Real-time deep reinforcement learning based vehicle navigation-Reference-Cited by-同舟云学术

Real-time deep reinforcement learning based vehicle navigation

Published:2020-11 Issue: Volume:96 Page:106694
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Koh Songsang,Zhou Bo,Fang Hui^ORCID,Yang Po^ORCID,Yang Zaili^ORCID,Yang Qiang^ORCID,Guan Lin,Ji Zhigang

Publisher

Elsevier BV

Subject

Software

Reference52 articles.

1. Recurring and Non-Recurring Congestion: Causes, Impacts, and Solutions;McGroarty,2010

2. Non-recurrent congestion: how big is the problem? Are traveler information systems the solution?;Hall;Transp. Res. C,1993

3. DxNAT—Deep neural networks for explaining non-recurring traffic congestion;Sun,2017

4. N. Zygouras, N. Panagiotou, N. Zacheilas, I. Boutsis, V. Kalogeraki, I. Katakis, D. Gunopulos, Towards detection of faulty traffic sensors in real-time, in: MUD@ ICML, 2015, pp. 53–62.

5. Optimal detection of faulty traffic sensors used in route planning;Ghafouri,2017

Cited by 69 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments;Applied Soft Computing;2024-11

2. C-SPPO: A deep reinforcement learning framework for large-scale dynamic logistics UAV routing problem;Chinese Journal of Aeronautics;2024-09

3. Effective State Space Exploration with Phase State Graph Generation and Goal-based Path Planning;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

4. Strategic data navigation: information value-based sample selection;Artificial Intelligence Review;2024-06-25

5. Traffic light recognition and V2I communications of an autonomous vehicle with the traffic light for effective intersection navigation using YOLOv8 and MAVS simulation;Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2024;2024-06-07