Deep Q-network-based traffic signal control models.
Traffic congestion has become common in urban areas worldwide. To solve this problem, the method of searching a solution using artificial intelligence has recently attracted widespread attention because it can solve complex problems such as traffic signal control. This study developed two traffic si...
Guardado en:
Autores principales: | Sangmin Park, Eum Han, Sungho Park, Harim Jeong, Ilsoo Yun |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/7f9b604ae37e4356b07a8755728d2c30 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Traffic Signal Time Optimization Based on Deep Q-Network
por: Hyunjin Joo, et al.
Publicado: (2021) -
Field-Based Prediction Models for Stop Penalty in Traffic Signal Timing Optimization
por: Suhaib Alshayeb, et al.
Publicado: (2021) -
A lightweight model for multi-traffic object detection based on deep learning under complex traffic conditions
por: Guoqiang Chen, et al.
Publicado: (2021) -
Traffic Signal Optimization for Multiple Intersections Based on Reinforcement Learning
por: Jaun Gu, et al.
Publicado: (2021) -
A Traffic Congestion Prediction Model Based on Dilated-Dense Network
por: SHI Min, et al.
Publicado: (2021)