INDOT has utilized many new technologies to reduce travel delay, mitigate traffic congestion, and enhance public and employees’ safety. Many projects are underway, including re-timing of most existing traffic signals and pavement maintenance and rehabilitation. To evaluate signal system performance, prioritize alternatives of improvement, conduct before and after studies and investigate work zone safety, it requires a large amount of traffic data such as travel time, speed and delay. Issues, such as safety, efficiency and cost, may arise associated with the current methods. For the current manual or automatic data collection, it usually requires two operators, a driver and a recorder. The current methods also require much time for data processing and the resulting data files may not be reusable. With the global positioning system (GPS) technologies, it appears that traffic data collection can be performed more safely and efficiently. The objective of this study is to investigate use of the GPS technologies to improve efficiency of INDOT traffic data collection, to enhance field operation safety, and to reduce potential human errors. Primary emphasis is given to utilization of GPS receivers to acquire traffic data so as to generate a reusable data file. This kind of data files is essential for providing INDOT traffic engineers with consistent information for assessing the performance of signal systems. Secondary emphasis is given to use of the GPS data in specific transportation studies, such as travel time and delay studies, work zone studies, and congestion management. In this study, the GPS techniques were examined and the Trimble AgGPS 132 devices were tested using the precisely known geographic points. A computer program, GPS-Trek, was developed for data collection and data processing. A huge amount of data was collected over the selected routes. Based on the results of analysis and field tests, a summary of the major findings are presented below: The proposed GPS data collection system is inexpensive and cost-effective. It can improve the efficiency of traffic data collection, save manpower and enhance field operation safety. The AgGPS 132 receiver can provide traffic data of high accuracy and consistency. The field data may exhibit gaps in “deep” urban canyons. However, through interpolation and proper data screening these disadvantages may be limited. The removal of Selective Availability from the GPS signals further improves the accuracy of GPS data. It was shown that the relative positional accuracy using a DGPS service is well below the 0.5 meter level. The GPS-Trek consists of two components, one for data collection and the other for data processing. The program is free of personal interpretation during data collection and provides a consistent system of analysis. The resulting data files are reusable. The data file can be easily exported to Microsoft® Excel, allowing traffic engineers to utilize their own experience and judgment for data analysis and specific transportation studies. A modified equation is presented to estimate the sample size requirements for field data collection using GPS devices. It was shown that in the filed tests, the modified equation produced a realistic estimate of the minimum sample size. Generally, a minimum of three initial test runs should be performed. If possible, five initial test runs for 90% confidence or six for 95% confidence are required to reduce the potential errors. The proposed system can be readily used for various transportation studies. This system bases its procedures on the existing INDOT highway digital map, resulting in a great saving in terms of manpower and time for creating a high resolution base map. The system also allows us to mark any critical points during data collection or data processing. As a result, it is possible for us to provide graphical reports, such as vehicle trajectory and speed profile that are required in the Manual of Transportation Engineering Studies and get a full picture of traveling situation on the test route. Also, this system can be used for measuring congestion on a system level.
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