By Brett DeNeve:
Vehicles usually tell us when something is wrong, via some type of illuminated icon, with ample time to get it to a garage or gas station for proper maintenance. Imagine a world where cars also gave us an alert about an accident that just occurred an exit or two up from our current location on the highway, prompting us to prepare to proceed with caution and possibly be prepared to detour.
Although this is not yet a reality, a research group at the University of Buffalo is attempting to harness said information our cars could be giving us by outfitting vehicles with a device that is connected and constantly feeding into a data mining system that tracks real-time traffic through cameras, toll barriers and more.
I don’t know how George Orwell would react to this, but there are definitely some crazy drivers out there; one step towards people knowing your every move inside your automobile, one step towards safer roads. This could be a hard choice for some individuals, but for Adel Sadek, the decision is quite clear.
“Our goal is to gather and analyze the wealth of data being collected by GPS units, smartphones and other devices,” said Sadek, PhD, UB civil engineer and the lead investigator. “We’ll then use this information to enhance the safety, sustainability, economic competitiveness and resiliency of our transportation system, and to inform transportation policy.”
The grant, awarded by the U.S. Department of Transportation, is a great help to UB’s new Institute for Sustainable Transportation and Logistics. It will fund multi- disciplinary research that utilizes data fusion and, ultimately, improves the safety and efficiency of our highways, transit systems and other transportation system components.
‘Big data’ refers to any data set that is too large or too complex to analyze using traditional methods. Researchers must build computer models to break down, or ‘mine,’ said information to find relevant correlations.
Sadek, professor in UB’s Department of Civil, Structural and Environmental Engineering, is taking this approach to transportation systems. For example, he is working on a model that mines historic data and considers current conditions to predict future border crossing delays. Another model provides motorists with directions designed to limit greenhouse gas emissions from their vehicle.
As described earlier, another component of using big data to solve transportation problems involves suiting up vehicles with systems that observe road or weather conditions. The vehicles then send data to a processing center, which analyzes it and replies to the vehicles with something along the lines of avoiding ice-covered roads.
An example of this is can be found in the Buffalo Niagara region. CUBRC, a not-for-profit research corporation based in Cheektowaga, has equipped hundreds of vehicles with cameras and sensors that hope to gain a better understanding of the interaction between the driver, vehicle and road conditions.
CUBRC will work with UB and the institutes of higher learning funded by the grant -Rensselaer Polytechnic Institute, George Mason University, and the University of Puerto Rico at Mayaguez – to analyze the data to better understand traffic safety and driver behavior.
The grant, which recognizes UB as one of 33 University Transportation Centers nationwide, comes months after UB established the Institute for Sustainable Transportation and Logistics, a joint effort between UB’s School of Engineering and Applied Sciences and its School of Management.
The institute is one of 10 initiatives created via the university’s 2012-13 E-Fund program.
“The grant follows a substantial new investment by UB in specific high-impact, high-return strategic initiatives that are responsive to NY SUNY 2020 and UB priorities,” said Liesl Folks, engineering school dean. “This new collaborative research program will allow UB and its partners to make a significant impact in this area of national concern.”
Photo: UB’s Adel Sadek, PhD, mines “big data” to help solve regional and national transportation issues. Photo by Doug Levere