Cluster-based correlation of severe braking events with time and location

Guoyan Cao, John Michelini, Karolos Grigoriadis, Behrouz Ebrahimi, Matthew A. Franchek

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

2 Scopus citations

Abstract

In this paper, a systematic strategy is proposed to identify severe braking events occurrence correlation with time and location. The proposed approach, which is constructed based on batch clustering and real-time clustering techniques, incorporates historical and real-time data to predict the time and location of severe braking events. Batch clustering is implemented with the combination of subtractive clustering and fuzzy c-means clustering to generate clusters representing the initial correlation patterns. Real-time clustering is then developed to create and update real-time correlation patterns on the foundation of the batch clustering using evolving Gustafson Kessel Like (eGKL) algorithm. Real-time driving data of operating vehicles each equipped with a data acquisition and wireless communication platform are used to validate the proposed strategy. Drivers can be notified of the potential severe braking locations through maps, and recognize the events occurrence at different times and locations through the variation of the identified correlation patterns.

Original languageEnglish (US)
Title of host publication2015 10th System of Systems Engineering Conference, SoSE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages187-192
Number of pages6
ISBN (Electronic)9781479976119
DOIs
StatePublished - Jul 7 2015
Event2015 10th System of Systems Engineering Conference, SoSE 2015 - San Antonio, United States
Duration: May 17 2015May 20 2015

Publication series

Name2015 10th System of Systems Engineering Conference, SoSE 2015

Other

Other2015 10th System of Systems Engineering Conference, SoSE 2015
CountryUnited States
CitySan Antonio
Period5/17/155/20/15

Keywords

  • clustering
  • correlation identification
  • evolving Gustafson Kessel Like approach
  • severe driving events

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering

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