license: cc-by-4.0
pretty_name: WMU AD Assurance Lab drives, 2019-2025
task_categories:
- object-detection
- image-segmentation
tags:
- autonomous-driving
- radar
- camera
- can-bus
- gnss
- lidar
size_categories:
- 100K<n<1M
viewer: false
WMU AD Assurance Lab drives, 2019-2025
Smaller recordings from the AD Assurance Lab at Western Michigan University: a six-camera urban drive, radar test
drives, radar-only drives, ZED 2i campus drives, a 2023 Basler camera test, two camera-LiDAR calibration recordings, a
2025 campus shuttle drive, a 2019 2D-lidar weather test and phone captures of a 2020 snowy highway drive. The Ouster
point clouds from the same recordings are in a companion dataset,
AD-Assurance-Lab/ouster-lidar-drives.
| Collection | When | What | Size |
|---|---|---|---|
kia_urban_2023-12 |
2023-12-04 | one 27-minute urban drive, six cameras, GNSS, road weather, CAN | 28.1 GB |
radar_tests_2023-24 |
2023-12-11 to 2024-03-27 | eight short radar test bags, radar, one camera, CAN | 259 MB |
radar_lidar_2020-21 |
2020-03-05, 2021-01-07 | a highway and a city drive, radar only | 14 MB |
zed2i_campus_2022-07 |
2022-07-27, 2022-07-29 | two campus drives, ZED 2i left camera | 1.6 GB |
lidar_weather_tests_2019 |
Oct-Nov 2019 | 13 static 2D-lidar runs in four weather conditions | 2.5 MB |
phone_snow_2020-02 |
2020-02-09 | 4 phone videos and 16 photos through the windshield on snowy highways | 1.0 GB |
basler_campus_2023-10 |
2023-10-16 | two 40-second camera tests on a campus path and service road, one camera | 172 MB |
calibration_2023-24 |
2023-12-21, 2024-05-10 | two camera-LiDAR chessboard calibration recordings, one camera each | 959 MB |
wmu_shuttle_2025-01 |
2025-01-29 | one 3-minute campus shuttle drive, one camera | 531 MB |
Sensors
| Sensor | Make and model | Collections | Source |
|---|---|---|---|
| Cameras | Basler, 1440×1080 (six at about 15 fps in the urban drive, one in the radar tests, one at about 10 fps on the shuttle, one in each calibration recording; 1280×720 at 30 fps in the 2023 campus test) | kia_urban_2023-12, radar_tests_2023-24, basler_campus_2023-10, calibration_2023-24, wmu_shuttle_2025-01 |
camera_info in the bags |
| Stereo camera | Stereolabs ZED 2i (left eye released), 1920×1080, about 14.6 fps | zed2i_campus_2022-07 |
Carow et al. 2023 |
| Radar | Aptiv (Delphi) ESR 2.5 | radar_tests_2023-24, radar_lidar_2020-21 |
Brown et al. 2022 |
| Second radar | smartmicro UMRR-96 Type 153 (inferred) | point clouds in three radar_tests_2023-24 bags (2024-02-15, 2024-03-27) |
Brown et al. 2023 sensor list |
| GNSS | Swift Navigation Duro (a ruggedized Piksi Multi) | kia_urban_2023-12, radar_tests_2023-24 |
topic names, Brown et al. 2022 |
| Road weather | Lufft MARWIS (serial 10722) | kia_urban_2023-12 |
/LastValues topic |
| 2D lidar | Slamtec RPLIDAR A2 | lidar_weather_tests_2019 |
Goberville et al. 2020 |
| Drive by wire | PolySync OSCC on the lab Kia Niro | kia_urban_2023-12, radar_tests_2023-24 |
Brown et al. 2022 |
| LiDAR | Ouster OS1-64 Gen1, serial 991951000513 (IMU here, plus its metadata in the radar tests and the shuttle; point clouds in the companion dataset) | kia_urban_2023-12, radar_tests_2023-24, calibration_2023-24, wmu_shuttle_2025-01 |
sensor metadata |
Conventions
Every camera stream comes with NAME.frames.parquet, giving per-frame bag time, header stamp and an MD5 of the original
image bytes. Raw-image cameras are released as HEVC 4:4:4 at constant QP 13; JPEG cameras keep their original JPEGs,
remuxed into MJPEG .mkv without re-encoding and verified frame for frame against the MD5s. Lossless FFV1 copies of the
raw-image cameras are kept in the lab archive and are available on request. Other topics are in
sensors/<topic>.parquet, one row per message, and each collection has a SHA256SUMS.
