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

Armagan, Ersin; Kumbasar, Tufan

doi:10.5505/pajes.2018.77910

Cited by 4 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As noted by Chen et al (2021), the advantage of PID controllers is their ability to reduce computational load; this particular characteristic is significant for vehicles operating at high speeds. Recent studies have implemented customized PID controllers for high-speed longitudinal control systems (Gomes et al, 2017;Wang et al, 2018;Chen et al, 2020Chen et al, , 2021, lateral (steering) control systems (Armagan & Kumbasar, 2017;Zhang et al, 2018), and at least one previous study by Wang et al (2021) has utilized two PID controllers for both longitudinal and lateral control. Generally, the results of these works found that PID controllers provided favorable results for simulated racing vehicles.…”

Section: Applications Of Pid Controllers For Simulated Vehiclesmentioning

confidence: 99%

Assessment of an Autonomous Racing Controller: A Case Study From the Indy Autonomous Challenge ’ s Simulation Race

Kim

Cazares

Decker

et al. 2023

The Journal of Technology, Management, and Applied Engineering

View full text Add to dashboard Cite

The Indy Autonomous Challenge (IAC) was a competition among universities from around the world created to showcase fully autonomous operations under the extreme circumstances encountered in high-performance racing. The pinnacle of the virtual portion of the competition occurred on June 30,2021, during the IAC Simulation Race that consisted of a series of qualifying events followed by a head-to-head race. The objectives of this paper are to present a team’s controller and demonstrate its performance throughout the IAC until the final simulation race. The results presented in this paper were obtained by testing the team’s controller within a simulated environment. The final controller is capable of sustaining speeds of nearly 300 kph (186 mph) with an average speed of 280 kph(174 mph) and a maximum speed of 298 kph (185 mph). The final steering proportional-integral-derivative controller yielded cross-track errors no more than 4.7 meters from the desired waypoint. Analysis of the simulated vehicle’s G-G diagram reveals that the vehicle could sustain operations while experiencing over 2.5 Gs of lateral force as it navigated the turns of the track, and there is evidence to suggest that future work can be performed to tap into the full potential of the tires’ grip capabilities.The results presented in this report are indicative that the race team’s controller can perform safe high-speed operations in the presence of seven additional script-controlled opponents within a simulated environment.

show abstract

Section: Applications Of Pid Controllers For Simulated Vehiclesmentioning

confidence: 99%

Assessment of an Autonomous Racing Controller: A Case Study From the Indy Autonomous Challenge ’ s Simulation Race

Kim

Cazares

Decker

et al. 2023

The Journal of Technology, Management, and Applied Engineering

View full text Add to dashboard Cite

show abstract

“…S. E. Ovur et al solved the inverted pendulum problem with a fuzzy logic system [13]. E. Armağan and T. Kumbasar designed a fuzzy system for autonomous vehicle control [14]. A. Yılmaz et al performed a risk analysis for cancer disease using the fuzzy logic method [15].…”

Section: Introductionmentioning

confidence: 99%

Farklı Malzemelerin Quadcopterde Yükseklik Performansına Etkisi

KILIÇTEK,

ŞAHİN,

AKGÜMÜŞ GÖK

et al. 2023

Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi

View full text Add to dashboard Cite

Bu çalışmada quadcopter yüksekliğine çeşitli malzemelerin etkileri incelenmiştir. Yapılan quadcopter tasarımının gövdesi üzerine polisten, kabon elyaf takviyeli epoksi kompozit ve alüminyum 7075 alaşımı SolidWorks ortamında eklenmiştir. Kanatları ve motorları taşıyan kollar da ise gövde malzemesinden bağımsız olarak polistren kullanılmıştır. Eklenen malzemelere göre quadcopterde kütle hesaplamaları yapılmıştır. Bu hesaplamalar ışığında quadcopter yükseklik kontrolü için bulanık mantık tabanlı PD kontrolör kullanılmıştır. Bulanık mantık tabanlı PD’nin giriş-çıkış kazançları referans yükseklik değerlerine göre elle ayarlanıp Matlab-Simulink ortamında deneyler gerçekleştirilmiştir. Deneylerde referans yükseklikleri sırasıyla 1 m,1-0.5 m 2.5 m ve 5 m olmak üzere dört farklı değer kullanılmıştır. Yapılan deney sonuçları göstermiştir ki, gövdesinde polistren malzeme kullanılan dron modeli kullanılan referans değerlerinde diğer malzemelere göre başarılı sonuçlar vermiştir.

