What question did this study set out to answer?

The research aims to develop a hybrid CNN-LSTM framework for improving V2X communication efficiency.

A Hybrid CNN–LSTM Deep Learning Framework for URLLC-Enabled Intelligent V2X Communication Systems

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Hybrid deep learning approach enhances adaptive routing and decision-making in intelligent transportation systems for vehicles.

The research aims to develop a hybrid CNN-LSTM framework for improving V2X communication efficiency.
Integrated Convolutional Neural Networks and Long Short-Term Memory networks.
Collected data from Vehicle-to-Vehicle, Vehicle-to-Infrastructure, and more.
Employed data preprocessing techniques like Min–Max scaling and dimensionality reduction.
Enhanced adaptive routing and real-time decision-making capabilities.
Improved computational efficiency and predictive accuracy for vehicular networks.

Jiang et al. (2026) studied this question.

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