Research and Application of Expressway Stake Digitization Based on Multisource Data Fusion
At present,there is a common problem in the transportation industry,especially on highways,due to incomplete handover of design,construction,and operation data or segmented design and construction.The relevant operation management departments in the transportation industry urgently need a safe,fast,and accurate method and related software and hardware e-quipment to investigate the current situation of pile numbers.This paper was based on a multi-source data fusion algorithm,used the methods of Global Satellite Positioning System(GNSS),Optoelectronic Encoder(DMI),and image recognition data fu-sion to establish a station measurement and data verification model.Artificial intelligence deep learning was applied to intelligent-ly extract kilometer/hundred meter stations.The results showed that compared with traditional methods such as manual walking GNSS marking and vehicle mounted GNSS marking,this method has improved the efficiency of pile number measurement.By synchronizing the road environment image and GNSS in time and space,each kilometer mark was used as a correction point to en-sure that the error between each kilometer mark does not accumulate,and the positioning error does not exceed 5m.The research results data of this paper have been applied to the underlying database of the intelligent maintenance management system of Hubei Jiaotou Operation Group.This provides precise data support for the later maintenance design,testing,construction,and informa-tization of highways.
highway stake numberoptoelectronic encodermulti source data fusionspace-time synchronizationartifi-cial intelligence
NETL
NSTL
万方数据
维普
