铁路列车控制系统简析

随着铁路运输的发展和科学技术的进步,列车运行控制系统也在不断发展。介绍了铁路列车控制系统的4个发展阶段,着重介绍了通信控制方式的特点及其在我国的发展,并在此基础上对其发展前景进行了展望。     

CAN局域网及J1939协议在货车和客车上的运用

叙述了CAN总线网络的特点及J1939协议的原理、内容及协议的应用。并设计最小节点实现应用J1939协议的CAN局域网的数据通信功能。     

智能压路机控制系统数据通信的实现

介绍了CAN总线及CANopen协议的技术特点,详细阐述了基于CAN总线技术的智能压路机控制系统数据通信的实现,使之达到了智能压路机的设计要求.     

公路超载超限检测控制系统的研究

针对目前公路运输中的超载超限问题,研究开发出一种固定式超载超限检测系统。该文介绍系统的主要组成、系统特点、技术路线等。对控制系统中串行通信的硬件组成及接口方式进行分析,重点论述了在Windows环境下,使用VB利用MSComm控件实现系统中串行通信的一般步骤和实现方式,较为详细地给出了公路固定超限检测系统中基于PC机的使用VB编制的控制程序。     

超深振捣条件下混凝土墙体模板侧压力的简化计算方法

超深振捣对混凝土成品质量有害无益,研究超深振捣引起模板侧压力增大的规律,可为规避其害提供依据。为此设计4个混凝土墙体试件,实测在浇筑过程中模板侧压力的变化情况。基于振捣液化和液体压力平衡理论,建立了超深振捣情况下混凝土模板侧压力计算模型,推导了计算公式,并与实验数据进行对比验证。研究结果表明,振捣深度是影响混凝土墙体模板侧压力的重要因素,本文提出的计算模型能很好地预测墙体结构超深振捣位置的模板侧压力。     

浅谈FAS双中心建设及设备维护

重点分析了西安局集团公司由2K数调主系统组网更新改造为FAS双中心网络的建设方法,并根据日常维护经验,列举了调度台通道故障处理、FASB简易故障判断及计表倒换试验、FASA和FASB系统与MSC之间的业务故障处理等.     

西南红层软岩地区铁路滑坡形成机理分析及治理措施

红层软岩地区铁路工程建设中滑坡问题突出。本文结合西南地区一铁路红层滑坡治理工程,利用该地区红层滑坡的现场调查结果,从红层软岩特性、地层岩性、地质地貌、水文地质条件、深孔位移监测数据等多方面对该地区铁路滑坡形成机理进行分析,并论述红层滑坡与一般滑坡的不同点,分析红层软岩岩体力学特性、地层主要成分以及红层软岩中的粉砂质泥岩在不同风化程度下的力学特性。根据分析结果提出治理措施,并对治理措施进行评价。总结得出地层岩性、地质水文、人为因素是导致红层滑坡病害发生的主要因素。     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

Field tests of a dynamic green driving strategy based on inter-vehicle communication

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions.     

铁路路基动态变形模量的数值模拟分析

介绍铁路路基动态变形模量理论计算公式的推导及动态变形模量的测试原理,采用有限元软件模拟动态变形模量的测试过程,分析承载板与土体接触压力、路基动态变形模量的影响因素,并计算动态变形模量的有效测试深度.结果表明:在承载板中心一定范围内,接触压力模拟结果较理论计算值大;土体的动弹性模量对接触压力影响很小,可以忽略;路基动态变形模量测试冲击荷载作用下,土体只发生弹性变形;动态变形模量与土体动弹性模量呈线性关系,路基动态变形模量的模拟结果大于理论计算值;土体的泊松比对动态变形模量影响较小;动态变形模量有效测试深度建议取0.5~0.6 m.