QualiT

A new smartphone initiative called QualiT, launched this month as part of a collaboration between MIT researchers and the Massachusetts Bay Transportation Authority (MBTA), is allowing riders of the Silver Line to rate their bus trips just like passengers who use ridesharing services such as Uber and Lyft. The new app app combines anonymous feedback with location and other spatial data to identify how user satisfaction relates to actual service quality. Ultimately, the aim is to provide information that can help the MBTA to improve service on this important route.

QualiT works by activating a research platform called Future Mobility Sensing (FM Sensing), developed by researchers from MIT and the Singapore-MIT Alliance for Research and Technology (SMART), where Zegras is a principal investigator. The tool seeks to better understand people’s travel paths and modes by collecting anonymous location data through smartphones’ sensors (such as GPS and WiFi).

Once they have installed the free FM Sensing app, riders will be able to see their own travels displayed on a map that is visible only to them. The app will automatically prompt users to rate their Silver Line trips.

Participation is voluntary, and riders may withdraw at any point by uninstalling the app. The app does not collect personally identifiable information, and the data system is highly encrypted and secured. Data collected will be used for research and service improvement only, and will never be shared with third parties.

The project team, which includes assistant professor Jinhua Zhao of the MIT Department of Urban Planning (DUSP) and Moshe Ben-Akiva, a professor in civil and environmental engineering, is hoping for high levels of rider engagement with QualiT, which will enable the MBTA to gather a wealth of information from passengers about their experiences with the service and plan improvements.

The app’s development involved several departments and groups within MIT that study transportation and urban mobility: DUSP and its Mobility Futures Collaborative; the Department of Civil and Environmental Engineering’s Intelligent Transportation Systems Lab; and SMART through its Future of Urban Mobility research group.