New Approaches of Traffic Flow Prediction

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.

Authors

Publication Details

Journal
Applied and Computational Engineering
Published
2024-12-06
DOI
https://doi.org/10.54254/2755-2721/2024.ch17897
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

New Approaches of Traffic Flow Prediction

Zhiwei Qiao
Applied and Computational Engineering
Traffic Prediction and Management Techniques
article

New Approaches of Traffic Flow Prediction

Zhiwei Qiao
article en

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.

Applied and Computational EngineeringVol. 111(1)
Sustainable cities and communities
Openalex Percentile: Top 76%
Traffic Prediction and Management Techniques
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