Auxiliary driving prompting method and device based on multi-mode transformer

Through the assisted driving prompt method based on multimodal transformer, the driver's emotional state and external environment information are integrated, and the problem of accurate driving prompts cannot be provided in the prior art is solved, and more accurate driving environment and driver status prediction are achieved, and driving safety is improved.

CN119659663AActive Publication Date: 2025-03-21GUANGDONG UNIV OF TECH
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Patent Information

Application Number
CN202510199795.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-24
Publication Date
2025-03-21
Estimated Expiration
2045-02-24

AI Technical Summary

Technical Problem

The existing assisted driving prompt methods cannot effectively integrate the driver's emotional state and external environment information, resulting in the inability to provide accurate driving prompts.

Method used

The assisted driving prompt method based on multimodal transformer is adopted. By obtaining facial expression images and road conditions images, the input module, the Transformer self-attention module, the cross attention module and the classification module are used to extract and fusion features to generate assisted driving prompt results.

Benefits of technology

It can more accurately understand and predict the driving environment and driver status, provide more accurate and timely driving tips, and improve driving safety.

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Abstract

The invention discloses an auxiliary driving prompting method and device based on a multi-mode transformer, relates to the technical field of automobile driving, and is used for solving the technical problem that an existing auxiliary driving prompting method cannot provide accurate driving prompts. The method comprises the following steps: processing acquired multi-modal images, namely a facial expression image and a road condition image, by adopting a multi-modal transformer-based auxiliary driving prompt model, and outputting an auxiliary driving prompt result; the auxiliary driving prompt model based on the multi-mode transformer comprises an input module, a transformer self-attention module, a cross attention module and a classification module.
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