A method for map matching using historical GPS data

Abstract

The invention discloses a method for map matching using historical GPS data. The historical GPS point records are organized into a trajectory form according to vehicle ID, recording time, and coordinate area, and the trajectory is converted into a KML file; the road network data of the corresponding area is Cut it out and convert it into a KML format file; superimpose the obtained KML files together, and use the marking method to mark the road segment ID of each GPS point in the trajectory. This part of the marked data is recorded as data set A; you only need to add it The direction angle information can be used as training data, and the obtained labeled data is recorded as data set B; the obtained data set A and the data set B obtained in the fourth step are combined as the training data set for the ELM algorithm. The selected part is different from data set A. The intersecting historical data sets are used as test data, and the parameter search algorithm is used to find the ELM parameters until the prediction accuracy is the highest. At this time, the corresponding ELM model is the map matching model in the area.

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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