This work describes the development and evaluation of a recognizer for different levels of
cognitive workload in the car. We collected multiple biosignal streams (skin conductance,
pulse, respiration, EEG) during an experiment in a driving simulator in which the drivers
performed a primary driving task and several secondary tasks of varying difficulty. From this
data, an SVM based workload classifier was trained and evaluated, yielding recognition
rates of up to for three levels of workload.