The vehicle CAN bus (/can_frame) is released whole, every ID logged. Only four IDs appear in any recording: 0x2B0
steering angle and 0x220 brake pressure (documented by OSCC and opendbc), and 0xB9 and 0x4B0, which are raw and
undecoded. No OSCC module traffic was logged. can_scan.json lists every ID seen with its frame count.
kia_urban_2023-12: six-camera urban drive on the lab Kia Niro
One 27-minute drive on 2023-12-04 (1,612.6 s).
- Cameras: six Basler cameras at about 15 fps, 24,189 to 24,190 frames each, the raw camera JPEGs remuxed unchanged
into
camera_0N.mjpeg.mkv, with per-cameracamera_info. The rectified streams stay in the archive bag. - GNSS: 1,725 Piksi fixes at about 7 Hz, nearly all RTK, but only in the first 4.3 minutes of the drive, plus the Piksi IMU.
- Ouster IMU and
/tf. - Road condition: MARWIS readings (dry, wet or damp).
- Speed: the roscco
can_frame_speedchannel. - CAN:
/can_framehas every ID seen (0xB9, 0x220, 0x2B0, 0x4B0).
radar_tests_2023-24: radar and camera test bags on the lab Kia
Eight bags of 15 to 37 s each, recorded 2023-12-11 to 2024-03-27, 4.0 minutes in total.
| Data | Bags | Form |
|---|---|---|
| Aptiv ESR tracks, status and raw radar-bus frames | 2023-12-11 and 2024-01-31 | sensors/radar_1_* |
| Second radar's point clouds | 2024-02-15 and 2024-03-27 | sensors/radar_*: x, y, z, radial speed, RCS and SNR per point |
| One Basler camera (raw RGB) | 6 of the bags | HEVC (lossless FFV1 in the archive), 1,787 frames |
| roscco steering, brake and throttle reports, and the derived angle and speed channels | 2024-01-31 and 2024-02-15 | sensors/ |
| Piksi fixes | 2024-02-15 only: 278 standalone (SPP) fixes | sensors/ |
The raw bags of the four 2024-01-31 recordings are also public in
AD-Assurance-Lab/infrastructure-sensing-doe-eems116
(radar retro-reflector tests, DOE award DE-EE0009657).
radar_lidar_2020-21: radar-only drives on the lab car
2020-03-05-radar_lidar_highway(134.4 s, highway): Aptiv ESR tracks, objects, status and the raw radar-bus frames (/can_tx,/can_rx). Its Ouster point clouds are in the companion dataset (highway_2020).2021-01-07-radar_city(40.9 s, city): Aptiv ESR objects only (sensors/as_tx_objects.parquet).
zed2i_campus_2022-07: ZED 2i summer campus drives
| Drive | Date | Duration | Frames |
|---|---|---|---|
Engineering_Drive |
2022-07-27 | 197.8 s | 2,887 |
Campus_Drive_partial |
2022-07-29 | 118.8 s | 1,753 |
Both are ZED 2i left-camera colour at 1920×1080 and about 14.6 fps, with no GNSS, IMU or right eye.
Campus_Drive_partial is the readable start of a recording whose file is damaged after 14.5 GB. The Trimble survey of
the campus route (2022-07-28) is in the lab archive.
lidar_weather_tests_2019: 2D lidar in four weather conditions
Thirteen static runs with a 2D lidar (/scan) aimed at a target at 5, 10 and 15 ft, in rain, cloudy, snowy and fair
conditions, October-November 2019, including one failed fair run that is flagged as such. runs.parquet gives, per
run, the condition, distance, duration and scan count, the mean number of finite returns per scan, and the authors'
published "average hits" on the target (a different measure).
basler_campus_2023-10: Basler camera test on campus
Two recordings on 2023-10-16 (39.8 s and 40.4 s, 1,201 and 1,211 frames) from a single Basler camera at 1280×720 and about 30 fps, mounted low and looking along a campus path and a curved service road, most likely at WMU. Only the camera was logged: no GNSS, IMU or vehicle data, and the platform is not recorded. HEVC, with the lossless FFV1 in the archive.
