is possible to reduce the runway occupancy time even by 50%.     

高等级公路监理工程项目管理综述

监理是一个项目管理的系统工程,有着严格的制度和程序,有助于有效控制工程的进度、质量和费用,实时监测发现施工过程中的问题,第一时间进行反馈,保证路面施工质量,对后续路面开放运营的质量具有明显作用.     

递进式连锁经营管理专业实践教学改革研究——基于加盟创业项目视角

连锁经营管理专业人才培养目标大多定位在一线服务员或基层管理者，所培养的学生必须具备较强的连锁专业能力和创业能力，而大多数高职院校培养出来的学生在这些方面所表现出来的能力却差强人意，尤其是创业能力方面。本文提出将加盟创业项目贯穿于连锁经营管理实践教学全过程，按照“仿真训练-校内孵化-校内模拟-市场全真”四个阶段，形成一个递进式的实践教学流程，从而促使学生的专业能力和创业能力实现递进式提升。