3-1.1: Influencing Travel Behavior via Open-Source Platform: Implementation of OneBusAway in Mayagüez
| Principal Investigator | Didier M. Valdés-Díaz, Ph.D. |
| Final Report (DOI) | View Final Report |
| TRID | Available Soon |
| Policy Brief | Available Soon |
Abstract
This project will use the open-source platform OneBusAway developed at USF to explore how travelers choose between public transit, transportation network companies (TNC), and other modes (e.g., micro-mobility) and how to influence this behavior. The project will focus on first and last-mile connections and filling gaps in the transit network, as well as older adults, people with disabilities and other vulnerable populations. We will also explore ways that alternative modes can assist transit during emergencies. In particular, we will study how mobility service providers can better support transit operations (e.g., route replacement, optimization, seamless mobility platforms for routing, booking, and payment); and how best to “message” travelers in real-time (via texts, emails, etc.) to nudge them toward making congestion reducing travel choices, including taking public transportation. OneBusAway currently provides real-time transit information to users on a full range of devices and communications modes (e.g., mobile apps, text messaging, etc.) and serves more than 400,000 individuals across ten cities in the United States. The objective of this project is to expand OneBusAway by including information on mobility providers in the city of Mayagüez, Puerto Rico. The UPRM NICR team will coordinate the activities to implement OneBusAway with one of the bus services operating in Mayagüez. To evaluate the effectiveness of the implementation of OneBusAway, before and after studies will be conducted, including focus groups, ridership studies, and a travel survey. Transit performance models and activity integration strategies developed in UPRM to increase ridership will be applied. A new survey tool will be developed and embedded in the platform to solicit information on the travel choices of users and their motivations. Statistical and econometric methods will be used to analyze focus groups and to determine what influences travel preferences.
