Exploring Spatial and Temporal Patterns of Large-scale Smartphone-based Dangerous Driving Event Data

Di Yang, Kun Xie, Kaan Ozbay, Hong Yang

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

Abstract

Dangerous driving events data are widely used as surrogates to traffic crashes. Large-scale dangerous driving events data collected from smartphones are explored in this study. Clustering analysis is performed on dangerous driving events counted in spatial cells. Spatial and temporal patterns of the cluster distributions are then explored. Both the existence of spatial autocorrelation and the similarity of cluster distributions for different time periods are uncovered.

Original languageEnglish (US)
Title of host publication2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages116-121
Number of pages6
ISBN (Electronic)9781538670248
DOIs
StatePublished - Oct 2019
Event2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand
Duration: Oct 27 2019Oct 30 2019

Publication series

Name2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

Conference

Conference2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Country/TerritoryNew Zealand
CityAuckland
Period10/27/1910/30/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Management Science and Operations Research
  • Instrumentation
  • Transportation

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