Skip to main content

Autonomous Driving with Multiple Hypothesis Testing

  • Chapter
  • First Online:
MATLAB Machine Learning Recipes

Abstract

There are two elements to this problem. One is to model the motion of the tracked automobiles using measurements to improve your estimate of each automobile’s location and velocity. The second is to systematically assign measurements to different tracks. A track should represent a single car, but the radar is just returning measurements on echoes, it doesn’t know anything about the source of the echoes.

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 34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Matthew G. Villella. Nonlinear Modeling and Control of Automobiles with Dynamic Wheel-Road Friction and Wheel Torque Inputs. PhD thesis, Georgia Institute of Technology, April 2004.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Michael Paluszek and Stephanie Thomas

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Paluszek, M., Thomas, S. (2019). Autonomous Driving with Multiple Hypothesis Testing. In: MATLAB Machine Learning Recipes. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3916-2_13

Download citation

Publish with us

Policies and ethics