Third Generation Simulation Data (TGSIM): A Closer Look at The Impacts of Automated Driving Systems on Human Behavior
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2024-05-01
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Alternative Title:Third Generation Simulation (TGSIM) Data
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Abstract:This study collected and processed accurate trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments. Multiple methods were utilized to collect data: fixed location aerial videography, moving aerial videography, and infrastructure-based videography. Fixed location aerial videography was used to collect data on I–90/I–94 in Chicago, IL; this methodology collected data using a stationary helicopter hovering over a segment of interest at a higher altitude to capture more roadway in a single image. Moving aerial videography was used to collect four datasets on I–90/I–94 and I–294 in Chicago, IL; this methodology collected data using a helicopter following a string of automated vehicles at a lower altitude as they drive a longer roadway segment. Infrastructure-based videography was utilized to collect data on I–395 in Washington D.C. and on the George Washington University campus (located in the Foggy Bottom neighborhood); this methodology utilized multiple overlapping cameras located on overpasses and buildings stitched together and synchronized, creating a comprehensive field of view of the study area. Extracting multiple vehicle trajectories from video data raises a set of methodological and practical challenges that vary across the three data collection approaches. This report details the methodologies used to collect data and extract vehicle trajectories. Additionally, this report provides a sample analysis showing how the collected data can be utilized in modeling automated vehicle driving behavior. Finally, this report offers a discussion on lessons learned during this project, including data collection set-up, instrumentation, and experimental design.
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