Investigating the relationship between traffic incidents and public events: A case study

Chase Grimm, Andre Fristo, Mostafa Amin-Naseri, Mingyi Hong, Anuj Sharma

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

1 Scopus citations

Abstract

Large social events can influence traffic conditions and possibly lead to jams and incidents. This study leverages crowdsourced data to analytically evaluate the relationship between social events and traffic incidents in the city of Chicago. In particular, we collected data on social events from scraping online webpages, as well as traffic data from a twitter account that posted irregular traffic incidents based on a crowdsourced navigation application (Waze). Using these two sources the relationship between social events and the occurrence of traffic incidents was investigated. The total number social events and their categories for each region and its neighboring regions were used to build models that predicted the chance of a traffic incident occurrence.

Original languageEnglish (US)
Title of host publication2017 Systems and Information Engineering Design Symposium, SIEDS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages198-201
Number of pages4
ISBN (Electronic)9781538618486
DOIs
StatePublished - May 31 2017
Event2017 Systems and Information Engineering Design Symposium, SIEDS 2017 - Charlottesville, United States
Duration: Apr 28 2017 → …

Publication series

Name2017 Systems and Information Engineering Design Symposium, SIEDS 2017

Other

Other2017 Systems and Information Engineering Design Symposium, SIEDS 2017
Country/TerritoryUnited States
CityCharlottesville
Period4/28/17 → …

Keywords

  • Crowdsourced data
  • social events
  • social media data
  • traffic incident prediction

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