@inproceedings{63cd850832f546999f2133908ce83332,
title = "Investigating the relationship between traffic incidents and public events: A case study",
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.",
keywords = "Crowdsourced data, social events, social media data, traffic incident prediction",
author = "Chase Grimm and Andre Fristo and Mostafa Amin-Naseri and Mingyi Hong and Anuj Sharma",
year = "2017",
month = may,
day = "31",
doi = "10.1109/SIEDS.2017.7937715",
language = "English (US)",
series = "2017 Systems and Information Engineering Design Symposium, SIEDS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "198--201",
booktitle = "2017 Systems and Information Engineering Design Symposium, SIEDS 2017",
note = "2017 Systems and Information Engineering Design Symposium, SIEDS 2017 ; Conference date: 28-04-2017",
}