The latest report to come out of this multi-project research effort, led by Dr Stephen Fickas of the University of Oregon (UO), introduces machine-learning algorithms to work with their mobile app FastTrack.
Developed and tested in earlier phases of the project, the app allowed cyclists in Eugene, Oregon, to communicate with traffic signals along a busy bike corridor. The researchers hope to make their app available in other cities.
“Our overall goal is to give cyclists a safer and more efficient use of a city’s signalled intersections,” Fickas explained. “The current project attempts to use two deep-learning algorithms, LSTM and 1D CNN, to tackle time-series forecasting. The goal is to predict the next phase of an upcoming, actuated traffic signal given a history of its prior phases in a time-series format. We’re encouraged by the results.”
Their latest work builds on two prior projects in which Fickas and his team successfully built and deployed a...