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.
Navigating sidewalks and intersections affected by road construction can be challenging for all pedestrians, but it’s especially difficult for those who are blind or visually impaired.
To help these pedestrians find their way safely, U of M researchers have developed a smartphone app that can detect upcoming work zones and provide routing instructions. The project, funded by the Minnesota Department of Transportation (MnDOT), was led by senior systems engineer Chen-Fu Liao at the U’s Minnesota Traffic Observatory.
Tagged with: intersections
, visually impaired
, work zones
Posted in Intelligent Transportation Systems (ITS)
, Transportation research
, Urban transportation