Paper Info
Title
Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions.
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.
Year
DOI
Venue
2018
10.3390/a11070108
ALGORITHMS
Keywords
Field
DocType
autonomous vehicles,automated steering,slippery road conditions,PID controllers,genetic programming
Mathematical optimization,Control theory,Heuristic,PID controller,Quality of control,Evolutionary computation,Genetic programming,Implementation,Control engineering,Mathematics
Journal
Volume
Issue
Citations 
11
7
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Natalia Alekseeva100.68
Ivan Tanev227846.51
Katsunori Shimohara3327106.53