A review of traffic congestion prediction using artificial intelligence
M Akhtar, S Moridpour - Journal of Advanced Transportation, 2021 - Wiley Online Library
In recent years, traffic congestion prediction has led to a growing research area, especially
of machine learning of artificial intelligence (AI). With the introduction of big data by …
of machine learning of artificial intelligence (AI). With the introduction of big data by …
City-wide traffic congestion prediction based on CNN, LSTM and transpose CNN
Traffic congestion is a significant problem faced by large and growing cities that hurt the
economy, commuters, and the environment. Forecasting the congestion level of a road …
economy, commuters, and the environment. Forecasting the congestion level of a road …
Understanding the potential of emerging digital technologies for improving road safety
Abstract Each year, 1.35 million people are killed on the world's roads and another 20–50
million are seriously injured. Morbidity or serious injury from road traffic collisions is …
million are seriously injured. Morbidity or serious injury from road traffic collisions is …
[HTML][HTML] A fundamental diagram based hybrid framework for traffic flow estimation and prediction by combining a Markovian model with deep learning
Accurate traffic congestion estimation and prediction are critical building blocks for smart trip
planning and rerouting decisions in transportation systems. Over the decades, there have …
planning and rerouting decisions in transportation systems. Over the decades, there have …
Machine learning approach on traffic congestion monitoring system in internet of vehicles
Traffic congestion is a major issue in urban cities leading to aggregated traffic. With the
advancement in intelligent internet of vehicles, new technologies and protocols have been …
advancement in intelligent internet of vehicles, new technologies and protocols have been …
Traffic prediction using machine learning
HR Deekshetha, AV Shreyas Madhav… - … Computing and Mobile …, 2022 - Springer
The paper deals with traffic prediction that can be done in intelligent transportation systems
which involve the prediction between the previous year's dataset and the recent year's data …
which involve the prediction between the previous year's dataset and the recent year's data …
Controlling highway toll stations using deep learning, queuing theory, and differential evolution
Traffic congestion is, nowadays, one of the most important highway problems. Highway tolls
with booth operators are one of the causes of traffic congestion on highways, especially in …
with booth operators are one of the causes of traffic congestion on highways, especially in …
[HTML][HTML] STTF: An efficient transformer model for traffic congestion prediction
With the rapid development of economy, the sharp increase in the number of urban cars and
the backwardness of urban road construction lead to serious traffic congestion of urban …
the backwardness of urban road construction lead to serious traffic congestion of urban …
[HTML][HTML] Short-term traffic congestion prediction using hybrid deep learning technique
M Anjaneyulu, M Kubendiran - Sustainability, 2022 - mdpi.com
A vital problem faced by urban areas, traffic congestion impacts wealth, climate, and air
pollution in cities. Sustainable transportation systems (STSs) play a crucial role in traffic …
pollution in cities. Sustainable transportation systems (STSs) play a crucial role in traffic …
Comparative analysis of multiple techniques for developing and transferring safety performance functions
Safety performance functions (SPFs) are crash count prediction models that are used for
identifying high crash risk locations, evaluating road safety before and after countermeasure …
identifying high crash risk locations, evaluating road safety before and after countermeasure …