Transforming multi-modal travel behavior data from an open-source platform to support traffic congestion reduction strategies
Multimodal transportation, such as transit, bike, walk, ride-hailing (e.g., Uber, Lyft), car-share, and bike-share, are vital to supporting livable communities. However, activity data of travelers using these modes have been difficult to acquire. In the NICR project 3.1 “Influencing Travel Behavior via an Open Source Platform”, the research team evaluated the accuracy and precision of the activity transition timing and location of data collected using OneBusAway, an open-source mobile transit app deployed in nine cities. Accuracy and precision were determined by comparing data from OBA with ground truth information manually recorded by the research team. While around 90% of detected activity transitions were within 4 minutes, and approximately 93% of the detected activity start locations had a position error less than 861 meters (0.54 miles), additional processing is needed to transform the data into origins, destinations, and behavioral data that are required by travel behavior researchers, practitioners, and city planners. The proposed research will leverage ground truth data collected in the NICR Year 1 project to develop intelligent models to infer missing and incomplete travel behavior characteristics from the OneBusAway data to provide trip origin, destination, and mode. The research team will deploy these models to provide an enhanced picture of the travel behavior of OneBusAway users in Mayaguez, Puerto Rico. The team will use the database generated by the intelligent model and additional transportation system information to conduct demand analysis and identify demand patterns and their impact on traffic congestion. The resulting model and tools will be immediately applicable to all nine cities that have deployed OneBusAway to better understand the relationship between multimodal travel behavior and traffic congestion. Using crowdsourcing, big data science, and machine learning, these tools will help transportation agencies deploy new, automated strategies to improve congested multimodal systems in the immediate future.
Language
- English
Project
- Status: Active
- Funding: $159343
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Contract Numbers:
69A3551947136
79075-00-A
79075-22
79075-23
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590National Institute for Congestion Reduction
University of South Florida
Tampa, FL United States 33620 -
Managing Organizations:
National Institute for Congestion Reduction
University of South Florida
Tampa, FL United States 33620 -
Project Managers:
Zhang, Yu
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Performing Organizations:
National Institute for Congestion Reduction
University of South Florida
Tampa, FL United States 33620University of Puerto Rico at Mayagüez
Department of Civil Engineering and Surveying
PO Box 9000
Mayagüez PR 00681-9000, PR United States 00681-9000 -
Principal Investigators:
Barbeau, Sean
Valdes Diaz, Didier
- Start Date: 20220601
- Expected Completion Date: 20230630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Data quality; Information processing; Mobile applications; Mode choice; Origin and destination; Travel behavior
- Identifier Terms: OneBusAway
- Subject Areas: Data and Information Technology; Transportation (General);
Filing Info
- Accession Number: 01853952
- Record Type: Research project
- Source Agency: National Institute for Congestion Reduction
- Contract Numbers: 69A3551947136, 79075-00-A, 79075-22, 79075-23
- Files: UTC, RIP
- Created Date: Aug 7 2022 9:46AM