Traveling Smart: Increasing Transit Ridership by Automatic Collection (TRAC) of Individual Travel Behavior Data and Personalized Feedback

Abstract

This final report is the first in a series to describe a new joint collaboration research effort between the Transportation Demand Management Program at the Center for Urban Transportation Research (CUTR), and the Computer Science Engineering Department, at the College of Engineering at the University of South Florida (USF). The research focuses on using innovative technology to better understand and pattern household travel behavior for the purposes of educating, promoting and encouraging households to utilize other alternatives to driving in general and to driving alone in particular. This study documents Phase 1 of the research effort: the development and preliminary testing of a prototype unit and a travel feedback advisory system. The scope of Phase 1 called for preliminary development and testing of a portable unit consisting of a personal digital assistant (PDA), a global positioning system (GPS) device, and a wireless card, all-in-one unit nicknamed TRAC-IT. With innovations emerging daily in this field of technology, a GPS-enabled cellular phone was briefly investigated as a possible alternative for the PDA TRAC-IT unit and showed promise. Phase 2 will investigate and analyze the impact of the travel feedback advisory system on household travel behavior. Phase 3 in this research effort will be dedicated to the design, development, and testing of the GPS-enabled cellular phone as a TRAC-IT unit. The TRAC-IT unit was designed to collect comprehensive individual trip data including start time, end time, origin, destination, travel speed, trip route, and trip distance with minimal input from participants. Limited field testing was conducted to validate that the technology works. The project also developed a preliminary personalized feedback system that provides suggestions and encourages participants to utilize other modes than the drive-alone option. These suggestions were sent to participants after the trip data had been transferred from the TRAC-IT unit into a database developed to pattern travel behavior and generate appropriate feedback to participants.

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