The main goal of the distraction and drowsiness field study was to evaluate a system for detecting driver distraction and drowsiness. This report focuses on the system implementation and the algorithms detecting distraction and drowsiness. A vehicle was instrumented with video cameras, an automatic eye tracker and GPS receivers. Further data were read from the CAN bus of the car. The data were logged continuously with high frequency. The log system operated autonomously. Seven participants drove the vehicle during one month each. During the first ten days a behavioural baseline was collected. Afterwards the warnings were activated, such that the drivers received distraction warnings in form of a vibration in the seat when the algorithm determined that they had looked away from the forward roadway too much. A separate algorithm judged whether the drivers were drowsy or not. Questionnaires were administered on three occasions during the course of the study. No major problems were encountered during the field operational test (FOT), but a number of smaller problems had to be solved. However, in the end of the data collection period the computer installed in the car became more and more unstable, which led to increased data loss.