Design and simulation of vehicle controllers through genetic algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@Article{VILORIA:2020:procs,

• author = "Amelec Viloria and Nelson Alberto {Lizardo Zelaya} and Noel Varela",
• title = "Design and simulation of vehicle controllers through genetic algorithms",
• journal = "Procedia Computer Science",
• volume = "175",
• pages = "453--458",
• year = "2020",
• note = "The 17th International Conference on Mobile Systems and Pervasive Computing (MobiSPC),The 15th International Conference on Future Networks and Communications (FNC),The 10th International Conference on Sustainable Energy Information Technology",
• ISSN = "1877-0509",
• DOI = "doi:10.1016/j.procs.2020.07.064",
• URL = "http://www.sciencedirect.com/science/article/pii/S1877050920317452",
• keywords = "genetic algorithms, genetic programming, Design, simulation, Vehicle controllers",
• abstract = "Genetic Programming (GP) is a population-based evolutionary technique, which, unlike a Genetic Algorithm (GA) does not work on a fixed-length data structure, but on a variable-length structure and aims to evolve functions, models or programs, rather than finding a set of parameters. There are different histories of driver development, so different proposals of the use of PG to evolve driver structures are presented. In the case of an autonomous vehicle, the development of a steering controller is complex in the sense that it is a non-linear system, and the control actions are very limited by the maximum angle allowed by the steering wheels. This paper presents the development of an autonomous vehicle controller with Ackermann steering evolved by means of Genetic Programming",

}

Genetic Programming entries for Amelec Viloria Nelson Alberto Lizardo Zelaya Noel Varela

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