@inproceedings{schneegass2013data,, title = {A data set of real world driving to assess driver workload},, author = { Stefan Schneegass and Bastian Pfleging and Nora Broy and Frederik Heinrich and Albrecht Schmidt},, url = {http://www.hcilab.org/research/hcilab-driving-dataset/, http://dx.doi.org/10.1145/2516540.2516561},, doi = {10.1145/2516540.2516561},, isbn = {978-1-4503-2478-6},, year = {2013},, date = {2013-01-01},, booktitle = {Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications},, pages = {150--157},, publisher = {ACM},, address = {New York, NY, USA},, series = {AutomotiveUI '13},, abstract = {, Driving a car is becoming increasingly complex. Many new features (e.g., for communication or entertainment) that can be used in addition to the primary task of driving a car increase the driver's workload. Assessing the driver's workload, however, is still a challenging task. A variety of means are explored which rather focus on experimental conditions than on real world scenarios (e.g., questionnaires). We focus on physiological data that may be assessed in an non-obtrusive way in the future and is therefore applicable in the real world., , Hence, we conducted a real world driving experiment with 10 participants measuring a variety of physiological data as well as a post-hoc video rating session. We use this data to analyze the differences in the workload in terms of road type as well as especially important parts of the route such as exits and on-ramps. Furthermore, we investigate the correlation between the objective assessed and subjective measured data., },, keywords = {},, pubstate = {published},, tppubtype = {inproceedings}, }