/mapmatching-

Trajectory Inference

Primary LanguageJupyter Notebook

MapMatching Algorthims


Map matching is the processing of recognizing the true driving route in the road network accroding to discrete GPS sampling datas . It is a necessary processing step for many relevant applications such as GPS trajectory data analysis and position analysis.
Author: Shenglong Yan
Created: 23/02/2019

Main Contributions


I have exposed several common map matching algorithms and some test datas for future reserach.

1.Hidden Markov Map Matching Through Noise and Sparseness(HMMM)

2.Map-matching for Low-sampling-rate GPS Trajectories(ST-matching)

3.An Interactive-Voting Based Map Matching Algorithm(IVMM)

4.AntMapper: An Ant Colony-Based Map Matching Approach for Trajectory-Based Applications(AntMapper)

5.Spatio-temporal trajectory simplification for inferring travel paths(SIMP)

6.Robust inferences of travel paths from GPS trajectories(OBRHMM)

Dependency


python 2.7(jupyter notebook,sublime text4)
1.pandas/geoPandas
2.numpy
3.shapely
4.networkx
5.osmnx
6.Rtree
7.matplotlib