Map matching method by use of historical GPS data

Abstract

The invention discloses a map matching method by use of historical GPS data. The method comprises the following steps: organizing historical GPS point records into a trajectory form according to vehicle ID, recording time and coordinate region and converting the trajectory into a KML file; clipping the road network data of a corresponding region and converting the road network data into a KML format file; overlapping the obtained KML files, marking each GPS point in the trajectory with the ID of the corresponding road section by use of a marking method, and recording the marking data as a data set A; just supplementing direction angle information to the marking data to obtain training data and recording the obtained marking data as a data set B; combining the obtained data set A and the data set B obtained in the fourth step to form a training data set for an ELM algorithm, selecting partial historical data set disjointed with the data set A as test data, finding an EML parameter by use of a parameter finding algorithm until the prediction precision is highest, and taking the corresponding ELM model at the moment as a map matching model in the region.

Description

technical field [0001] The invention relates to a map matching method, in particular to a method for map matching using historical GPS data. Background technique [0002] In the vehicle navigation system, the vehicle movement trajectory displayed on the electronic map reflects the result of real-time measurement by GPS measurement equipment. However, the navigation effect will be affected by many factors, such as equipment error, signal strength, geographical environment, weather and so on. Since GPS data inevitably contains a lot of uncertain information, the vehicle trajectory displayed on the map may not be consistent with the real trajectory, so it is necessary to detect these errors before further mining and analyzing geographic information. [0003] Map matching is the process of using software methods to identify and correct GPS sampling points to corresponding spatial road network locations. In the past 20 years, map matching algorithms have been intensively studie...

AI Technical Summary

Problems solved by technology

In the past 20 years, map matching algorithms have been intensively studied, but there is still room for improvement

First, the previous algorithms did not make full use of the existing information, such as vehicle orientation, map topology information, and historical GPS tracks; second, the previous algorithms had poor adaptability, and sometimes small deviations from the map may have a large impact on the matching results. Influence, such as coordinate offset of vector electronic map

Finally, the matching process of some algorithms is very complicated and not suitable for real-time processing

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