Sparse GPS sampling point based method and device for fine moving track reduction

Abstract

The invention discloses a sparse GPS sampling point based method and device for fine moving track reduction. The method includes the following steps: step 1, collecting the station data and track dataof several shifts of public transport vehicles in the same line during operation through a vehicle terminal data acquisition unit; step 2, selecting one shift as a reference shift; step 3, constructing a track point model M for the track data according to the station data and the time parameters of the track data; step 4, judging whether a track point is a turn point; step 5, performing interpolation on the turn point; and step 6, performing interpolation on other track points. Through the method, effective bases can be provided for the management and decision of public transport companies, costs can be reduced, influences of weak GPS signals can be eliminated, and sampling periods can be greatly shortened; and a new precise line track can be generated through fast fitting by only drivingvehicles on a set track for several times.

Description

technical field [0001] The invention relates to the field of intelligent transportation research and the field of GPS application, in particular to a method for restoring traffic routes or running route trajectories, and in particular to a method and device for restoring fine running trajectories based on sparse GPS sampling points. Background technique [0002] With the rapid development of my country's transportation and the increase of urban passenger capacity, the bus lines continue to expand. How to quickly and accurately determine the actual running track of the newly added bus lines has become a major problem for bus companies. Traffic is facing enormous management pressure. How to determine whether the bus is running on the predetermined track has become an important management requirement of the bus company, so the track restoration technology of the bus becomes more important. The existing implementation method is to use high-precision intensive GPS sampling to comp...

AI Technical Summary

Problems solved by technology

The existing implementation method is to use high-precision intensive GPS sampling to complete, which requires a high-precision GPS sampler to sample, and the cost is high; the sampling interval is short, the time period is long, and reciprocating sampling is required to ensure coverage; at the same time, GPS often occurs in some places Weak signal, GPS loss, and GPS drift lead to inaccurate trajectory, so there are many limitations and deficiencies in existing methods

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