Simulation of Autonomous Vehicles in CARLA Simulator
| Autor: | Žalar, Leonardo |
|---|---|
| Přispěvatelé: | Čeperić, Vladimir |
| Jazyk: | chorvatština |
| Rok vydání: | 2020 |
| Předmět: |
reinforcement learning
TEHNIČKE ZNANOSTI. Računarstvo autonomna vožnja deep learning RGB camera autonomni auto RGB kamera simulation simulacija autonomous car Q-učenje strojno učenje potporno učenje self-driving car machine learning autonomous driving TECHNICAL SCIENCES. Computing Q-learning samovozeći automobil duboko učenje GTA V CARLA lidar radar |
| Popis: | Područje autonomnih vozila bilo je veoma zanimljivo za mnoge istraživačke skupine i proizvođače automobila te ima dugu povijest razvoja. Izgradanja prototipova autonomnih vozila je skupa te nije moguće u stvarnom svijetu prototip isprobati u mnogim situacijama zato što bi bile preopasne. Stoga, simulatori za autonomna vozila dopuštaju nam brži i jeftiniji razvoj te omogućuju podvrgavanje autonomnih agenata situacijama koje su preopasne u stvarnosti. CARLA je simulator urbane vožnje otvorenog koda izgrađen za razvoj, treniranje te validaciju autonomnih vozila. CARLA simulator ima velik broj ugrađenih senzora. Kako bi simulirali autonomnu vožnju trenirana su 3 različita agenta dubokim Q-učenjem u CARLA simulatoru te svaki koristi drugačiji senzor za navigiranje okolinom. Od senzora korišteni su RBG kamera, radar i lidar. The field of autonomous vehicles has been very interesting for many research groups and car manufactures for a long time and has a rich history of development. Building autonomous vehicle prototypes is costly and it's not possible for the prototype to be tested under all circumstances because it would be too dangerous. Autonomous vehicle simulators allow for faster and cheaper development of autonomous vehicles and enable us to test our simulated car in situations that would be too dangerous in real life. CARLA is an open urban driving simulator built for the development, training and validation of autonomous vehicles. CARLA has a lot of in-built sensors. In order to simulate autonomous driving, 3 different agents have been trained with deep Q-learning in the CARLA simulator and each agent used a different sensor to navigate in the environment, the sensors that have been used are: RGB camera, lidar and radar. |
| Databáze: | OpenAIRE |
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