Document Type
Technical Report
Publication Date
3-1-2024
Keywords
Public transportation, travel behavior, GNSS, GPS, mobile app, trip activity, travel diary, OneBusAway
Digital Object Identifier (DOI)
https://doi.org/10.5038/CUTR-NICR-Y3-3-7
Abstract
This research proposes an innovative approach that applies crowdsourced data from mobile applications and GPS technology to enhance the information used in transportation planning modeling activities. The study focused on gathering accurate, real-time travel data through the OneBusAway (OBA) app, a widely used open-source transit user application, and the newly developed Travel Transit Tracker (TTT) app. The goal was to address urban congestion and promote more efficient and sustainable management of transportation systems. The study was conducted by researchers from the University of Puerto Rico at Mayagüez in collaboration with the University of South Florida. The goal was to incorporate user travel patterns into transportation models. While OBA was first used for data collection, its shortcomings in terms of accuracy and functionality prompted the creation of TTT. This companion software improved multimodal tracking and data validation capabilities. The suggested platforms are positioned as fundamental instruments for gathering travel behavior data to empower policymakers and transportation planners to make data-driven decisions. Detailed trip data collected through TTT has the potential to help shape future transportation system optimization plans. Technical issues addressed in the study include data cleaning, GPS accuracy, and software optimization for iOS and Android. Integrating GPS-based mobile applications into transportation planning provides precise data to improve traffic management and reduce congestion. This study can serve as a base for similar applications in other urban areas and highlights the potential of mobile technology to improve urban mobility. The project findings contribute to the ongoing development of data-driven, user-centered transportation planning solutions and suggest that using crowdsourced travel data for planning modeling and analysis can significantly enhance cities' ability to manage traffic congestion.
Scholar Commons Citation
Valdés, Didier M.; Figueroa-Medina, Alberto M.; Cruzado, Ivette; del Valle, Carlos; Martínez, Juan; Santiago, Joshua; and Velásquez, Alonso, "Influencing Travel Behavior via an Open-Source Platform Phase 3: Transforming Multimodal Travel Behavior Data to Support Traffic Congestion Reduction Strategies" (2024). Research Reports. 50.
https://digitalcommons.usf.edu/cutr_nicr/50
Policy Brief
