Virtual Trajectories for I–24 MOTION: Data and Tools

Conference · Mon Feb 26 04:00:00 EST 2024 · 2024 Forum for Innovative Sustainable Transportation Systems (FISTS)

DOI:https://doi.org/10.1109/fists60717.2024.10485593· OSTI ID:2545926

Ji, Junyi ^[1]; Wang, Yanbing ^[2]; Gloudemans, Derek ^[2]; Zachár, Gergely ^[2]; Barbour, William ^[2]; Work, Daniel B. ^[1]

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1. Department of Civil and Environmental Engineering
2. Institute for Software Integrated Systems, Vanderbilt University

This paper introduces a toolbox for generating virtual trajectories, which we call VT-tools v1.0, to address challenges in analyzing large but imperfect trajectory datasets. VT-tools v1.0 is able to generate virtual trajectories from large raw datasets that are typically challenging to process due to their size. We also provide a set of these virtual trajectories resulting from I–24 MOTION INCEPTION v1.0 data and demonstrate the practical utility of these trajectories in as-sessing speed variability and travel times across different lanes within the INCEPTION dataset. The virtual trajectory toolbox opens future research on traffic waves and their impact on energy. The VT-tools v1.0 Python implementation and sample data are publicly available at https://i24motion.org.

• Research Organization: UC Berkeley; Vanderbilt University; Rutgers University-Camden; Temple University
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO)
• DOE Contract Number: EE0008872
• OSTI ID: 2545926
• Conference Information: Journal Name: 2024 Forum for Innovative Sustainable Transportation Systems (FISTS)
• Country of Publication: United States
• Language: English

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