GPS测量中坐标系统、坐标系的转换过程

GPS在测量领域得到了广泛的应用,本文介绍将GPS所采集到的WGS-84坐标转换成工程所需的坐标的过程。     

基于GPS和RFID技术的铁路信号设备巡检系统

为便于对铁路信号设备巡检人员的管理，结合GPS（卫星定位系统）和RFID（射频识别）技术，设计了一种铁路信号设备巡检系统。它采用GPS技术记录巡检路径，考查巡检人员是否按照规定的路径和顺序检查设备，采用RFID技术考查巡检人员是否检查了某个设备。结合两种技术考查巡检人员开箱检查信号设备时的操作规范性。它将克服基于信息钮扣巡检系统的信息钮扣易受破坏、接触不良的缺点，避免由于GPS／GIS巡检系统的巡检精度低导致无法区分设备的缺陷，同时解决基于RFID的巡检茅统无法进行线路巡检和无法考察巡检人员操作规范性的问题，提高了巡检系统的可靠性。本文介绍了系统设计原理、关键技术的运用及软硬件实现。     

铁路航测控制测量的应用技术

本文从铁路航测的特点,简述了铁路航测控制测量的外控点布设和外控点联测的技术及其特点.对利用GPS进行外控点测量的常用方法进行了系统介绍.     

基于GPS的列车监控系统的设计与实现

主要讨论GPS(全球定位系统)技术在铁路上的应用.研究了系统的组成,设计方案,软件设计,以及实验与结论.     

移动定位系统在高速公路管理中的应用

移动定位系统的应用对规范通行费用拆分方式、提高拆分透明度和公平性具有重要意义。文章分析了目前广西高速公路管理中存在的问题,同时结合移动定位定义、系统的构成及基本原理,介绍移动定位系统在高速公路管理中的具体应用情况及达到的效果。     

GPS和惯导组合系统的导弹遥测系统

随着卫星导航和惯性导航在导弹中的使用,导弹的精确打击能力越来越强.为了进一步提高导弹性能,人们需要通过遥测了解导弹在飞行过程中的工作状态参数.分析遥测数据可对设计作出评价,为改进设计提供依据,缩短导弹的研制周期.     

The vehicle emissions and performance monitoring system: analysis of tailpipe emissions and vehicle performance

This paper describes tailpipe emission results generated by the Vehicle Performance and Emissions Monitoring system (VPEMS). VPEMS integrates on‐board emissions and vehicle/driver performance measurements with positioning and communications technologies, to transmit a coherent spatio‐temporally referenced dataset to a central base station in near real time. These results focus on relationships between tailpipe emissions of CO, CO₂, NO_x and speed and acceleration. Emissions produced by different driving modes are also presented. Results are generally as one would expect, showing variation between vehicle speed, vehicle acceleration and emissions. Data is based upon a test run in central London on urban streets with speeds not exceeding about 65 km/h. The results presented demonstrate the capabilities of the system. Various issues remain with regard to validation of the data and expansion of the system capability to obtain additional vehicle performance data.     

消除公交串车——一种基于GPS与GIS的实时控制方法

城市公共交通系统是一个包含人、车、路、环境、能量和信息的高度非线性的大规模复杂系统。公交串车问题严重降低了公交服务的可靠性，本文综合运用系统工程理论与方法，给出了公交串车与大间隔的定义，提出了公交串车与大间隔问题的成因分析模型、基于BP人工神经网络的行车间隔预测模型和基于GPS与GIS的实时动态反馈控制模型。最后，对北京公交300路车所采集的680组数据进行了实证分析。分析结果表明所使用的方法能有效地消除公交串车问题，同时也能为公交企业自身的运营管理和乘客的出行规划提供有价值的决策参考。     

Analysis of consumer response to fuel price fluctuations applying sample selection model to GPS panel data: Dynamics in individuals’ car use

The effects of fuel price increases on people’s car use have been widely discussed during the last few decades in travel behavior research. It is well recognized that fuel price has significant effects on driving distance and driving efficiency. However, most of this research assumed that these effects are invariant across individuals and weather conditions. Moreover, intrinsic variability in people’s preferences has not been given much attention due to the difficulty of collecting the necessary data. In this paper, we collected detailed travel behavior data of 276 respondents in the Netherlands, spanning a time period between one week and three months using GPS logs. These GPS data were fused with weather data, allowing us to estimate both exogenous (such as weather and fuel price) and endogenous effects (inertia and activity plans) on individual’s car use behavior. To further understand the effects of fuel price on the environment, we estimated the effects of fuel price fluctuation on CO₂ emissions by car. The results show a significant degree of inertia in car use behavior in response to increased fuel prices. Weather and fuel price showed significant effects on individual’s car using behavior. Moreover, fuel price shows two-week lagged effects on individual’s travel duration by car.     

Time of day intervals partition for bus schedule using GPS data

Time of day partition of bus operating hours is a prerequisite of bus schedule design. Reasonable partition plan is essential to improve the punctuality and level of service. In most mega cities, bus vehicles have been equipped with global positioning system (GPS) devices, which is convenient for transit agency to monitor bus operations. In this paper, a new algorithm is developed based on GPS data to partition bus operating hours into time of day intervals. Firstly, the impacts of passenger demand and network traffic state on bus operational performance are analyzed. Then bus dwell time at stops and inter-stop travel time, which can be attained based on GPS data, are selected as partition indexes. For buses clustered in the same time-of-day interval, threshold values of differences in dwell time at stops and inter-stop travel time are determined. The buses in the same time-of-day interval should have adjacent dispatching numbers, which is set as a constraint. Consequently, a partition algorithm with three steps is developed. Finally, a bus route in Suzhou China is taken as an example to validate the algorithm. Three partition schemes are given by setting different threshold values for the two partition indexes. The present scheme in practice is compared with the three proposed schemes. To balance the number of ToD intervals and partition precision, a Benefit Evaluation Index is proposed, for a better time-of-day interval plan.