Computer Science ›› 2016, Vol. 43 ›› Issue (Z6): 68-72.doi: 10.11896/j.issn.1002-137X.2016.6A.015

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Map Matching Algorithm Based on Conditional Random Fields and Low-sampling-rate Floating Car Data

YANG Xu-hua and PENG Peng   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In this paper,a new map matching algorithm(FB-MM) based on conditional random fields and low-sample-rate floating car data was proposed.On the basis of the road network model,the candidate projection points and their observation probability of the GPS observation point can be gained,and the candidate paths and the transfer probability between adjacent candidate projection points can be also gained.Then the probability weight value of every candidate projection points can be computed by using forward and backward recursion algorithm based on the conditional random fields in the sliding window.After that,the best matching projection point can be selected by the probability weight value.Based on low-sampling-rate floating car data,this map matching algorithm can make full use of the topological information of road network and the correlation information between GPS observation points.So it can achieve the better map matching effect.

Key words: Floating car,Low-sampling-rate,Topological information,Conditional random fields,Forward and backward recursion,Map matching

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