Urban Traffic Signal Control at the Edge: An Ontology-Enhanced Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

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Urban Traffic Signal Control at the Edge: An Ontology-Enhanced Deep Reinforcement Learning Approach

Published:2023-09-24 Issue: Volume: Page:6027-6033
ISSN:
Container-title:2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
language:
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Author:

Guo Jiaying¹,Ghanadbashi Saeedeh¹,Wang Shen¹,Golpayegani Fatemeh¹

Affiliation:

1. School of Computer Science, University College Dublin,Ireland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420842/10420843/10422573.pdf?arnumber=10422573

Reference15 articles.

1. Deep Reinforcement Learning for Traffic Signal Control: A Review

2. Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning

3. Using Reinforcement Learning With Partial Vehicle Detection for Intelligent Traffic Signal Control

4. Multi-Agent Reinforcement Learning for Traffic Signal Control: Algorithms and Robustness Analysis

5. An Ontology-Based Intelligent Traffic Signal Control Model

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