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DTSTART;TZID=America/New_York:20211019T150000
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DTSTAMP:20260509T215926
CREATED:20211015T152545Z
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UID:69113-1634655600-1634659200@c2smart.engineering.nyu.edu
SUMMARY:Proactive Safety Management Empowered by Big Data
DESCRIPTION:In the last few decades\, data-driven methods have been used to assist with key tasks of road safety management like hotspot identification\, countermeasure development\, and before-after evaluation. These methods have traditionally relied heavily on historical crash data for safety assessment\, which can take a long time to collect. Professor Kun Xie will share a more proactive and time-efficient approach based on surrogate safety measures (SSMs)\, which can assess safety by capturing the more frequent “near-crash” situations. Massive amounts of data from emerging sources like GPS devices\, smartphone apps\, traffic cameras\, naturalistic driving\, and connected vehicles (CV) can be leveraged to extract SSMs on a large scale\, presenting new opportunities for proactive traffic safety management. Results will show that risk status is a reliable criterion for safety assessment\, and promisingly point towards the use CV data for proactive traffic safety management.
URL:https://c2smart.engineering.nyu.edu/event/proactive-safety-management-empowered-by-big-data/
LOCATION:Virtual\, 6 MetroTech Center\, Brooklyn\, NY\, 11201\, United States
CATEGORIES:Big Data & Planning for Smart Cities,Safety in Transportation Systems,Webinars
ORGANIZER;CN="C2SMART":MAILTO:c2smart@nyu.edu
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