Pedestrian-movement prediction based on mixed Markov-chain model

@inproceedings{Asahara2011PedestrianmovementPB,
  title={Pedestrian-movement prediction based on mixed Markov-chain model},
  author={Akinori Asahara and Kishiko Maruyama and Akiko Sato and Kouichi Seto},
  booktitle={GIS},
  year={2011}
}
A method for predicting pedestrian movement on the basis of a mixed Markov-chain model (MMM) is proposed. MMM takes into account a pedestrian's personality as an unobservable parameter. It also takes into account the effects of the pedestrian's previous status. A promotional experiment in a major shopping mall demonstrated that the highest prediction accuracy of the MMM method is 74.4%. In comparison with methods based on a Markov-chain model (MM) and a hidden-Markov model (HMM) (i.e… CONTINUE READING
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