TORCS oyun ortamında bulanık mantık tabanlı akıllı bir otonom araç kontrol sistemi tasarımı

Öz

Bu çalışmada TORCS (The Open Racing Car Simulator) oyun ortamında bulanık mantık tabanlı otonom araç kontrol sistemi tasarımı yapılmıştır. Bu çalışmadaki amaç, aracın yol bariyerlerine çarpasını engelleyerek hiçbir zarar almadan ve yol sınırları içerisinde kalmasını sağlayarak pistin dışına çıkmadan yarışı tamamlamasıdır. Bu bağlamda, aracın otonom bir şekilde ilerleyebilmesi için bulanık mantık ve klasik kontrol yapılarından oluşan akıllı bir sistem geliştirilmiştir. Aracın vites geçişleri otomatik hale getirildikten sonra aracın gerçekçi bir şekilde hızlanması/yavaşlamasını sağlamak ve de aracın sabit bir hızda gitmesi için bulanık mantık tabanlı bir gaz/fren kontrol sistemi tasarlanmıştır. Ayrıca, aracın pistin dışına çıkmadan ilerleyebilmesi ve de virajlarda pist içinde kalabilmesi için bulanık mantık tabanlı bir direksiyon kontrol sistemi geliştirilmiştir. Geliştirilen bu uzman tabanlı sistem sayesinde, aracın önünde bulunan virajın yönüne ve keskinliğine göre de aracın bulunması gereken uygun pozisyon hesaplanmıştır. Geliştirilen akıllı kontrol sistemin oyun performansına https://youtu.be/qOvEz3-PzRo bağıntısından ulaşılabilir.

Anahtar Kelimeler

• Akıllı kontrol sistemler,Bulanık mantık,Benzetim,TORCS

A fuzzy logic based intelligent autonomous vehicle control system design in the TORCS game environment

Abstract

In this study, a fuzzy logic based autonomous vehicle control system is designed and tested in The Open Racing Car Simulator (TORCS) environment. The purpose of this study is that vehicle complete the race without to get any damage with preventing to hit to the barriers and to go out of the way with staying in boundary of the road. In this context, an intelligent control system composed of fuzzy logic and conventional control structures has been developed such that the racing car is able to compete the race autonomously. Once the vehicle's gearshifts have been automated, a fuzzy logic based throttle/brake control system has been designed such that the racing car is capable to accelerate/decelerate in a realistic manner as well as to drive at desired velocity. The steering control problem is also handled to end up with a racing car that is capable to travel on the road even in the presence of sharp curves. In this context, we have designed a fuzzy logic based positioning system that uses the knowledge of the curvature ahead to determine an appropriate positon. The game performance of the developed intelligent control system can be observed from https://youtu.be/qOvEz3-PzRo

Keywords

• Intelligent control systems,Fuzzy logic,Simulation,TORCS

Kaynakça

1. Wymann B, Espié E, Guionneau C, Dimitrakakis C, Coulom R, Sumner A. “TORCS: The Open Racing Car Simulator”. http://torcs.sourceforge.net (13.10.2016).
2. Muñoz J, Gutierrez G, Sanchis A. “Controller for TORCS created by imitation”. IEEE Symposium on Computational Intelligence and Games, Milan, Italy, 7-10 September 2009.
3. Muñoz J, Gutierrez G, Sanchis A. “A human-like TORCS controller for the Simulated Car Racing Championship”. IEEE Conference on Computational Intelligence and Games, Kopenhag, Denmark, 18-21 August 2010.
4. Cardamone L, Loiacono D, Lanzi PL. “Learning Drivers for TORCS through Imitation Using Supervised Methods”. IEEE Symposium on Computational Intelligence and Games, Milan, Italy, 7-10 September 2009.
5. Loiacono D, Prete A, Lanzi PL, Cardamone L. “Learning to Overtake in TORCS Using Simple Reinforcement Learning”. IEEE Congress on Evolutionary Computation, Barselona, Spain, 18-23 July 2010.
6. Butz MV, Lönneker TD. “Optimized Sensory-motor Couplings plus Strategy Extensions for the TORCS Car Racing Challenge”. IEEE Symposium on Computational Intelligence and Games, Milan, Italy, 7-10 September 2009.
7. Lun TW, Leary J. “School of Environment and Technology MSC Automotive Engineering MEM47 Automotive Project. University of Brighton”. http://itsuite.it.brighton.ac.uk/jjl/reports/torcs1.pdf (13.10.2016).
8. Onieva E, Pelta DA, Alonso J, Milanés V, Pérez J. “A modular parametric architecture for the TORCS racing engine”. IEEE Symposium on Computational Intelligence and Games, Milan, Italy, 7-10 September 2009.

9. Kemmerling M, Preuss M. “Automatic adaptation to generated content via car setup optimization in TORCS”. IEEE Conference on Computational Intelligence and Games, Kopenhag, Denmark, 18-21 August 2010.
10. Preuss M, Quadflieg J, Rudolph G. “TORCS sensor noise removal and multi-objective track selection for driving style adaptation”. IEEE Conference on Computational Intelligence and Games, Seul, Güney Kore, 31 August.-3 September 2011.
11. Kim TS, Na JC, Kim KJ. “Optimization of an autonomous car controller using a self-adaptive evolutionary strategy". International Journal of Advanced Robotic Systems, 9(73), 1-15, 2012.
12. Kim KJ, Seo JH, Park JG, Na JC. “Generalization of TORCS car racing controllers with artificial neural networks and linear regression analysis”. Neurocomputing, 88, 87-99, 2012.
13. Yakami G, Tanev I, Shimohara K, Katagiri S, Ohsaki, M. "Automobile driving support system evolved by Genetic Programming". Region 10 Conference (TENCON), Singapur, Singapur, 22-25 November 2016.
14. Onieva E, Pelta DA, Milanés V, Pérez J. “A fuzzy-rule-based driving architecture for non-player characters in a car racing game”. Soft Computing, 15(8), 1617–1629, 2011.
15. McAree O. “TORCSLink”. https://github.com/VerifiableAutonomy/TORCSLink (13.10.2016).
16. Åström K, Hägglund T. Advanced PID Control, New York, USA, ISA, 2005.
17. Wymann B. “Torcs Robot Tutorial”. http://www.berniw.org/tutorials/robot/tutorial.html” (13.10.2016).