Towards prediction of driving behavior via basic pattern discovery with BP-AR-HMM

Ryunosuke Hamada, Takatomi Kubo, Kazushi Ikeda, Zujie Zhang, Tomohiro Shibata, Takashi Bando, Masumi Egawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Prediction of driving behaviors is important problem in developing the next-generation driving support system. In order to take account of diverse driving situations, it is necessary to deal with multiple time series data considering commonalities and differences among them. In this paper we utilize the beta process autoregressive hidden Markov model (BP-AR-HMM) that can model multiple time series considering common and different features among them using the beta process as a prior distribution. We apply the BP-AR-HMM to actual driving behavior data to estimate VAR process parameters that represent the driving behaviors, and with the estimated parameters we predict the driving behaviors of unknown test data. The results suggest that it is possible to identify the dynamical behaviors of driving operations using BP-AR-HMM, and to predict driving behaviors in actual environment.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages2805-2809
Number of pages5
DOIs
Publication statusPublished - 2013 Oct 18
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 2013 May 262013 May 31

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period13/5/2613/5/31

Keywords

  • Bayesian nonparametric approach
  • beta process
  • beta process autoregressive hidden Markov model
  • driving behavior prediction

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Towards prediction of driving behavior via basic pattern discovery with BP-AR-HMM'. Together they form a unique fingerprint.

Cite this