GPS RTK测量技术在公路外业测量中的应用

文章以GPS RTK测量技术为研究对象,结合南宁伶俐至钦州陆屋公路工程,介绍了GPS RTK测量技术在公路外业测量中的应用方法,并评述了GPS RTK测量技术的优缺点,提出了相应的建议。     

GPS在公路测量上的应用

详细阐述GPS全球定位系统的测量原理和结构组成,以及GPS系统在某高速公路工程项目测量上的应用实例,并对其测量成果进行精度评价.     

GPS在公路工程测量中的应用

GPS(Global Positioning System)全球定位系统是美国研制并在1994年投入使用的卫星导航与定位系统。其应用技术已遍及国民经济的各个领域。在测量领域,GPS系统已广泛用于大地测量、工程测量、航空摄影测量以及地形测量等各个方面。本文将以青海省公路路网项目为例,概略叙述GPS系统在公路工程控制测量中的应用。     

GPS RTK技术在公路勘测中的应用

针对GPS RTK技术快速静态定位和动态定位两种测量模式在公路勘测过程中不同阶段的应用,通过对GPS RTK技术测量误差来源的分析,总结其在测量过程中形成误差的因素。     

GPS在高速公路测量中的应用

全球定位系统GPS技术应用于高速公路测量是公路外业勘测的一项重大技术革新,其应用及开发的前景十分宽广。尤其是实时动态(RTK)定位技术在高速公路测量中蕴含着巨大的技术潜力,介绍GPS技术的发展由来和组成,并重点介绍RTK技术在高速公路测量中的特点。     

桂江GPS平面控制网的布设及实施

文章结合桂江首级平面控制网的测量工作实践,阐明在特殊测区采用边连式GPS控制网布设方式的优点,并总结采取该布网方式进行GPS控制测量应注意的几个问题,为类似测量项目提供参考。     

铁路平面控制测量中GPS技术的应用研究

铁路平面控制测量已经成为铁路工程项目施工顺利进行的重要保障,而针对常规人工测量方法中存在的精准度差、效率低等问题,利用GPS技术则可以有效解决传统检测技术的弊端,其优势显著。从GPS技术的技术原理出发,对GPS技术在铁路平面控制测量中的应用技术进行深入研究,并详细介绍路线平面控制网布设方案、平面控制网检测的注意事项等;最后,采用案例分析总结GPS技术的应用要求,并针对铁路平面控制测量的GPS数据处理方法提出相关意见,以供参考。     

青藏铁路J隧道群GPS应用

文章介绍高原及山区铁路隧道GPS施工控制测网的建立与特点，GPS测量距离角度与常规测量比较，以及其应用。     

手机GPS在公路前期外业勘察和内业阶段的应用

传统的公路项目在外业勘察测量和内业整理阶段工作量较大且繁重。文章基于手机GPS的工作原理,介绍手机GPS在公路项目勘察设计中的应用方法。手机GPS精度高、携带方便、充电方便,能应用于外业勘察中的简单测量、路线导航和内业设计中的资料汇总、汇报材料、动画演示,数据流转方便快捷,资料审阅查阅方便,可大大提高工作效率,应用效果明显。     

GPS在高速公路复线测量中的应用

在现代公路勘测中,采用GPS技术能够满足公路勘测的精度要求,同时测量工作效率高。结合具体的高速公路复线测量工程实例,简要探讨GPS技术的具体应用过程,希望能对类似工程起到借鉴作用。     

红水河曹渡河口至桥巩段平面高程控制测量方法

文章从GPS静态测量、导线测量、高程控制测量等三个方面入手,详细阐述了红水河曹渡河口至桥巩段平面高程控制测量方法及实施情况。     

An analysis of the factors influencing differences in survey-reported and GPS-recorded trips

Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional survey-reported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPS-recorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-h period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.     

GPS-RTK在水下地形测量中的应用

RTK(Real Ti me Kinematic)定位技术是GPS定位技术的一项飞跃,文章通过工程实例,介绍了GPS-RTK在水下测量中的应用,对其作业流程和关键技术问题进行了分析,得出了一些有益的结论。     

Identifying travel mode with GPS data

Travel mode identification is an essential step in travel information detection with global positioning system (GPS) survey data. This paper presents a hybrid procedure for mode identification using large-scale GPS survey data collected in Beijing in 2010. In a first step, subway trips were detected by applying a GPS/geographic information system (GIS) algorithm and a multinomial logit model. A comparison of the identification results reveals that the GPS/GIS method provides higher accuracy. Then, the modes of walking, bicycle, car and bus were determined using a nested logit model. The combined success rate of the hybrid procedure was 86%. These findings can be used to identify travel modes based on GPS survey data, which will significantly improve the efficiency and accuracy of travel surveys and data analysis. By providing crucial travel information, the results also contribute to modeling and analyzing travel behaviors and are readily applicable to a wide range of transportation practices.     

