【正文】 , while the dump areas consisted of two rock crusher bins and the waste area.The system was installed on four pieces of equipment and wired through the ignition switch, which allowed the system to operate only when the equipment was operating. The equipment battery provided a reliable power source. Data were collected over several days and recorded at a 2s time interval. The equipment operated approximately 11 h each day, thereby producing approximately 19,800 records daily. This large volume of recorded data resulted in a clear need for automated data reduction methods.The system simply and efficiently recorded position and velocity. The challenge became how to present the data in a graphical format for a preliminary review and then to identify and select the relatively small number of key records needed to calculate activity times. A preliminary review is necessary for the user to evaluate the data to determine in which activities the truck was engaged and the location of each activity.Graphical data representations and knowledge of the projectare the most appropriate sources from which to gather this information. The areas in which earthmoving activities were performed can be determined based on knowledge of the project and a plan view of the data. The truck from which the sample data were obtained moved material from two separate loading areas to two separate dumping areas.Fig. 3 shows that the truck was engaged in three separate operations, the first two of which are of importance (a single cycle of the third operation was performed and is therefore of little importance). Five loads were hauled approximately 800 m between 10:20 and 11:30 in the first operation, and a second hauling operation hauled 36 loads a distance of approximately 100 m between 10:30 and 20:20.Therefore, 2 load and haul operations consisting of 4 activities (load, haul, dump, and return) each were identified from the preliminary review. The activitynaming convention adopted for this work is the activity name followed by the associated areas. For example, loading in area 3 is labeled Load 3, while hauling from load area 1 to dump area 2 is labeled Haul 12. The TIMs were applied to the data to identify the beginning and end times for each of the identified activities.The dump activities occur in fixed locations and with zero velocity, and therefore the ADTIM was used to identify the records key to those activities. The ADTIM areas to be applied to the data are shown in Fig. 5. The user can determine the central coordinates and radial distance of each ADTIM area from the plan view of the recorded data. Once the input data are provided,the ADTIM is executed and the results are placed on an ADTIM sheet. A portion of the ADTIM results for the Dump 2 activity are provided in Table 2.The results obtained should be pared with the preliminary review results to verify the ADTIM process and ensure that the total instances and time frame of the associated activities concur with the results of the preliminary review. A total of approximately 18,850 data records were collected and analyzed. The set of records where velocity equaled zero numbered approximately 13,900, a reduction of approximately 25%. Further reduction by ADTIM identified 90 key records that mark the start and end of activities. These 90 records represent less than % of the total records collected, and thus the collected data were reduced by more than %.The EXTIM was used to identify the records key to the load activities because the area in which the truck was loaded changed over time. The data file recorded on the loader was used with a critical distance of 20 m. This distance was selected based on previous experience with data from the same or similar operations.It is also necessary to review the EXTIM results to identify and eliminate any extraneous results. Such results can be produced by actions occuring outside of time frames identified during data evaluation and by trucks queuing at the loader at a distance less than the specified critical distance. Results outside an operational time frame are easily identified。 the data were reduced by more than 99%.Data AnalysisThe results produced can be used to calculate the collection of durations for each activity over the workday. These collections of durations can be used to provide insight into both the activity and the parent operation as a whole. They can also be used to develop bestfit statistical functions for use in puter simulation and modeling techniques. The Dump 2 activity results will be used to demonstrate data analysis, and a portion of these results are presented in Table 2.Graphical representations of data are more meaningful than collections of numbers in a table. A histogram of the durations can indicate the shape of the statistical distribution underlying the duration data and is presented in Fig. 7. The histogram shows that the majority of durations were between 6 and 12 min, with some observations much shorter in duration. Six minutes are not required to raise the dump body and dump the load, and it can be seen from Table 2 that the dump activity can be pleted in less than 1 min. This indicates that the truck is not the constrainingequipment in the Dump 2 activity and that the duration is often many times greater than necessary.The collection of activity durations can be further used to determine statistical functions that fit the sample data within statistical limits. The Stat?Fit program is a statistical analysis software package that accepts the sample data as input, estimates the parameters of several potentially fitting statistical functions, evaluates the appropriateness of the function through goodnessoffittests, and provides a remendation to the user regarding each function.Modeling and simulation techniques can be used to analyze construction operations, using stochastic definitions of activity durations as input. To determine the duration of e