The invention relates to a path fitting implementation method based on multivariate data fusion, and the method comprises the steps: S1, data collection: building a data center, collecting the data, and collecting the desensitized data of each highway electromechanical system through an SDK/API mode; s2, data fusion preprocessing: taking license plate information, identification point information and passing time as triple parameters of a to-be-fitted passing vehicle path, extracting desensitization data in the data to perform data preprocessing, and providing a data basis for subsequent fitting processing; s3, full-time-space domain path fitting: based on a full-time-space domain frame, performing consistency comparison and reasonability judgment analysis on multivariate data; s4, performing path fitting calculation, specifically, generating a vehicle path restoration and toll calculation scene by calling a path fitting algorithm set; the path fitting implementation method based on multivariate data fusion provided by the invention can adapt to different application scenes and improve the charging capability and the calculation accuracy of highway passage.
本发明涉及一种基于多元数据融合的路径拟合实施方法,包括步骤S1:数据汇集,建立数据中台并采集数据,通过SDK/API方式汇聚各高速公路机电系统脱敏后数据;步骤S2:数据融合预处理,通过将车牌信息、标识点信息、通行时间作为待拟合通行车辆路径的三元组参数,提取数据中台的脱敏数据进行数据预处理,为后续拟合处理提供数据基础;步骤S3:全时空域路径拟合,基于全时空域框架通过多元数据的一致性比对与合理性判定分析;步骤S4:路径拟合计算,具体通过调用路径拟合算法集生成车辆路径还原、通行费计算场景;本发明能够提供一种可适应不同应用场景,并提升高速公路通行的计费能力和计算准确性的基于多元数据融合的路径拟合实施方法。
Path fitting implementation method based on multivariate data fusion
一种基于多元数据融合的路径拟合实施方法
2023-07-18
Patent
Electronic Resource
Chinese
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