Traffic Flow Prediction Methods Based on Deep Learning
Year: 2024
Type: article
Abstract: In recent years, due to the rapid development of deep learning, it has been found that deep learning has shown good experimental results in traffic flow prediction, and is significantly better than traditional traffic flow prediction methods. This paper mainly classifies, sorts out, and summarizes the classic techniques and research status of traffic flow prediction based on deep learning. According to the length of traffic flow data, the traffic flow prediction method based on deep learning is further subdivided into long traffic flow prediction method and short traffic flow prediction method. The representative models of the two traffic flow prediction methods are analyzed and introduced in detail. Each representative model is expanded and extended, and the performance evaluation indicators of the long and short traffic flow prediction models are introduced. Finally, the possible future research directions and corresponding development trends in this field are summarized.
Authors: Haoxuan Yang, Yang Zhang
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405120706