New Approaches of Traffic Flow Prediction
Year: 2024
Type: article
Abstract: Recently, transportation has become a part of people's workday lives, with the fierce development of information, technology, and living standards. Nevertheless, it causes a great deal of inevitable trouble, such as congestion. As artificial intelligence (AI) is becoming increasingly popular, people have begun looking for solutions from AI daily. To bring convenience to relevant scientific research, the author has reviewed some novel AI models for traffic flow forecasting designed in recent years, based on a brief introduction to both machine learning and deep learning. According to the newly proposed AI models, the author has also drawn some expectations of traffic flow prediction that have the potential to be widely applied, the expectation combines mathematical functions, statistical models, and AI algorithms, making the traffic flow forecasting and adjustment more scientific and precise. The integration of advanced AI models into traffic flow prediction holds significant promise for enhancing urban mobility and reducing congestion in our daily lives.
Author: Zhikun Qiao
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405121473