Smart Trucking Hackathon

ROUTE DRIVE DELIVER BETTER. the problem In New York City, all vehicles defined as a truck are required to follow the truck route network and are reliant on a static

Improving Traffic Safety Risk Analysis Through Big Data

How do we know whether a section of the roadway is at high safety risk?

Historically, the answer has been relatively straightforward: we count the number of crashes at that location over a period of time and compare it to other roadway sections. If the roadway section of our interest contains a high number of crashes, we then decide what can be done, if anything, to lower the number of crashes.

This method has been the go-to method for safety evaluation for decades, and with good reason. The number of crashes (or other crash-based safety measures) at a roadway section is a fairly straightforward piece of evidence regarding its relative safety risk level.

There’s only one problem with it, which is that in order to obtain this data, we have to wait for crashes to happen.

But, thanks to big data, there is a different way to do things.

C2SMART Students Present at the ITS-NY Annual Meeting

ITS New York held its 29th Annual Meeting and Technology Exhibition on Thursday, June 16 – Friday June 17, 2022 in Saratoga Springs, New York. C2SMART was well-represented at the event, with three student presenters and a booth where we were able to meet other attendees and discuss C2SMART’s work and ongoing projects.

C2SMART Featured in IEEE Spectrum

C2SMART Director Kaan Ozbay, along with Senior Research Associate Jingqin Gao, were interviewed by IEEE Spectrum’s Dexter Johnson for the June 2022 issue, which features an article on C2SMART’s Mobility Dashboard called AI Tool for COVID Monitoring Offers Solution for Urban Congestion. 

Daniel Vignon

Daniel Vignon is currently pursuing his PhD in Civil Engineering and MA in Economics at the University of Michigan. Under the supervision of Professor Yafeng Yin, his research seeks to inform the design, regulation and operation of emerging mobility services and of smart infrastructure systems. Drawing from his background in both engineering and economics, he models and analyzes the interactions of these systems with different markets, studies their impact on social welfare, and designs policies to maximize welfare. He holds a BSc in Mechanical Engineering from the Massachusetts Institute of Technology.

Eugene Vinitsky

Eugene Vinitsky has a PhD in controls and optimization from UC Berkeley’s Mechanical Engineering department. Prior to that, he received his MS in physics from UC Santa Barbara and a BS in physics from Caltech.