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| Auteurs principaux: | , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2410.08616 |
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| _version_ | 1866910645329330176 |
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| author | Zhang, Wei Li, Pengfei Wang, Junli Sun, Bingchuan Jin, Qihao Bao, Guangjun Rui, Shibo Yu, Yang Ding, Wenchao Li, Peng Chen, Yilun |
| author_facet | Zhang, Wei Li, Pengfei Wang, Junli Sun, Bingchuan Jin, Qihao Bao, Guangjun Rui, Shibo Yu, Yang Ding, Wenchao Li, Peng Chen, Yilun |
| contents | Automatic Emergency Braking (AEB) systems are a crucial component in ensuring the safety of passengers in autonomous vehicles. Conventional AEB systems primarily rely on closed-set perception modules to recognize traffic conditions and assess collision risks. To enhance the adaptability of AEB systems in open scenarios, we propose Dual-AEB, a system combines an advanced multimodal large language model (MLLM) for comprehensive scene understanding and a conventional rule-based rapid AEB to ensure quick response times. To the best of our knowledge, Dual-AEB is the first method to incorporate MLLMs within AEB systems. Through extensive experimentation, we have validated the effectiveness of our method. The source code will be available at https://github.com/ChipsICU/Dual-AEB. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_08616 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dual-AEB: Synergizing Rule-Based and Multimodal Large Language Models for Effective Emergency Braking Zhang, Wei Li, Pengfei Wang, Junli Sun, Bingchuan Jin, Qihao Bao, Guangjun Rui, Shibo Yu, Yang Ding, Wenchao Li, Peng Chen, Yilun Robotics Automatic Emergency Braking (AEB) systems are a crucial component in ensuring the safety of passengers in autonomous vehicles. Conventional AEB systems primarily rely on closed-set perception modules to recognize traffic conditions and assess collision risks. To enhance the adaptability of AEB systems in open scenarios, we propose Dual-AEB, a system combines an advanced multimodal large language model (MLLM) for comprehensive scene understanding and a conventional rule-based rapid AEB to ensure quick response times. To the best of our knowledge, Dual-AEB is the first method to incorporate MLLMs within AEB systems. Through extensive experimentation, we have validated the effectiveness of our method. The source code will be available at https://github.com/ChipsICU/Dual-AEB. |
| title | Dual-AEB: Synergizing Rule-Based and Multimodal Large Language Models for Effective Emergency Braking |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.08616 |