Survey of deep reinforcement learning for motion planning of autonomous vehicles
S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …
recent years related to several topics as sensor technologies, V2X communications, safety …
Artificial intelligence applications in the development of autonomous vehicles: A survey
The advancement of artificial intelligence (AI) has truly stimulated the development and
deployment of autonomous vehicles (AVs) in the transportation industry. Fueled by big data …
deployment of autonomous vehicles (AVs) in the transportation industry. Fueled by big data …
Intelligent total transportation management system for future smart cities
Smart mobility and transportation, in general, are significant elements of smart cities, which
account for more than 25% of the total energy consumption related to smart cities. Smart …
account for more than 25% of the total energy consumption related to smart cities. Smart …
[PDF][PDF] Hybrid DDPG approach for vehicle motion planning
The paper presents a motion planning solution which combines classic control techniques
with machine learning. For this task, a reinforcement learning environment has been …
with machine learning. For this task, a reinforcement learning environment has been …
Vehicle control in highway traffic by using reinforcement learning and microscopic traffic simulation
The paper presents a simple yet powerful and intelligent driver agent, designed to operate in
a preset highway situation using Policy Gradient Reinforcement Learning (RL) agent. The …
a preset highway situation using Policy Gradient Reinforcement Learning (RL) agent. The …
Driving on highway by using reinforcement learning with CNN and LSTM networks
This work presents a powerful and intelligent driver agent, designed to operate in a preset
highway situation using Policy Gradient Reinforcement Learning (RL) agent. Our goal is to …
highway situation using Policy Gradient Reinforcement Learning (RL) agent. Our goal is to …
Policy gradient based control of a pneumatic actuator enhanced with monte carlo tree search
This paper presents a synergy of the Monte-Carlo tree search (MCTS) and a reinforcement
learning (RL) based control strategy to achieve the position control of an electropneumatic …
learning (RL) based control strategy to achieve the position control of an electropneumatic …
Continuous Autonomous Ship Learning Framework for Human Policies on Simulation
Considering autonomous navigation in busy marine traffic environments (including harbors
and coasts), major study issues to be solved for autonomous ships are avoidance of static …
and coasts), major study issues to be solved for autonomous ships are avoidance of static …
Least-Violating Motion Planning for Traffic-Compliant Autonomous Driving
J Karlsson - 2022 - diva-portal.org
Over the last decade, autonomous vehicles has received an increasing amount of interest
from industries and research institutes. For autonomous vehicles to properly function …
from industries and research institutes. For autonomous vehicles to properly function …
A Neural Tangent Kernel Approach for Constrained Policy Gradient Reinforcement Learning
This paper presents a constrained policy gradient method where we introduce constraints
for safe learning, augmenting the traditional REINFORCE algorithm by taking the following …
for safe learning, augmenting the traditional REINFORCE algorithm by taking the following …