Skip to main content

Development of a Driver-State Adaptive Co-Driver as Enabler for Shared Control and Arbitration

  • 928 Accesses

Part of the Communications in Computer and Information Science book series (CCIS,volume 1294)

Abstract

For automated and partially automated cars, there are new crucial questions to answer: “When should the driver or the automated system take control of the vehicle?" ; and also: “Can both control the vehicle together at the same time, or can this create potential conflicts?" . These are non-trivial issues because they depend on different conditions, such as the environment, driver’s state, vehicle capabilities, and fault tolerance, among others. This paper will describe a human-machine cooperation approach for collaborative driving maneuvers, developed in the EU funded project PRYSTINE. In particular, this study presents the work-in-progress and will focus attention on the proposed architecture design and the corresponding use case for testing.

Keywords

  • Shared control
  • Arbitration
  • Highly automated vehicles
  • Human-machine cooperation.

PRYSTINE has received funding within the Electronic Components and Systems for European Leadership Joint Undertaking (ECSEL JU) in collaboration with the European Union’s H2020 Framework Programme and National Authorities, under grant agreement No. 783190.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-60703-6_69
  • Chapter length: 7 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-60703-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   149.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.

References

  1. National Highway Traffic Safety Administration, "Crash factors in intersection-related crashes: An on-scene perspective," Nat. Center Stat. Anal., National Highway Traffic Safety Administration, Washington, DC, USA, Technical Report DOT HS 811366 (2010). http://www-nrd.nhtsa.dot.gov/Pubs/811366.pdf

  2. Dong, Y., Hu, Z., Uchimura, K., Murayama, N.: Driver inattention monitoring system for intelligent vehicles: a review. IEEE Trans. Intell. Transp. Syst. 12(2), 596–614 (2010)

    CrossRef  Google Scholar 

  3. Yusoff, N.M., Ahmad, R.F., Guillet, C., Malik, A.S., Saad, N.M., Mérienne, F.: Selection of measurement method for detection of driver visual cognitive distraction: a review. IEEE Access 5, 22844–22854 (2017)

    CrossRef  Google Scholar 

  4. Gutjahr, B., Gröll, L., Werling, M.: Lateral vehicle trajectory optimization using constrained linear time-varying MPC. IEEE Trans. Intell. Transp. Syst. 18(6), 1586–1595 (2016)

    Google Scholar 

  5. Rodríguez-Ibíez, N., García-González, M. A., Fernández-Chimeno, M., Ramos-Castro, J: Drowsiness detection by thoracic effort signal analysis in real driving environments. In 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6055–6058. IEEE August 2011

    Google Scholar 

  6. Druml, N., et al.: PRYSTINE-technical progress after year 1. In: 22nd Euromicro Conference on Digital System Design (DSD), pp. 389–398 (2019)

    Google Scholar 

  7. Ficosa International SA. https://www.ficosa.com/es/productos/adas/somnoalert

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrea Castellano .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Castellano, A., Carbonara, G., Diaz, S., Marcano, M., Tango, F., Montanari, R. (2020). Development of a Driver-State Adaptive Co-Driver as Enabler for Shared Control and Arbitration. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2020 – Late Breaking Posters. HCII 2020. Communications in Computer and Information Science, vol 1294. Springer, Cham. https://doi.org/10.1007/978-3-030-60703-6_69

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-60703-6_69

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60702-9

  • Online ISBN: 978-3-030-60703-6

  • eBook Packages: Computer ScienceComputer Science (R0)