【正文】 o production measures through the use of surrogate measures and protocol rules. Kannan (1998) describes the use of suspension strut pressure, gear control lever position,bed raise switch position, and speed to derive the duration of truck cycle ponents. Truck cycle ponents or activities are defined in terms of the parameters. It is evident from the literature reviewed that traditional datacollection methods are limited by the ability of an observer to instantaneously decide activity start and stop times within a narrow and static field of view. Modern techniques remove this limitation by using sensorbased datacollection techniques to identify key times through changes in sensor output. A thorough understanding of the methods for reviewing, reducing, and analyzing GPS data from construction operations requires background knowledge of how and what data are collected.Data Capture An automated data capture system based on GPS technology was used to record the raw data at a userspecified time interval, including date, time, velocity, and horizontal position. The system consists of a data box, junction box, and sensor pack and was developed based on field evaluations of mercially available systems. The data acquisition and storage box is a weathertight enclosure that houses the system circuitry and the CompactFlash media on which the data is stored. The sensor pack consists of a Garmin GPS35 LVC receiver and a Vector 2X magnetic pass manufactured by Precision Navigation, Inc. In addition to the GPS and pass, the system has been developed such that additional analog and digital sensors can be incorporated into the system for future research. The junction box serves as a central location for all electrical connections to be made. Power is made available in the box at 5 V for any additional analog sensors incorporated into the system. Data are recorded in ma delimited ASCII text format, with a separate data file for each day of collection to ensure files of a manageable size. The parameters recorded by the system include unit identification number, date, UTM time, latitude, longitude,velocity, type of GPS fix, output from the five analog and eight digital sensors, and direction of travel from the pass. Preliminary ReviewA tradeoff exists between the volume of data recorded and the level of detail provided by the data. Large volumes of data are produced when recorded at a time interval sufficiently short to facilitate operations analysis. The several thousand records produced daily on each machine must be reduced to the relatively few key records necessary to calculate activity times. The large volume of data dictates that the data reduction process be automated.The format of the data, a text string repeatedly recorded at aset time interval, is conducive to analysis in a spreadsheet environment supported by capable graphics. Microsoft Excel was chosen as the data processing engine as it is a widely used and recognized program already familiar to many potential users, thereby minimizing or eliminating the learning curve. Excel is a mon and robust spreadsheet application that can be automated through the Visual Basic for Applications (VBA) language and provides the means to graphically represent data.Processing the collected data for evaluation and reduction is performed in three steps: the data into Excel。s field of view. Global Positioning System (GPS) technology incorporated into an onboard instrumentation system can be used to autonomously collect position and velocity data without the field of view limitation. Data must be collected at a short time interval to provide the level of detail necessary for operations analysis. Thus the issue bees managing the data and identifying the relatively key records that mark the start and stop of activities. A field observer identifies the key times in real time withinstantaneous decisions of when one activity stops and the next starts based on enormous volumes of visual information. This work developed a methodology for making equivalent decisions based on GPS data and presents the procedures developed to identify the key records necessary to calculate activity durations. A case study is used to illustrate application of the system to an earthmoving operation. Also, it is postulated how the information can be used in discrete event simulation. DOI: (ASCE)07339364(2005)131:8(920)CE Database subject headings: Geographic information systems。Reduction of ShortInterval GPS Data for Construction Operations AnalysisJohn Hildreth, 。 Construction industry。 recorded horizontal position from geodetic to planar coordinates。and required to travel through or between fixed areas—.,a haul truck traveling between load and dump areas. Time identification modules (TIMs) were developed to identify the GPS data records corresponding to the beginning and end of activities associated with each of the three specific modules have been developed in the VBA language for execution in Excel. The results produced by TIMs have been pared to those produced by a PAVIC+ analysis of the videotaped operation in an effort to validate the TIMs results. The activity durations resulting from both analyses were pared and found to be in agreement,both in the duration of activities and the order in which they occurred. It was concluded that the shortinterval GPS data can be reduced to the key records using the TIMs.Arrive and Depart Time Identification ModuleThe duration of certain construction activities that repeatedly occur in a fixed location can be characterized as the time elapsed while the vehicle was stopped within a given distance from a fixed point. A truck loaded from a hot mix asphalt bin or a truck dumping into the bin of a rock crusher are examples of such activities. The Arrive and Depart Time Identification Module (ADTIM) was developed for this condition and to identify the first (arrive) and last (depart) times