Chart showing info collected by Quantified Traveler app

The Quantified Traveler app gives users (orange) personalized information about their transportation decisions while collecting travel footprint data for researchers (purple). (Map courtesy San Francisco Municipal Transportation Agency)

Rerouting behavior

Raja Sengupta and Joan Walker, both associate professors of civil and environmental engineering, are tackling traditional challenges in transportation planning with a decidedly nontraditional approach—a blend of behavioral theory and smartphone technology. With their latest project, the Quantified Traveler app, the research group is trying to quantify what influences travel behavior and learn how to encourage more sustainable travel. 

Conventional transportation models are based on assumptions of rational choice and measured in terms of time and money: build a faster and cheaper train, the logic goes, and people will use it. But travel decisions are often irrational. Routine, peer influence and indelible memories of ill-fated public transportation trips override economic self-interest. But irrationality doesn’t have to mean chaos. 

“There’s a rhyme and reason behind irrationality,” says Walker. “People are processing the information differently. A lot of habit and experience goes into making these decisions.”

And since they are not chaotic or arbitrary, travel decisions can be tracked and quantified.

Understanding behavior requires data, which until now came from paper surveys of sample populations and cost millions of dollars. By comparison, a sensing phone app obtains individualized, real-time data with very little cost.

“This takes transportation systems data collection into the big data era,” says Sengupta. 


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