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Auxiliary Network Enhanced Hierarchical Graph Reinforcement Learning for Vehicle Repositioning
期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 页码: 13
作者:
Xi, Jinhao
;
Zhu, Fenghua
;
Ye, Peijun
;
Lv, Yisheng
;
Xiong, Gang
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2024/07/03
Mobility-on-demand system
vehicle repositioning
hierarchical graph reinforcement learning
auxiliary graph reinforcement learning
Autonomous Vehicle Platoons In Urban Road Networks: A Joint Distributed Reinforcement Learning and Model Predictive Control Approach
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 141-156
作者:
Luigi D’Alfonso
;
Francesco Giannini
;
Giuseppe Franzè
;
Giuseppe Fedele
;
Francesco Pupo
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/01/02
Distributed model predictive control
distributed reinforcement learning
routing decisions
urban road networks
Self-Organized Routing for Autonomous Vehicles via Deep Reinforcement Learning
期刊论文
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2024, 卷号: 73, 期号: 1, 页码: 426-437
作者:
Pei, Huaxin
;
Zhang, Jiawei
;
Zhang, Yi
;
Xu, Huile
;
Li, Li
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2024/07/03
Routing
Autonomous vehicles
Vehicle-to-everything
Vehicle dynamics
Estimation
Automation
Traffic congestion
self-organized
deep reinforcement learning
autonomous vehicle
Spatio-Temporal Transformer with Clustering and Dilated Attention for Traffic Prediction
会议论文
Bilbao, Bizkaia, Spain, 2023-4
作者:
Xu BW(许宝文)
;
Wang XL(王学雷)
;
Liu CB(刘承宝)
;
Li S(李铄)
;
Li JW(李经纬)
收藏
  |  
浏览/下载:0/0
  |  
提交时间:2024/06/26
Optimized Multicar Dynamic Route Planning Based on Time-Hierarchical Graph Model
期刊论文
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2023, 页码: 15
作者:
Song, Qing
;
Li, Xiaolei
;
Gao, Chao
;
Shen, Zhen
;
Xiong, Gang
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2023/11/16
Automobiles
Planning
Roads
Vehicles
Optimization
Computer architecture
Real-time systems
Hierarchical Multi-Objective Optimization for Dedicated Bus Punctuality and Supply-Demand Balance Control
期刊论文
SENSORS, 2023, 卷号: 23, 期号: 9, 页码: 18
作者:
Shang, Chunlin
;
Zhu, Fenghua
;
Xu, Yancai
;
Liu, Xiaoming
;
Jiang, Tianhua
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2023/11/17
intelligent transportation system
hierarchical multi-objective optimization
driving speed decision-making
dedicated bus
Lagrangian multiplier method
Network-Wide Traffic Signal Control Based on MARL With Hierarchical Nash-Stackelberg Game Model
期刊论文
IEEE ACCESS, 2023, 卷号: 11, 页码: 145085-145100
作者:
Shen, Hui
;
Zhao, Hongxia
;
Zhang, Zundong
;
Yang, Xun
;
Song, Yutong
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2024/02/22
Games
Roads
Approximation algorithms
Q-learning
Multi-agent systems
Process control
Optimization
Reinforcement learning
Traffic control
Network-wide traffic signal control
hierarchical game model
multi-agent reinforcement learning
Sharing Traffic Priorities via Cyber-Physical-Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 页码: 12
作者:
Li, Bai
;
Cao, Dongpu
;
Tang, Shiqi
;
Zhang, Tantan
;
Dong, Hairong
收藏
  |  
浏览/下载:25/0
  |  
提交时间:2023/02/22
Autonomous intersection management (AIM)
cyber-physical-social intelligence
metaverse
numerical optimal control
A Self-Attention-Based Deep Reinforcement Learning Approach for AGV Dispatching Systems
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 12
作者:
Wei, Qinglai
;
Yan, Yutian
;
Zhang, Jie
;
Xiao, Jun
;
Wang, Cong
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2023/01/09
Automated guided vehicle (AGV) dispatching
deep learning
reinforcement learning (RL)
self-attention
An Agent-Based Traffic Recommendation System: Revisiting and Revising Urban Traffic Management Strategies
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 页码: 13
作者:
Jin, Junchen
;
Rong, Dingding
;
Pang, Yuqi
;
Ye, Peijun
;
Ji, Qingyuan
收藏
  |  
浏览/下载:38/0
  |  
提交时间:2022/07/25
Switches
Control systems
Timing
Task analysis
Behavioral sciences
Analytical models
Research and development
Agent-based recommendation system
deep recommendation
human-in-the-loop
operation on-demand
traffic management strategies
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