本发明公开了一种基于MEMS传感器的车位级停车惯性导航系统及导航方法,惯性导航结合拐点修正算法、车辆动力学以及BP模型训练优化惯性导航模型,应用于地下停车场,提高地下导航准确性,摆脱外部信息依赖,解决地下停车场末端导航问题;运用NB‑IOT解决停车场信息管理问题,利用计算机技术、传感器等设备组建的信息管理系统,智能有序的管理,提高停车场的安全性和经济性并大幅提升停车场的停车效率。车位级导航基础上融合大数据分析实现车位变化预测及偏好分析,提高用户出行效率,改善出行体验。优化区域资源配置,解决城市出行、城市交通和改善城市的面貌,助力于城市交通信息化发展,可产生巨大的经济效应。
The invention discloses a parking space level parking inertial navigation system and navigation method based on an MEMS sensor. Inertial navigation combines an inflection point correction algorithm, vehicle dynamics and BP model training optimization inertial navigation model, is applied to an underground parking lot, improves the underground navigation accuracy, gets rid of external information dependence, and solves the terminal navigation problem of the underground parking lot; the information management problem of the parking lot is solved by applying NB-IOT, and intelligent and orderly management is realized by utilizing an information management system established by a computer technology, a sensor and other equipment, so that the safety and economy of the parking lot are improved, and the parking efficiency of the parking lot is greatly improved. Parking space change prediction and preference analysis are realized by fusing big data analysis on the basis of parking space level navigation, the user travel efficiency is improved, and the travel experience is improved. Regional resource allocation is optimized, urban travel and urban traffic are solved, urban appearance is improved, urban traffic informatization development is assisted, and huge economic effects can be generated.
基于MEMS传感器的车位级停车惯性导航系统及导航方法
2022-06-24
Patent
Elektronische Ressource
Chinesisch
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