Smart City Traffic Flow and Signal Optimization Using STGCN-LSTM and PPO Algorithms

Smart City Traffic Flow and Signal Optimization Using STGCN-LSTM and PPO Algorithms

Urban traffic congestion remains a critical challenge for smart city development, necessitating innovative approaches to improve traffic flow and reduce delays. This study presents a novel framework that integrates the Spatiotemporal Graph Convolutional Network-Long Short-Term Memory (STGCN-LSTM) mo...

Full description

Saved in:
Bibliographic Details
Main Authors: Tuxiang Lin, Rongliang Lin
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Long short-term memory (LSTM)
intelligent transportation systems
proximal policy optimization (PPO)
spatio-temporal graph convolutional networks (STGCN)
traffic flow prediction
Online Access:https://ieeexplore.ieee.org/document/10806681/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10806681/

Similar Items