In September 2007 the Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance (CTA) conducted an assessment of multiple pedestrian detection algorithms based upon LADAR or video sensor data. Eight detection algorithms developed by the Robotics CTA member organizations, including ARL, were assessed in an experiment conducted by the National Institute of Science & Technology (NIST) and ARL to determine the probability of detection/misclassification and false alarm rate as a function of vehicle speed, degree of environmental clutter, and pedestrian speeds. The study is part of an ongoing investigation of safe operations for unmanned ground vehicles. This assessment marked the first time in this program that human movers acted as targets for detection from a moving vehicle. A focus of the study was to choreograph repeatable human movement scenarios relative to the movement of the vehicle. The resulting data is intended to support comparative analysis across treatment conditions and to allow developers to examine performance with respect to specific detection and tracking events. Events include humans advancing and retreating from the vehicle at different angles, humans crossing paths in close proximity and occlusion situations where sight to the mover from the sensor system is momentarily lost. A detailed operational procedure ensured repeatable human movement with independent ground truth supplied by a NIST ultra wideband wireless tracking system. Post processing and statistical analysis reconciled the tracking algorithm results with the NIST ground truth. We will discuss operational considerations and results.