A Follow-Up Risk Identification Model Based on Multi-Source Information Fusion
To address poor real-time performance and low accuracy in car-following risk identification, a model based on autoencoders is proposed. Using the SHRP2 natural driving dataset, this paper constructs a car-following risk identification model in two stages. In Stage 1, a deep feedforward neural networ...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/13/1/41 |
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