Autonomous Taxi Driving Environment Using Reinforcement Learning Algorithms

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Deep Reinforcement Learning framework for Autonomous Driving

Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes. Despite its perceived utility, it has not yet been successfully applied in automotive applications. Motivated by the successful demonstrations of learning of Atari games and Go by Google DeepMind, we propose a framework fo...

متن کامل

Application of Reinforcement Learning Algorithms for Predicting Taxi-out Times

Accurate estimation of taxi-out time in the presence of uncertainties in the National Airspace System (NAS) is essential for the development of a more efficient air traffic management system. The dynamic nature of operations in the NAS indicates that traditional regression methods characterized by constant parameters would be inadequate to capture variations in taxi-out time across a day. In th...

متن کامل

Virtual to Real Reinforcement Learning for Autonomous Driving

Reinforcement learning is considered as a promising direction for driving policy learning. However, training autonomous driving vehicle with reinforcement learning in real environment involves non-affordable trial-and-error. It is more desirable to first train in a virtual environment and then transfer to the real environment. In this paper, we propose a novel realistic translation network to m...

متن کامل

Autonomous Driving in Reality with Reinforcement Learning and Image Translation

Supervised learning is widely used in training autonomous driving vehicle. However, it is trained with large amount of supervised labeled data. Reinforcement learning can be trained without abundant labeled data, but we cannot train it in reality because it would involve many unpredictable accidents. Nevertheless, training an agent with good performance in virtual environment is relatively much...

متن کامل

Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving

Autonomous driving is a multi-agent setting where the host vehicle must apply sophisticated negotiation skills with other road users when overtaking, giving way, merging, taking left and right turns and while pushing ahead in unstructured urban roadways. Since there are many possible scenarios, manually tackling all possible cases will likely yield a too simplistic policy. Moreover, one must ba...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: International Journal of Modern Education and Computer Science

سال: 2022

ISSN: ['2075-0161', '2075-017X']

DOI: https://doi.org/10.5815/ijmecs.2022.03.06