井下无轨胶轮车多传感器数据融合智能辅助驾驶系统设计

    Design of an intelligent assisted driving system for underground trackless rubber-tired vehicles based on multi-sensor data fusion

    • 摘要: 针对煤矿井下无轨胶轮车智能化程度低,工作环境恶劣,具有照明不充分、水雾粉尘多、道路条件差、路况路网复杂、司机视觉盲区大等问题,设计了一套基于多传感器数据融合的智能辅助驾驶系统。首先,分析了无轨胶轮车智能化应用的现状及趋势;其次,设计了多模态数据融合智能辅助驾驶系统的框架结构,包括硬件架构和软件架构;最后,给出了智能辅助驾驶系统的具体功能设计。测试结果表明:该系统的多模态融合感知算法在障碍物识别方面准确率达到了96%以上,人机协作驾驶安全性提升到了99.6%。

       

      Abstract: Aiming at the low intelligence level of trackless rubber-tyred vehicles in coal mines, the harsh working environment, insufficient lighting, high water mist, poor road conditions, complex road conditions and networks, and large visual blind spots of drivers, an intelligent assisted driving system based on multi-sensor data fusion is designed. Firstly, the current status and trend of intelligent application of trackless rubber-tyred vehicles are analyzed; secondly, the framework structure of the multimodal data fusion intelligent assisted driving system is designed, including hardware architecture and software architecture; finally, the specific functional design of the intelligent assisted driving system is given. The test results show that the accuracy of the multimodal fusion perception algorithm of the system in obstacle recognition has reached more than 96%, and the safety of man-machine cooperative driving is improved to 99.6%.

       

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