Go ahead, rant about the snow on Twitter. It can ease traffic on slippery, congested roads.
That’s the crux of a study that examined how weather-related tweets can be analyzed to bolster computer models which, among other things, recommend safe driving speeds and which roads motorists should avoid during inclement weather.
“It doesn’t matter if someone tweets about how beautiful the snow is or if they’re complaining about unplowed roads. Twitter users provide an unparalleled amount of hyperlocal data that we can use to improve our ability to direct traffic during snowstorms and adverse weather,” said Adel Sadek, director of UB’s Institute for Sustainable Transportation and Logistics, and the study’s lead author.
Co-authors of the study, which was published in the journal Transportation Research Record, include Qing He, Stephen Still Assistant Professor in Transportation Engineering and Logistics; Jing Gao, assistant professor in the Department of Computer Science and Engineering; Ming Ni, a PhD candidate at UB; and Lei Lin, who earned a PhD from UB in 2015.
The study was funded in part by the Transportation Informatics Tier I University Transportation Center.