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Emerging GPS (Global Positioning System) enabled cell phones offer new opportunities of data collection in massive volumes at relatively cheaper cost than the dedicated probe vehicles. In Canada, commercial cell phone service providers are beginning to offer GPS-enabled phones and hence enabling a variety of Location Based Services (LBS). Regardless of the application, each cell phone location query or ping is charged with a certain cost and therefore it is in the user's interest to minimize the pinging frequency. Traffic monitoring applications first need to determine whether the GPS-enabled cell phone is actually in an automobile and secondly, it needs to match the current GPS device location to a corresponding link on a GIS (Geographic Information Systems) map. This paper develops a methodology to determine the relationship between cell phone pinging sampling rate and the accuracy of mode detection and map matching processes. It is found that 2 pings of an AGPS cell phone per every 3 minutes results in 80% accuracy in auto mode detection rate. It is also found that the higher the number of pings per interval and the longer the data trace interval, the better the accuracy, achieving as high as 98% auto mode identification rate. The impact of a sampling frequency on map matching algorithm is found to be a function of link length, current speed of a vehicle and period of the day. The developed algorithms are implemented in a previously developed application framework named GISTT.
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