In recent years, deep learning as a subfield of machine learning has gained increasing attention due to its potential advantages in empowering autonomous systems with the ability to automatically learn underlying features in data at different levels of abstractions, to build complex concepts out of ...
Providing autonomous systems with an effective quantity and quality of information from a desired task is challenging. In particular, autonomous vehicles, must have a reliable vision of their workspace to robustly accomplish driving functions. Speaking o
However, for autonomous vehicles to go into mass production, it is critical to ensure that they are safe, reliable, and viable, and in such a scenario, deep learning technology may well be the answer. Over the next few years, we can envisage cost-effective, efficient, and reliable vehicles...
7. Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning 8. Reinforcement Learning with A* and a Deep Heuristic 4.1 状态空间、动作空间和奖励 为了成功地将 DRL 应用于自动驾驶任务,设计适当的状态空间、动作空间和奖励函数非常重要。 状态空间 自动驾驶汽车常用的状态空间特征...
REINFORCEMENT LEARNING FOR AUTONOMOUS DRIVING TASKS 可应用RL的自主驾驶任务包括:控制器优化、路径规划和轨迹优化、运动规划和动态路径规划、为复杂导航任务制定高级驾驶策略、基于场景的高速公路、交叉口、汇聚和分叉路口的策略学习,基于专家数据的反逆强化学习的奖励学习,用于预测行人、车辆等交通参与者的意图,并最终学习...
Convolutional Neural Networks for End-to-End Learning of the full driving tasks(用于全驾驶任务端到端学习的卷积神经网络) Recurrent Neural Networks for Steering Through Time(循环神经网络与时序驾驶操纵) Deep Learning for Human-Centered Semi-Autonomous Vehicles(以人为中心的半自主驾驶深度学习) ...
Convolutional Neural Networks for End-to-End Learning of the full driving tasks(用于全驾驶任务端到端学习的卷积神经网络) Recurrent Neural Networks for Steering Through Time(循环神经网络与时序驾驶操纵) Deep Learning for Human-Centered Semi-Autonomous Vehicles(以人为中心的半自主驾驶深度学习) ...
The growing need for autonomous vehicles in the offroad space raises certain complexities that need to be considered more rigorously in comparison to onroa... A Joglekar,S Sathe,SV Krovi - 《Ifac Papersonline》 被引量: 0发表: 2022年 Deep Reinforcement Learning for Perception and Control of A...
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 23, NO. 1, JANUARY 2022 33 Deep Learning-Based Vehicle Behavior Prediction for Autonomous Driving Applications: A Review Sajjad Mozaffari , Omar Y. Al-Jarrah , Mehrdad Dianati , Senior Member, IEEE , Paul Jennings, and Alexandros Mouzak...
The design of autonomous vehicles will bring together many modern technologies such as control, computer vision, path planning, sensor fusion and fault diagnosis. Although traditional algorithms can be used to implement these technologies, in the last decade, deep learning has been proposed to ...