1 to 10 of 221 Results
May 15, 2026 - SHRP2 Naturalistic Driving Study
Shi, Liang; Jiang, Boyu; Yuan, Zhenyuan; Guo, Feng; Perez, Miguel, 2025, "SynSHRP2: A Synthetic Multimodal Benchmark for Driving Safety Critical Events Derived from Real-World Driving Data", https://doi.org/10.15787/VTT1/FOZRSM, VTTI, V3, UNF:6:yIF2LuLBraPGwkZo/uS6Cg== [fileUNF]
Project Description SynSHRP2 is a large-scale synthetic multimodal dataset derived from the SHRP 2 Naturalistic Driving Study (NDS), focusing on safety-critical driving events such as crashes and near-crashes. The dataset includes over 6,500 events (1,340 crashes and 5,191 near-c... |
May 11, 2026 - SHRP2 Naturalistic Driving Study
Jiao, Yiru; Calvert, Simeon; Costa, Rufina, 2026, "Bird’s eye view trajectory reconstruction of naturalistic crashes and near-crashes in the SHRP2 NDS (Public Version)", https://doi.org/10.15787/VTT1/T7UUC1, VTTI, V2
Project Description This database contains reconstructed bird's eye view trajectories from SHRP2 NDS, including 10,919 safe baseline trips and 8,111 trips involving safety-critical events (crashes and near-crashes). Of the total trips, 3,893 safe baseline and 6,664 safety-critica... |
Feb 24, 2026 - VTTI Public NDS Data
Radlbeck, Joshua; Rossi-Alvarez, Alexandria; Patrick, Rafael; Klauer, Sheila G.; Schaudt, W. Andy, 2026, "Pedestrian External Display Motion Judgment Data", https://doi.org/10.15787/VTT1/PR2F9X, VTTI, V1, UNF:6:TyUWcmVK/WeYJz5/TfmiTQ== [fileUNF]
Project Description: This dataset supports two controlled test track experiments conducted on the Surface Street section of the Virginia Smart Roads in Blacksburg, VA. Data collection for experiment 1 occurred in 2022, and Experiment 2 was completed in 2023. The primary objective... |
Jul 30, 2025 - VTTI Public NDS Data
Ali, Gibran, 2025, "Roadway Traversal and Weather Dataset for Virginia Highways (2021–2022)", https://doi.org/10.15787/VTT1/K70APR, VTTI, V1
Project Description This research project examines how adverse weather conditions affect traffic behavior across Virginia’s roadway network. It integrates large-scale telematics data with high-resolution, model-based weather data to understand impacts on vehicle speeds and safety... |
May 30, 2025 - SHRP2 Naturalistic Driving Study
Jiao, Yiru; Calvert, Simeon, 2025, "Bird’s eye view trajectory reconstruction of naturalistic crashes and near-crashes in the SHRP2 NDS", https://doi.org/10.15787/VTT1/EFYEJR, VTTI, V1
Project Description This database contains reconstructed bird's eye view trajectories from SHRP2 NDS, including 10,919 safe baseline trips and 8,111 trips involving safety-critical events (crashes and near-crashes). Of the total trips, 3,893 safe baseline and 6,664 safety-critica... |
Feb 28, 2024 - CONOPS
Krum, Andrew; Hanowski, Richard; Hammond, Rebecca; Hickman, Jeffrey; Walker, Martin, 2022, "Trucking Fleet Concept of Operations (CONOPS) for Managing Mixed Fleets", https://doi.org/10.15787/VTT1/ZYMSEM, VTTI, V7
Project Description: The CONOPS is a living, comprehensive document that describes the ADS characteristics from the viewpoint of the truck fleets that will use ADS technology. the CONOPS includes eight key sections: 1) Installation and Maintenance Guide for Fleets, 2) Inspection... |
Jan 31, 2024 - Safe-D UTC
Sarkar, Abhijit; Papakis, Ioannis; Herbers, Eillen; Viray, Reginald, 2024, "Development of an Infrastructure Based Data Acquisition System (iDAS) to Naturalistically Collect the Roadway Environment (04-121)", https://doi.org/10.15787/VTT1/FN5TWT, VTTI, V1
Project Description: Automatic traffic monitoring is becoming an important investment for transportation specialists, especially as the overall volume of traffic continues to increase, as do crashes at intersections. Infrastructure cameras can be a good source of information for... |
Jan 30, 2024 - Safe-D UTC
Miller, Marty, 2024, "Investigating and Developing Methods for Traditional Participant-based Data Collection with Remote Experimenters (05-097)", https://doi.org/10.15787/VTT1/HEDSB6, VTTI, V1
Project Description: This project focused on developing tools for performing in-vehicle experiments remotely, i.e. without a researcher in the vehicle with participants. Data Scope: The data uploaded consists of a set of NodeJS and Python tools to simulate and visualize vehicle s... |
Jan 25, 2024 - Safe-D UTC
Terranova, Paolo; Perez, Miguel, 2023, "Characterizing Level 2 Automation in a Naturalistic Driving Fleet (VTTI-00-024)", https://doi.org/10.15787/VTT1/42MUF1, VTTI, V2, UNF:6:kSozA0lDwXTeOARy9aEHuQ== [fileUNF]
Project Description: The introduction of automation features into the vehicle fleet is disrupting the way vehicles operate. Likewise, the introduction of more vehicles with automated features of increasing ability into the fleet can potentially affect what drivers do when the fea... |
Jan 19, 2024 - Safe-D UTC
Jahangiri, Arash; Paolini, Chris; Salehipour, Sina; Bergcollins, Django, 2024, "Developing an Intelligent Transportation Management Center (ITMC) with a Safety Evaluation Focus for Smart Cities (04-110)", https://doi.org/10.15787/VTT1/P9GYI6, VTTI, V1
Project Description: The Intelligent Transportation Management Center (ITMC) project was launched to address the limitations of traditional Transportation Management Centers (TMCs) by integrating advanced technologies such as machine learning, big data science, and image processi... |
