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Minimization of Systemic Risk for Directed Network Using Genetic Algorithm Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Driving in TORCS Using Modular Fuzzy Controllers

Authors : Mohammed Salem, Antonio Miguel Mora, Juan Julian Merelo, Pablo García-Sánchez

Published in: Applications of Evolutionary Computation

Publisher: Springer International Publishing

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Abstract

When driving a car it is essential to take into account all possible factors; even more so when, like in the TORCS simulated race game, the objective is not only to avoid collisions, but also to win the race within a limited budget. In this paper, we present the design of an autonomous driver for racing car in a simulated race. Unlike previous controllers, that only used fuzzy logic approaches for either acceleration or steering, the proposed driver uses simultaneously two fuzzy controllers for steering and computing the target speed of the car at every moment of the race. They use the track border sensors as inputs and besides, for enhanced safety, it has also taken into account the relative position of the other competitors. The proposed fuzzy driver is evaluated in practise and timed races giving good results across a wide variety of racing tracks, mainly those that have many turning points.

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Metadata
Title
Driving in TORCS Using Modular Fuzzy Controllers
Authors
Mohammed Salem
Antonio Miguel Mora
Juan Julian Merelo
Pablo García-Sánchez
Copyright Year
2017
Book
Applications of Evolutionary Computation

Print ISBN: 978-3-319-55848-6

Electronic ISBN: 978-3-319-55849-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-55849-3_24

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