Discovering the happiest mode of transportation

Activities and trips detected by the Daynamica smartphone application can be easily be annotated by users, allowing researchers to collect data about the emotions associated with those. The following screenshot shows an example survey for collecting companionship and emotion data associated with a completed activity.

A recent paper published in the journal Transport Findings and co-authored by Dr. Yingling Fan and Dr. Julian Wolfson used Daynamica to study trip-associated emotions for individuals in the Minneapolis-St. Paul metro area.

Here’s the abstract:

Understanding trip happiness—a measurement of people’s emotional well-being during trips—is an essential aspect of people-oriented transportation planning. We use data collected via smartphones from 350 residents in the Minneapolis-St. Paul region to examine trip- and person-level factors associated with trip happiness. Trip mode, purpose, duration, distance, companionship, activities during the trip, and temporal characteristics of the trip are significantly associated with trip happiness. Mode and companionship are the strongest predictors of trip happiness. Among personal factors, age is the strongest predictor, followed by general happiness of the person. Race, gender, and neighborhood have modest effects on trip happiness.

From Understanding Trip Happiness using Smartphone-Based Data: The Effects of Trip- and Person-Level Characteristics

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