A GPS-aided survey for assessing trip reporting accuracy and travel of students without telephone land lines

A geo-positioning satellite (GPS)-based survey, using a web-based prompted recall tool, was conducted on a sample of 94 students at the University of Toronto from November 2008 to April 2009. The sample included students with and without telephone land lines, allowing for a statistical comparison of demographic and travel behaviour attributes. The same subjects simultaneously completed a traditional trip reporting survey, modelled on the household travel survey in Toronto, allowing for a comparison between the travel behaviour information obtained from the GPS and that reported by the participants in the traditional survey. Students with a land line are more likely to live in houses, with parents, and to live in suburban areas than students without a land line. They also make fewer trips in total, fewer discretionary trips, more transit and auto trips and fewer active trips than students without a land line. By comparing questionnaire-based data and GPS data, we found that most participants reported in the questionnaire either the same number of GPS-based trips or fewer. On average, the GPS survey captured 1.29 more daily trips per participant than the corresponding trips reported in the questionnaire.     

Assessing the accuracy of the Sydney Household Travel Survey with GPS

Over the past few years, GPS has been used in a number of surveys in the US to assess the accuracy of household travel surveys. The results have been somewhat alarming in that most of these exercises have shown that the standard trip-based CATI survey conducted in the US under-reports travel by about 20–25%. It was decided to use GPS to assess the accuracy of the Sydney Household Travel Survey, a continuous survey conducted by face-to-face interviewing. The procedure used was for the interviewers to recruit households for the household travel survey in the normal manner, and then, if the household met certain criteria, to endeavour to recruit the household to also undertake a GPS survey. A small sample of about 50 households was obtained, and GPS devices successfully retrieved that measured data on the same day as the travel diary was completed. In addition, participants in the GPS survey completed a prompted recall survey a week or two later, using maps and tabulations of travel obtained from the GPS devices, to identify mode, purpose and occupancy for trips measured by the GPS, and also to check for accuracy in defining trip ends and total number of trips. Based on the analysis of the GPS compared to the diary results, it was found that respondents under-reported their travel by about 7%, which is much less than in the US CATI results. Respondents were also found to under-report travel distances and over-report travel times. There was also a high incidence of non-reporting for VKT.

影响科氏流量计测量精度的原因及处理措施

随着油气管道业快速发展,油品交易日益增多,流量计的重要性日益突出。科氏流量计可以直接显示质量流量、密度以及温度,有着广阔的应用前景。文中从介绍科氏流量计组成、工作原理入手,以提高质量流量计的测量准确度为目的,结合实际工作,通过分析零点不稳定度、油品含气等对流量计测量精度的影响,提出了安装、调零、选取合适的流量范围、后期维护等方面的处理方法,提高了质量流量计的准确度。     

Detecting trip purposes from smartphone-based travel surveys with artificial neural networks and particle swarm optimization

Travel surveys based on global positioning system (GPS) data have exponentially increased over the past decades. Trip characteristics, including trip ends, travel modes, and trip purposes need to be detected from GPS data. Compared with other trip characteristics, studies on trip purpose detection are limited. These studies struggle with three types of limitations, namely, data validation, classification approach-related issues, and result comparison under multiple scenarios. Therefore, we attempt to obtain full understanding and improve these three aspects when detecting trip purposes in the current study. First, a smartphone-based travel survey is employed to collect GPS data, and a surveyor-intervened prompted recall survey is used to validate trip characteristics automatically detected from the GPS data. Second, artificial neural networks combined with particle swarm optimization are used to detect trip purposes from the GPS data. Third, four scenarios are constructed by employing two methods for land-use type coding, i.e., polygon-based information and point of interest, and two methods for selecting training dataset, i.e., equal proportion selection and equal number selection. The accuracy of trip purpose detection is then compared under these scenarios. The highest accuracies of 97.22% for the training dataset and 96.53% for the test dataset are achieved under the scenario of polygon-based information and equal proportion selection by comparing the detected and validated trip purposes. Promising results indicate that a smartphone-based travel survey can complement conventional travel surveys.     

Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands

In the past few decades, travel patterns have become more complex and policy makers demand more detailed information. As a result, conventional data collection methods seem no longer adequate to satisfy all data needs. Travel researchers around the world are currently experimenting with different Global Positioning System (GPS)-based data collection methods. An overview of the literature shows the potential of these methods, especially when algorithms that include spatial data are used to derive trip characteristics from the GPS logs. This article presents an innovative method that combines GPS logs, Geographic Information System (GIS) technology and an interactive web-based validation application. In particular, this approach concentrates on the issue of deriving and validating trip purposes and travel modes, as well as allowing for reliable multi-day data collection. In 2007, this method was used in practice in a large-scale study conducted in the Netherlands. In total, 1104 respondents successfully participated in the one-week survey. The project demonstrated that GPS-based methods now provide reliable multi-day data. In comparison with data from the Dutch Travel Survey, travel mode and trip purpose shares were almost equal while more trips per tour were recorded, which indicates the ability of collecting trips that are missed by paper diary methods.