Monitoring Traffic for Incidents and Extreme Congestion Events


flickr photo shared by canihazit under a Creative Commons ( BY-NC-ND ) license

Last week's Friday Seminar welcomed back ITS alumn, now Univeristy of Illinois Urbana-Champaign Assistant Professor, Dan Work. He presented some of his work in the area of monitoring traffic data to better responde to incidents and extreme congestion events. The talk began with focus on how his group uses the app TrafficTurk for low-cost traffic sensing, which has been used in managing big events like homecoming weekend at University of Illinois and the Farm Progress Shows in Decatur, IL (where over 100,000 people flock for the event). He then talked about how he's used this sensing data to more quickly respond to traffic incidents through multiple model particle filtering. He concluded the talk preseting some preliminary results from New York City taxi data (which is shared here as open data) on the congestion in the city following Hurricane Sandy. The data shows that there was not much congestion during evacuation, as there was a system and a plan in place, but that the extreme congestion after the storm shows a need for better post-event planning and coordination. 

You can find more of Work's publications (and source code) here