Cargando…
Deep Reinforcement Learning-Based Traffic Signal Control Using High-Resolution Event-Based Data
Reinforcement learning (RL)-based traffic signal control has been proven to have great potential in alleviating traffic congestion. The state definition, which is a key element in RL-based traffic signal control, plays a vital role. However, the data used for state definition in the literature are e...
Autores principales: | Wang, Song, Xie, Xu, Huang, Kedi, Zeng, Junjie, Cai, Zimin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515273/ https://www.ncbi.nlm.nih.gov/pubmed/33267458 http://dx.doi.org/10.3390/e21080744 |
Ejemplares similares
-
Deep Reinforcement Learning for Traffic Signal Control Model and Adaptation Study
por: Tan, Jiyuan, et al.
Publicado: (2022) -
Traffic Signal Control Using Hybrid Action Space Deep Reinforcement Learning
por: Bouktif, Salah, et al.
Publicado: (2021) -
Quantifying the impact of non-stationarity in reinforcement learning-based traffic signal control
por: Alegre, Lucas N., et al.
Publicado: (2021) -
Navigation in Unknown Dynamic Environments Based on Deep Reinforcement Learning
por: Zeng, Junjie, et al.
Publicado: (2019) -
A traffic light control method based on multi-agent deep reinforcement learning algorithm
por: Liu, Dongjiang, et al.
Publicado: (2023)