Transportation agencies need travel behavior data to plan changes to their networks, systems, and policies. A new smartphone application developed by a U of M research team makes it easier and less costly to collect this important information and provides richer, more accurate data than traditional methods.
The Daynamica open-source app provides an efficient approach for collecting and processing data for driving, walking, biking or taking transit. It combines smartphone GPS sensing with statistical and machine-learning techniques to detect, identify, and summarize daily activity and travel episodes. The app then allows users to view and annotate information at their convenience.