Trucking fleets are increasingly installing video event recorders in their vehicles. The video event recorder system is usually mounted near the vehicle's rear view mirror, and consists of two cameras: one looking forward and one looking towards the driver. The system also contains accelerometers that record lateral and longitudinal g-loading, and some may record vehicle speed (in mph) based on GPS positions. The unit constantly monitors vehicle acceleration and speed, and also records video. However, the recorded data is only stored when a preset acceleration threshold is met. The primary use of the system is to assist fleets with driver training and education, but the recorded data is also being used as a tool to reconstruct accidents. By integrating the accelerometer data, the vehicle speed and distance traveled during the event can be calculated. However, the calculated speeds and distances from video event recorder data may differ from reconstructions based on data taken from engine control modules (ECM's) or classic reconstruction techniques. The objective of this study was to determine the source(s) of these differences and to determine whether or not the differences could be accounted for and corrected. Results of the study indicate that the differences can be corrected by analyzing the recorded video and matching the calculated results to known vehicle speeds, i.e., when the vehicle comes to rest. In cases where the vehicle does not come to rest during the recorded event, the differences can only be corrected if the vehicle in question can be accurately modeled.