By Topic

Using Fuzzy Logic in Automated Vehicle Control

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Naranjo, J.E. ; Instituto de Autom. Industrial, Madrid ; Sotelo, M.A. ; Gonzalez, C. ; Garcia, R.
more authors

Automated versions of a mass-produced vehicle use fuzzy logic techniques to both address common challenges and incorporate human procedural knowledge into the vehicle control algorithms. In-vehicle computing has been largely relegated to auxiliary tasks such as regulating cabin temperature, opening doors, and monitoring fuel, oil, and battery-charge levels. However, computers are increasingly assuming driving-related tasks in some commercial models. Among those tasks are: maintaining a reference velocity or keeping a safe distance from other vehicles; improving night vision with infrared cameras; and building maps and providing alternative routes

Published in:

Intelligent Systems, IEEE  (Volume:22 ,  Issue: 1 )