Skip to main content

Feature Classification of Skilled and Unskilled Persons in Car Driving Operation

  • Conference paper
  • First Online:
Advances in Human Aspects of Transportation (AHFE 2018)

Abstract

This study was conducted to find out exactly how experts are driving a car from objective data during driving operation, focusing on improving driving skills. Experiments were conducted using a sports sedan type experimental vehicle that can change the assist amount of the steering wheel, using a circumferential circuit having multiple curves in an automobile company. For the analysis, steering angle data obtained from the vehicle and electromyogram data obtained from an electromyograph are used. From the analysis of the steering angle, the skilled turn curves with less turning the steering compared to the unskilled. From the analysis of the steering angular velocity data and the steering angular acceleration data, it became possible to classify them into skilled and unskilled in the steering handle operation rhythm during driving. From the analysis of the electromyogram data, focusing on the triangular muscle on the push side during the curve, it became possible to classify into skilled and unskilled.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Dobashi: Analysis of experimental data in Car Driving Operation - Proposal of a method suitable for time series in-vehicle data. Japan Ergonomics Association Kanto branch 22nd graduation research presentation, Japan Ergonomics Association Kanto branch 22nd graduation research presentation lecture collection, pp. 168–169 (2016)

    Google Scholar 

  2. Sugawara: Analysis of electromyogram data in Car Driving Operation by time series analysis. Japan Ergonomics Association System Conference, Japan Ergonomics Association System Conference Committee (2017)

    Google Scholar 

  3. Try SVM using e1071 in R. http://d.hatena.ne.jp/kj-ki/20120117/p1

  4. Time series clustering starting at {TSclust}. http://sinhrks.hatenablog.com/entry/2014//16/194012

  5. Isomura, A.: Human factors on driver’s steering operation, society of automotive engineers of Japan. Society of Automotive Engineering Academic Lecture Conference preprinting, vol. 946, pp. 153–156 (1994)

    Google Scholar 

  6. Sumikawa: A Study of Steering Feeling Evaluation Method for Vehicle by Analyzing Muscular Activity and Steering Action. Society of Automotive Engineering 2016 Fall Conference (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Takuro Sugita .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sugita, T. et al. (2019). Feature Classification of Skilled and Unskilled Persons in Car Driving Operation. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2018. Advances in Intelligent Systems and Computing, vol 786. Springer, Cham. https://doi.org/10.1007/978-3-319-93885-1_68

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-93885-1_68

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93884-4

  • Online ISBN: 978-3-319-93885-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics