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Human Performance Profiling While Driving a Sidestick-Controlled Car

  • Ljubo MercepEmail author
  • Gernot Spiegelberg
  • Alois Knoll
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

We have established a metric for measuring human performance while operating a sidestick-controlled car and have used it in conjunction with a known environment type to identify unusual steering trends. We focused on the analysis of the vehicle’s offset from the lane center in the time domain and identified a set of this signal’s features shared by all test drivers. The distribution of these features identifies a specific driving environment type and represents the essence of the proposed metric. We assumed that the driver performance, while operating a sidestick-controlled car, is determined by the environment type on one side and the driver’s own mental state on the other. The goal is to detect the mismatch of the assumed driving environment, gained from the introduced metric, and a ground truth about the actual environmental type, which can be obtained through map and GPS data, in order to identify unusual steering trend possibly caused by a change in driver fitness.

Keywords

Driving Environment Road Vehicle Environment Type Driver Performance Road Profile 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Buckl, C., Camek, A., Kainz, G., Simon, C., Mercep, Lj., Staehle, H., et al. (2012). The software car: Building ICT architectures for future electric vehicles. In IEEE Electric Vehicle Conference (IEVC) 2012, Greenville.Google Scholar
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  3. Mercep, L., Spiegelberg, G., & Knoll, A. (2013). A case study on implementing future human-machine interfaces. In IEEE Intelligent Vehicles Symposium, Gold Coast.Google Scholar
  4. Spiegelberg, G. (2005). Advantage in integration and active safety by using drive-by-wire technologies. In Results of EU-Project PEIT and SPARC, Autotec 2005, Stuttgart.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Institute for Informatics, Chair for Robotics and Embedded SystemsTechnische Universität MünchenMünchenGermany
  2. 2.Institute for Advanced Study der Technischen Universität München / Siemens AGMünchenGermany

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