show abstract

“…To overcome these aspects, researchers have tested their self-driving car systems in games as they provide dynamic, cheap, realistic, and convenient testbeds. In this context, various self-driving car systems have been proposed that are tested in racing game environments such as The Open Racing Car Simulator (TORCS) (Armagan and Kumbasar, 2017; Wang and Liaw, 2015), JavaScript Racer (Yu et al, 2016), VDrift (Kehrle et al, 2011), and World Rally Championship 6 (Perot et al, 2017). Kehrle et al, (2011) designed a nonlinear model predictive control that uses model mismatch between the physical model and an approximate coarser model.…”

Section: Introductionmentioning

confidence: 99%

“…Kehrle et al, (2011) designed a nonlinear model predictive control that uses model mismatch between the physical model and an approximate coarser model. In Armagan and Kumbasar (2017), a fuzzy logic-based autonomous vehicle control system has been designed for the TORCS environment. In this structure, a fuzzy logic-based throttle/brake control system has been implemented to make the car capable to accelerate/decelerate in a realistic manner at desired velocity.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, lane tracking is also an important problem as it is needed for the lateral control of the self-driving car. Various methods have been proposed and employed to generate position reference trajectory based on lane tracking systems such as deep reinforcement learning (Yu et al, 2016), neural network (Kim, 2008) and fuzzy logic (Armagan and Kumbasar, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A fuzzy logic-based autonomous car control system for the JavaScript Racer game

Etlik

Korkmaz

Beke

et al. 2019

Transactions of the Institute of Measurement and Control

Self Cite

View full text Add to dashboard Cite

In this study, we propose a fuzzy logic-based autonomous car control system and its deployment into the JavaScript Racer game. The main design goal of the self-driving car control system is to end up with an intelligent vehicle control system that is capable to keep the car finish race in the shortest time as possible while keeping the car on the road course regardless the road conditions. To accomplish such a design goal, the proposed intelligent driving system takes up and merges the frameworks of control theory, fuzzy logic and image processing. The proposed structure is composed of vision-based lane detection system, fuzzy logic-based position reference (FPR) generator, fuzzy logic-based velocity reference (FVR) generator, low level position and velocity controllers. The vision-based lane detection system solves the road curve estimation problem in real time and provides this estimation feedback for the FPR and FVR to generate appropriate position and velocity reference signals. The design of the intelligent FPR and FVR generators is accomplished by converting expert knowledge into fuzzy rules. The generated reference signals from the FPR and FVR are then tracked by low level position and velocity controllers. The proposed structure is capable to percept the environment (i.e. road tracking), make decisions (reference signal generation) and control car dynamics (i.e. speed and position) as expected from an autonomous system. The paper presents the structure and design of the intelligent driving system by providing all the design steps in detail. The efficiency of the fuzzy logic-based car control system is shown with results collected from the game environment. It is revealed that the developed intelligent system can successfully operate in various racetracks and different operating points.

show abstract

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

Cited by 4 publications

References 8 publications

Assessment of an Autonomous Racing Controller: A Case Study From the Indy Autonomous Challenge ’ s Simulation Race

Assessment of an Autonomous Racing Controller: A Case Study From the Indy Autonomous Challenge ’ s Simulation Race

Farklı Malzemelerin Quadcopterde Yükseklik Performansına Etkisi

A fuzzy logic-based autonomous car control system for the JavaScript Racer game

Contact Info

Product

Resources

About