Research on Risk Quantification Methods for Connected Autonomous Vehicles Based on CNN-LSTM

Research on Risk Quantification Methods for Connected Autonomous Vehicles Based on CNN-LSTM

Quantifying and predicting driving risks for connected autonomous vehicles (CAVs) is critical to ensuring the safe operation of traffic in complex environments. This study first establishes a car-following model for CAVs based on molecular force fields. Subsequently, using a convolutional neural net...

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Bibliographic Details
Main Authors: Kedong Wang, Dayi Qu, Dedong Shao, Liangshuai Wei, Zhi Zhang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
traffic safety
deep learning
risk quantification
risk prediction
Online Access:https://www.mdpi.com/2076-3417/14/23/11204
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