Introduction to the Third Generation Simulation Dataset: Data Collection and Trajectory Extraction

Abstract

This study aims to provide accurate trajectory datasets capable of characterizing human–automated vehicle interactions under a diverse set of scenarios in diverse highway environments. Distinct methods were utilized to collect data from Level 1, Level 2, and Level 3 automated vehicles: (1) fixed location aerial videography (a helicopter hovers over a segment of interest); (2) moving aerial videography (a helicopter follows the automated vehicles as they move in a much longer segment than in the first method); and (3) infrastructure-based videography (multiple overlapping cameras located on overpasses creating a comprehensive image of the study area). Utilizing the fixed location aerial videography approach, trajectories were extracted on I-90/I-94 in Chicago, IL. The moving aerial videography approach was adopted to extract four datasets on I-90/I-94 and I-294 in Chicago, IL. Finally, two datasets were collected on I-395 and George Washington University Campus in Washington, D.C., using the infrastructure-based videography approach. Extracting multiple complete and accurate vehicle trajectories raises a set of methodological and practical challenges that vary across the three data measurement approaches. The methodological details to extract these trajectories are presented in this paper along with the lessons learned with respect to data collection setup, instrumentation, and experimental design efforts.