Sampling Frequency Effects on Trajectory Routes and Road Network Travel Time

GPS data is often used for computing travel time in road networks. In addition, GPS data is often map matched to find the routes driven by vehicles. Today GPS data is collected with different sampling periods, however, both the computed travel times and the routes found by map matching algorithms actual depends on the sampling period. This paper proposes a generic approach to study how travel time and map matched routes vary with the sampling period. Two types of map matching algorithms are used, point based where each position is handled individually, and trajectory based where positions from a vehicle is consider a data stream. A baseline is created using a real-world data set of 455 million positions from 368 vehicles collected with a sampling period of 1 second. This data set is downsampled to 8 data sets with sampling periods between 2 and 120 seconds. This downsampling enables an apple-to-apple comparison of travel time computation and route restoration for different sampling periods. The main conclusion is that travel times are reasonably accurate if the sampling period is 5 second or below for the point-based method and 20 seconds or below for the trajectory-based method. GPS data collected with 60 second is to inaccurate to be used for computing travel times. Trajectory-based map matching works best if the sampling period is 20 seconds or below.