Bayesian path estimation using the spatial attributes of a road network

We consider the problem of estimating the path taken by an object in a road network from sparse, noisy position measurements. Path estimation is posed in a Bayesian framework which allows the incorporation of prior information about vehicle movements. A carefully designed importance sampler is used to approximate the posterior path probabilities. The algorithm is demonstrated on simulated data.

[1]  Y. Ho,et al.  A Bayesian approach to problems in stochastic estimation and control , 1964 .

[2]  Washington Y. Ochieng,et al.  A general map matching algorithm for transport telematics applications , 2003 .

[3]  J. Besag,et al.  Bayesian Computation and Stochastic Systems , 1995 .

[4]  Tae-Kyung Sung,et al.  Development of a map matching method using the multiple hypothesis technique , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[5]  Hassan A. Karimi,et al.  A critical review of real-time map-matching algorithms: Current issues and future directions , 2014, Comput. Environ. Urban Syst..

[6]  S.S. Blackman,et al.  Multiple hypothesis tracking for multiple target tracking , 2004, IEEE Aerospace and Electronic Systems Magazine.

[7]  Simon J. Godsill,et al.  On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..

[8]  Michel Bierlaire,et al.  A Probabilistic Map Matching Method for Smartphone GPS data , 2013 .

[9]  M. Bierlaire,et al.  Metropolis-Hastings sampling of paths , 2013 .

[10]  David Bernstein,et al.  Some map matching algorithms for personal navigation assistants , 2000 .

[11]  Véronique Berge-Cherfaoui,et al.  Map-Matching Integrity Using Multihypothesis Road-Tracking , 2008, J. Intell. Transp. Syst..

[12]  David Eppstein,et al.  Finding the k Shortest Paths , 1999, SIAM J. Comput..

[13]  Qingquan Li,et al.  Map-matching algorithm for large-scale low-frequency floating car data , 2014, Int. J. Geogr. Inf. Sci..

[14]  Bradford S. Westgate VEHICLE TRAVEL TIME DISTRIBUTION ESTIMATION AND MAP-MATCHING VIA MARKOV CHAIN MONTE CARLO METHODS , 2013 .

[15]  Robert B. Noland,et al.  Current map-matching algorithms for transport applications: State-of-the art and future research directions , 2007 .

[16]  Oleksiy Mazhelis,et al.  Using recursive Bayesian estimation for matching GPS measurements to imperfect road network data , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.