Add to ORKGAbstract: Research in the collaborative driving domain strives to create control systems that coordinate the motion of multiple vehicles in order to navigate traffic both efficiently and safely. In this paper a novel individual vehicle controller based on reinforcement learning is introduced. This controller is capable of both lateral and longitudinal control while driving in a multi-vehicle platoon. The design and development of this controller is discussed in detail and simulation results showing learning progress and performance are presented. Copyright © 2006 IFA
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
Abstract—Recently, improvements in sensing, communicating, and computing technologies have led to th...
Considering an increasing urbanization on a global scale, traffic congestion is becoming a progressi...
Research in the collaborative driving domain strives to create control systems that coordinate the m...
Research in the collaborative driving domain strives to create control systems that coordinate the m...
The research of reinforcement learning is increasing recently due to its application in different fi...
This paper presents a supervised reinforcement learning (SRL)-based framework for longitudinal vehic...
This paper presents a supervised reinforcement learning (SRL)-based framework for longitudinal vehic...
Self-driving cars have become a popular research topic in recent years. Autonomous driving is a comp...
Rapport stage masterThis paper considers the problem of longitudinal control of a linear platoon and...
Dynamic Collaborative Driving is the concept of decentralized multi-vehicle automated driving where ...
With the development of artificial intelligence and autonomous driving technology, the vehicle-road ...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
Abstract—Recently, improvements in sensing, communicating, and computing technologies have led to th...
Considering an increasing urbanization on a global scale, traffic congestion is becoming a progressi...
Research in the collaborative driving domain strives to create control systems that coordinate the m...
Research in the collaborative driving domain strives to create control systems that coordinate the m...
The research of reinforcement learning is increasing recently due to its application in different fi...
This paper presents a supervised reinforcement learning (SRL)-based framework for longitudinal vehic...
This paper presents a supervised reinforcement learning (SRL)-based framework for longitudinal vehic...
Self-driving cars have become a popular research topic in recent years. Autonomous driving is a comp...
Rapport stage masterThis paper considers the problem of longitudinal control of a linear platoon and...
Dynamic Collaborative Driving is the concept of decentralized multi-vehicle automated driving where ...
With the development of artificial intelligence and autonomous driving technology, the vehicle-road ...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
The vehicle platoon will be the most dominant driving mode on future roads. To the best of our knowl...
Abstract—Recently, improvements in sensing, communicating, and computing technologies have led to th...
Considering an increasing urbanization on a global scale, traffic congestion is becoming a progressi...