基于总线控制机的机车油脂自动发放系统的实现

针对机务段油脂发放的现状,提出机车油脂自动发放和计算机管理的新方法,介绍一种机车油脂自动发放系统的实现方法.实践表明,该系统简单实用,提高了机务段油脂发放的设备自动化水平和油脂的管理水平.     

基于CAN总线的机车电气监控系统的设计

介绍CAN总线及其相关协议,设计了基于CAN总线的机车电气监控系统的硬件结构,阐述了现场控制模块应用层通讯协议的设计并给出了具体的流程图.     

CAN总线在车辆空气制动试风系统中的应用研究

随着铁路信息化、数字化的发展,铁路运营和检修设备的安全性和实时性的要求越来越高.车辆单车试风系统也正在经历这一过程.基于CAN总线的货车单车试风系统的设计,包括CAN总线的简介,系统的整体设计原理框图,上位机和下位CAN节点硬件设计与实现,下位CAN节点控制系统的软件设计与流程,上位工控计算机管理信息系统的构成和功能,在现场的应用情况.     

铁路局车站间数据交换系统的设计与实现

在铁路运输生产中,车站起着重要的作用.讨论铁路局调度系统中铁路局与车站数据交换的实现方法,利用Socket技术使得数据交换变得准确和快捷.实践表明,该系统能够很好地满足日常运输生产要求.     

A hybrid machine learning model for short-term estimated time of arrival prediction in terminal manoeuvring area

4D trajectory prediction is the core element of future air transportation system, which is intended to improve the operational ability and the predictability of air traffic. In this paper, we introduce a novel hybrid model to address the short-term trajectory prediction problem in Terminal Manoeuvring Area (TMA) by application of machine learning methods. The proposed model consists of two parts: clustering-based preprocessing and Multi-Cells Neural Network (MCNN)-based prediction. Firstly, in the preprocessing part, after data cleaning, filtering and data re-sampling, we applied principal Component Analysis (PCA) to reduce the dimension of trajectory vector variable. Then, the trajectories are clustered into several patterns by clustering algorithm. Using nested cross validation, MCNN model is trained to find out the appropriate prediction model of Estimated Time of Arrival (ETA) for each individual cluster cell. Finally, the predicted ETA for each new flight is generated in different cluster cells classified by decision trees. To assess the performance of MCNN model, the Multiple Linear Regression (MLR) model is proposed as the comparison learning model, and K-means++ and DBSCAN are proposed as two comparison clustering models in preprocessing part. With real 4D trajectory data in Beijing TMA, experimental results demonstrate that our proposed model MCNN with DBSCAN in preprocessing is the most effective and robust hybrid machine learning model, both in trajectory clustering and short-term 4D trajectory prediction. In addition, it can make an accurate trajectory prediction in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) with regards to comparison models.     

How to assess the benefits of connected vehicles? A simulation framework for the design of cooperative traffic management strategies

Advances in Information and Communication Technologies (ICT) allow the transportation community to foresee dramatic improvements for the incoming years in terms of a more efficient, environmental friendly and safe traffic management. In that context, new ITS paradigms like Cooperative Systems (C-ITS) enable an efficient traffic state estimation and traffic control. C-ITS refers to three levels of cooperation between vehicles and infrastructure: (i) equipped vehicles with Advanced Driver Assistance Systems (ADAS) adjusting their motion to surrounding traffic conditions; (ii) information exchange with the infrastructure; (iii) vehicle-to-vehicle communication. Therefore, C-ITS makes it possible to go a step further in providing real time information and tailored control strategies to specific drivers. As a response to an expected increasing penetration rate of these systems, traffic managers and researchers have to come up with new methodologies that override the classic methods of traffic modeling and control. In this paper, we discuss some potentialities of C-ITS for traffic management with the methodological issues following the expansion of such systems. Cooperative traffic models are introduced into an open-source traffic simulator. The resulting simulation framework is robust and able to assess potential benefits of cooperative traffic control strategies in different traffic configurations.     

Adaptive data dissemination for time-constrained messages in dynamic vehicular networks

With the advent of emerging wireless communication technologies, tremendous efforts have been put on promoting the safety and efficiency of transportation services by developing innovative applications. In particular, there has been significant interest in accessing information stored at RSUs (Roadside Units). The unique characteristics in vehicular networks, such as dynamic traffic factors including vehicle arrival rate, dwell time and data access patterns, bring us new challenges on data dissemination. This work dedicates to the investigation of timely and adaptive data dissemination in the dynamically changing traffic environment. Firstly, we derive an analytical model to explore and examine the effects of the dynamic traffic factors. In light of the theoretical results, an on-line scheduling algorithm is proposed for adaptive data dissemination. Finally, we evaluate performance of the new algorithm in a variety of circumstances. The simulation results demonstrate satisfactory performance of the proposed algorithm.     

Numerical analysis of electric bus fast charging strategies for demand charge reduction

Electric transit buses have been recognized as an important alternative to diesel buses with many environmental benefits. Electric buses employing lithium titanate batteries can provide uninterrupted transit service thanks to their ability of fast charging. However, fast charging may result in high demand charges which will increase the fuel costs thereby limiting the electric bus market penetration. In this paper, we simulated daily charging patterns and demand charges of a fleet of electric buses in Tallahassee, Florida and identified an optimal charging strategy to minimize demand charges. It was found that by using a charging threshold of 60–64%, a $160,848 total saving in electricity cost can be achieved for a five electric bus fleet, comparing to a charging threshold of 0–28%. In addition, the impact of fleet sizes on the fuel cost was investigated. Fleets of 4 and 12 buses will achieve the lowest cost per mile driven when one fast charger is installed.     

地下管线测漏仪中数据的采集和预处理

在对管线渗漏信号进行分析的基础上 ,利用DSP芯片TMS32 0VC5 40 2和模数转换器CS5 36 0实现了数据的高精度采集。同时设计了基于渗漏信号特征的数字滤波器 ,对采集后的信号进行有效预处理。     

基于B/S模式的机车信号检测数据分析系统

结合当今比较流行的计算机技术,研究了一种新型的基于浏览器/服务器（Browser/Server,简称B/S）模式的机车信号检测数据分析系统,给出了系统设计原理和实现方法.