calibration_2023-24: camera-LiDAR calibration recordings
Two recordings of a chessboard target moved in front of a Basler camera and the Ouster, for camera-LiDAR calibration.
| Recording | Where | Duration | Camera frames | Also |
|---|---|---|---|---|
2023-12-21_cam_lidar |
indoors, in the lab | 91.8 s | 354 at about 4 fps (camera_01) |
camera_info, /tf |
2024-05-10_chessboard |
outdoors, a parking lot | 137.7 s | 4,130 at about 30 fps (camera_front) |
camera_info, /tf, Ouster IMU |
The cameras are HEVC (lossless FFV1 in the archive), with faces blurred (see Privacy). No calibration result was
recorded: /tf holds only the Ouster's internal frames. The LiDAR scans are in the companion dataset
(calibration_2023-24).
phone_snow_2020-02: snowy highway, phone captures
Four videos (1920×1080 at 30 fps, 6.0 minutes in total) and 16 photos (4032×3024) taken with a phone through a car's
windshield on 2020-02-09, on snow-covered highways near Kalkaska in northern Michigan. The video streams and the photo
image data are the phone's originals; the audio tracks and all file metadata were removed. captures.parquet keeps each
file's UTC time, video duration and the phone's GPS position. The photos' positions are the phone's last fix and can lag
by a few minutes.
wmu_shuttle_2025-01: campus shuttle drive
One 179.5 s campus drive on 2025-01-29: a Basler camera at 1440×1080 and about 10 fps, 1,724 frames, as HEVC (lossless
FFV1 in the archive), with its camera_info, the Ouster IMU and metadata, and /tf. GNSS and CAN were not recorded.
The Ouster point clouds and the lidar map built from this drive are in the companion dataset (shuttle_2025-01).
Privacy
The driving cameras face outward. Pedestrians are small and distant; parked-car plates are legible in a few frames and are not blurred, as in the lab's winter-driving release.
In calibration_2023-24 the people moving the chessboard have their faces blurred. Faces and heads were found with
OpenCV YuNet and torchvision Keypoint R-CNN, each box was held two frames either side, and the frames left unblurred
were checked by eye. In a few frames of 2023-12-21_cam_lidar the blur also covers part of the board. The MD5s in
frames.parquet are of the original images, so they do not match these videos; the originals stay in the lab
archive.
Citation
CC BY 4.0. Please cite the paper for the data you use:
lidar_weather_tests_2019: N. A. Goberville, M. El-Yabroudi, M. Omwanas, J. Rojas, R. Meyer, Z. Asher and I. Abdel-Qader, "Analysis of LiDAR and Camera Data in Real-World Weather Conditions for Autonomous Vehicle Operations," SAE Technical Paper 2020-01-0093, 2020, doi:10.4271/2020-01-0093.zed2i_campus_2022-07: K. Carow, P. Kadav, J. Fanas Rojas and Z. Asher, "Projecting Lane Lines from Proxy High-Definition Maps for Automated Vehicle Perception in Road Occlusion Scenarios," SAE Technical Paper 2023-01-0051, 2023, doi:10.4271/2023-01-0051 (the paper's campus route;Engineering_Driveis not in the paper).radar_lidar_2020-21and the lab Kia Niro platform: N. E. Brown et al., "Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform," Sensors 22(16):5999, 2022, doi:10.3390/s22165999. Related: N. E. Brown et al., "Higher Accuracy and Lower Computational Perception Environment Based Upon a Real-time Dynamic Region of Interest," SAE Technical Paper 2022-01-0078, doi:10.4271/2022-01-0078.radar_tests_2023-24: related to N. E. Brown et al., "Real World Use Case Evaluation of Radar Retro-reflectors for Autonomous Vehicle Lane Detection Applications," SAE Technical Paper 2024-01-2042, doi:10.4271/2024-01-2042.kia_urban_2023-12,basler_campus_2023-10,calibration_2023-24,phone_snow_2020-02,wmu_shuttle_2025-01: no paper yet; please cite this dataset.
@misc{wmu_lab_drives_2026,
title = {{WMU AD Assurance Lab} drives, 2019-2025},
author = {{AD Assurance Lab, Western Michigan University} and Asher, Zachary D.},
year = {2026},
howpublished = {Hugging Face dataset},
url = {https://huggingface.co/datasets/AD-Assurance-Lab/lab-drives}
}
Contact: Zachary D. Asher, Western Michigan University, zach.asher@wmich.edu.