A safe driving guidance method and system based on road surface wetness state detection

Abstract

The present application relates to the field of automobile environment perception, and particularly relates to a safe driving guidance method and system based on road surface wet and slippery state detection; real-time collection of road surface image signals, road surface temperature signals, vehicle speed signals and roadside information in front of the vehicle; input of the road surface image signals and the road surface temperature signals into a pre-trained multi-modal detection model to output a perception result; calculation of a comprehensive road surface-vehicle safety margin index based on the vehicle speed signals, a forward adhesion coefficient prediction curve and a forward risk interval; comparison of the safety margin index with a preset threshold to output a risk level; generation of corresponding driving guidance instructions according to the risk level. The present application overcomes the limitations of a single perception mode, can perform high robustness identification and spatial positioning on various wet and slippery working conditions, and can convert the perception result into a safety margin index to realize prediction and active guidance of driving risks, thereby significantly improving the active safety of the vehicle.

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