Novel Mobile Motion Prediction Algorithm for Predicting Pedestrian’s Next Location

  • Yan Zhuang
  • Simon FongEmail author
  • Meng Yuan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 393)


This paper describes a novel mobile motion prediction algorithm to meet the need of today’s mobile system and application which is based on Markov model. As in different time period, the things people always do usually are different, so does the route they have taken. It provides a way to constrain the path sample with time interval to enhance the prediction. In the end, the prediction accuracy is experimented up to 92 %.


Location prediction Trajectory mining GPS trajectory analysis 



The authors of this paper are thankful to the financial supports of the grant offered with code: MYRG2015-00024, called “Building Sustainable Knowledge Networks through Online Communities”, by RDAO, University of Macau.


  1. 1.
    Hui L, Lei Y (2009) Mobile geographic information services. IGI Global, pp 944–945Google Scholar
  2. 2.
    Deguchi Y, Kuroda K, Shouji M, Kawabe T (2004) HEV charge/discharge control system based on navigation information. In: Convergence international congress & exposition on transportation electronics. pp 21–28Google Scholar
  3. 3.
    Tate E, Boyd S (2000) Finding ultimate limits of performance for hybrid electric vehicles. In: Proceedings of Society of Automotive Engineers 2000 future transportation technology conference. pp. 1–12Google Scholar
  4. 4.
    Yu XG, Liu YH, Wei D, Ting M (2006) Hybrid Markov model used for path prediction. In: Proceedings. 15th international conference on computer communications and network. ICCCN 2006, pp 374–379Google Scholar
  5. 5.
    Jeung H, Yiu ML, Zhou X (2010) Path prediction and predictive range querying in road network databases. VLDB J 585–602Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  1. 1.Department of Computer and Information ScienceUniversity of MacauMacau SarPeople’s Republic of China

Personalised recommendations