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Full-Text Articles in Urban Studies and Planning
Data Files: Green Waves, Machine Learning, And Predictive Analytics: Making Streets Better For People On Bikes, Stephen Fickas
Data Files: Green Waves, Machine Learning, And Predictive Analytics: Making Streets Better For People On Bikes, Stephen Fickas
TREC Datasets and Databases
The project builds on a prior app that was designed for Green Light Optimized Speed Advisory (GLOSA). This is more colloquially known as keeping a vehicle in the green wave: you are at a location and moving at a speed that will allow you to (theoretically) have a green light at each intersection you encounter along a corridor. Our long-term goal is to extend the FastTrack app described in the Background section to include actuated signals along a corridor. This project takes a first step by evaluating the effectiveness of machine-learning algorithms to predict the next phase of an actuated …
Green Waves, Machine Learning, And Predictive Analytics: Making Streets Better For People On Bikes, Stephen Fickas
Green Waves, Machine Learning, And Predictive Analytics: Making Streets Better For People On Bikes, Stephen Fickas
TREC Final Reports
This project focuses on giving bicyclists a safer and more efficient path through a city’s signalized intersections. It builds on a prior NITC project that tested an app for a fixed-time corridor. The goal of this project is to lay the groundwork for extending this earlier app to include actuated signals. Two machine-learning algorithms are introduced that have a good track record with time-series forecasting: LSTM and 1D CNN. The algorithms are tested on data captured from a busy bike corridor on the south end of the University of Oregon campus. A specific actuated intersection is identified on this corridor …