Driverless car: Autonomous driving using deep reinforcement learning in urban environment
Deep Reinforcement Learning has led us to newer possibilities in solving complex control
and navigation related tasks. The paper presents Deep Reinforcement Learning …
and navigation related tasks. The paper presents Deep Reinforcement Learning …
Autonomous braking system via deep reinforcement learning
In this paper, we propose a new autonomous braking system based on deep reinforcement
learning. The proposed autonomous braking system automatically decides whether to apply …
learning. The proposed autonomous braking system automatically decides whether to apply …
Autonomous driving system based on deep q learnig
T Okuyama, T Gonsalves… - … conference on intelligent …, 2018 - ieeexplore.ieee.org
This paper deals with the simulation results of an autonomous car learning to drive in a
simplified environment containing only lane markings and static obstacles. Learning is …
simplified environment containing only lane markings and static obstacles. Learning is …
Human-like autonomous vehicle speed control by deep reinforcement learning with double Q-learning
Y Zhang, P Sun, Y Yin, L Lin… - 2018 IEEE intelligent …, 2018 - ieeexplore.ieee.org
Autonomous driving has become a popular research project. How to control vehicle speed is
a core problem in autonomous driving. Automatic decision-making approaches, such as …
a core problem in autonomous driving. Automatic decision-making approaches, such as …
Driving decision and control for automated lane change behavior based on deep reinforcement learning
To fulfill high-level automation, an automated vehicle needs to learn to make decisions and
control its movement under complex scenarios. Due to the uncertainty and complexity of the …
control its movement under complex scenarios. Due to the uncertainty and complexity of the …
Self-driving cars using CNN and Q-learning
SOA Chishti, S Riaz, M BilalZaib… - 2018 IEEE 21st …, 2018 - ieeexplore.ieee.org
DrivingMatter is an experiment carried out to understand the deeper side of an autonomous
car. In 1900s, idea was to drive car on Moon from Earth. This was initial motivation which …
car. In 1900s, idea was to drive car on Moon from Earth. This was initial motivation which …
Learning how to drive in a real world simulation with deep q-networks
We present a reinforcement learning approach using Deep Q-Networks to steer a vehicle in
a 3D physics simulation. Relying solely on camera image input the approach directly learns …
a 3D physics simulation. Relying solely on camera image input the approach directly learns …
[HTML][HTML] Deep reinforcement learning based control for Autonomous Vehicles in CARLA
Ó Pérez-Gil, R Barea, E López-Guillén… - Multimedia Tools and …, 2022 - Springer
Abstract Nowadays, Artificial Intelligence (AI) is growing by leaps and bounds in almost all
fields of technology, and Autonomous Vehicles (AV) research is one more of them. This …
fields of technology, and Autonomous Vehicles (AV) research is one more of them. This …
End-to-end deep reinforcement learning for lane keeping assist
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 …
teach machines through interaction with the environment and learning from their mistakes …
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 …
teach machines through interaction with the environment and learning from their mistakes …