May 18, 2020 · In this paper, we propose a new prediction system in real time using Big Data to improve the VANET network. Firstly, The Traffic density and ...
This article proposes a new image-inspired data architecture capable of capturing the microscopic scene of vehicular behavior.
Many factors such as priority, distance from the junction, vehicle direction, and density are considered during the waiting time calculation.
In this dissertation, we have aggregated seven years of real-life tra c and incidents data, obtained from the Florida Department of Transportation District 4.
The study aims to propose an intelligent real-time traffic model to address the traffic congestion problem.
Second dataset is real time vehicular traffic which we analyze to find users located near accident spot or ones approaching the accident prone area. To reduce ...
May 17, 2023 · Big data and data-driven analysis could be utilized for traffic management to improve road safety and the performance of transportation systems.
Machine learning based real-time prediction of freeway crash risk ...
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Aug 9, 2022 · This study aims to use machine learning models to predict crash risk on freeways according to pre-crash traffic dynamics (eg, mean speed, speed reduction)
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This paper proposes a bidirectional long short-term memory (LSTM) model with two convolutional layers to predict real-time crash potential on freeways.
The purpose of this paper is to highlight the use of the big data technologies for health and safety risks analytics in the power infrastructure domain.