- author = "Natalia Alekseeva and Ivan Tanev and Katsunori Shimohara",
- title = "Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions",
- journal = "Algorithms",
- year = "2018",
- volume = "11",
- number = "7",
- pages = "108",
- month = jul,
- note = "Special Issue Algorithms for PID Controller",
- keywords = "genetic algorithms, genetic programming, autonomous vehicles, automated steering, slippery road conditions, PID controllers",
- ISSN = "1999-4893",
-
URL = "
http://www.mdpi.com/1999-4893/11/7/108",
-
URL = "http://www.mdpi.com/1999-4893/11/7/108/pdf",
-
URL = "https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201902252618556627",
-
DOI = "
doi:10.3390/a11070108",
- size = "17 pages",
- abstract = "The most important characteristics of autonomous vehicles are their safety and their ability to adapt to various traffic situations and road conditions. In our research, we focused on the development of controllers for automated steering of a realistically simulated car in slippery road conditions. We comparatively investigated three implementations of such controllers: a proportional-derivative (PD) controller built in accordance with the canonical servo-control model of steering, a PID controller as an extension of the servo-control, and a controller designed heuristically via the most versatile evolutionary computing paradigm: genetic programming (GP). The experimental results suggest that the controller evolved via GP offers the best quality of control of the car in all of the tested slippery (rainy, snowy, and icy) road conditions.",
-
notes = "Department of Information Systems Design, Faculty of
Engineering, Doshisha University 1-3, Tatara
Miyakodani, Kyotanabe City, Kyoto 610-0394,
Japan
http://www.mdpi.com/journal/algorithms",
