Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions
AbstractThe 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. View Full-Text
Share & Cite This Article
Alekseeva, N.; Tanev, I.; Shimohara, K. Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions. Algorithms 2018, 11, 108.
Alekseeva N, Tanev I, Shimohara K. Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions. Algorithms. 2018; 11(7):108.Chicago/Turabian Style
Alekseeva, Natalia; Tanev, Ivan; Shimohara, Katsunori. 2018. "Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions." Algorithms 11, no. 7: 108.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.