Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data

Goberville, Nick

doi:10.15483/1993980

Title: Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data

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Abstract

As part of the sensor characterization task of the SMART 2.0 project, this dataset includes raw data from three spinning lidars ([Ouster OS2-128](https://ouster.com/products/scanning-lidar/os2-sensor/), [Velodyne Puck (VLP-16)](https://velodynelidar.com/products/puck/), and [Velodyne Ultra Puck (VLP-32)](https://velodynelidar.com/products/ultra-puck/)), one camera ([Mako G-319](https://www.alliedvision.com/en/camera-selector/detail/mako/g-319/)), and one present weather sensor ([Vaisala FD-70](https://www.vaisala.com/en/products/weather-environmental-sensors/forward-scatter-fd70)). All data were synchronized, with the log start time indicated in the file name (HHMMSS). The data can be filtered by date, log time (HHMMSS), sensor, frame ID, and weather classification. These data were gathered statically at the Argonne Testbed for Multiscale Observational Science (ATMOS). Two target stop signs were placed in view of the sensors to contribute a target for comparing sensor data under different conditions. The weather data for each day are stored in netCDF “.nc” files. The lidar data contain the X, Y, Z, intensity, reflectivity, and ring from Ouster OS2-128 rev6, Velodyne VLP-16, and Velodyne VLP-32 lidars. ![raw lidar image](LiDAR_pointcloud_ATMOS.png)

Authors:

Goberville, Nick

Argonne National Laboratory

Publication Date:: Fri Dec 12 04:00:00 UTC 2025

DOE Contract Number:: AC05-76RL01830

Research Org.:: National Renewable Energy Laboratory; Pacific Northwest National Laboratory; Idaho National Laboratory

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office (EE-3V)

Subject:: 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; automated/autonomous vehicles; cooperative adaptive cruise control; light-duty vehicles; sensor fusion

OSTI Identifier:: 1993980

DOI:: https://doi.org/10.15483/1993980

Citation Formats


                    Goberville, Nick. Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data.  United States: N. p., 2025. 
        Web.  doi:10.15483/1993980.

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                    Goberville, Nick. Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data.  United States.  doi:https://doi.org/10.15483/1993980

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                    Goberville, Nick. 2025.  
"Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data".  United States.  doi:https://doi.org/10.15483/1993980.  https://www.osti.gov/servlets/purl/1993980. Pub date:Fri Dec 12 04:00:00 UTC 2025

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@article{osti_1993980,

  title        = {Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data},

  author       = {Goberville, Nick},

  abstractNote = {As part of the sensor characterization task of the SMART 2.0 project, this dataset includes raw data from three spinning lidars ([Ouster OS2-128](https://ouster.com/products/scanning-lidar/os2-sensor/), [Velodyne Puck (VLP-16)](https://velodynelidar.com/products/puck/), and [Velodyne Ultra Puck (VLP-32)](https://velodynelidar.com/products/ultra-puck/)), one camera ([Mako G-319](https://www.alliedvision.com/en/camera-selector/detail/mako/g-319/)), and one present weather sensor ([Vaisala FD-70](https://www.vaisala.com/en/products/weather-environmental-sensors/forward-scatter-fd70)). All data were synchronized, with the log start time indicated in the file name (HHMMSS). The data can be filtered by date, log time (HHMMSS), sensor, frame ID, and weather classification. These data were gathered statically at the Argonne Testbed for Multiscale Observational Science (ATMOS). Two target stop signs were placed in view of the sensors to contribute a target for comparing sensor data under different conditions. The weather data for each day are stored in netCDF “.nc” files. The lidar data contain the X, Y, Z, intensity, reflectivity, and ring from Ouster OS2-128 rev6, Velodyne VLP-16, and Velodyne VLP-32 lidars. ![raw lidar image](LiDAR_pointcloud_ATMOS.png)},

  doi          = {10.15483/1993980},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Dec 12 04:00:00 UTC 2025},

  month        = {Fri Dec 12 04:00:00 UTC 2025}

}

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DOI: https://doi.org/10.15483/1993980

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