When handling a vehicle trajectory dataset composed of a large number of points on a digital map, all the collected data may not be required. In particular when a trajectory is displayed on a computer screen, it is desirable to use the smallest dataset that can accurately describe the actual trajectory. The objective of this study is to develop an algorithm that reduces the amount of vehicle tracking data while retaining the original shape of the vehicle trajectory. The algorithm assigns a degree of importance in shape representation to each data point. The degree of importance is defined in terms of wavelet coefficients, and the algorithm determines the order by which data points are eliminated To evaluate the performance of the algorithm, a 15,618-point dataset obtained from a GPS unit mounted on an agricultural vehicle was processed Even when the dataset was reduced to 912 points, which is only 5.8% of the original dataset, the root mean square error was no more than 0.76 m. The computational time for data reduction on the selected computer was 8 ms. The proposed reduction algorithm was embedded in the map software used to display the vehicle trajectory.