Datasets:

AD-Assurance-Lab
/

lab-drives

---
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`](https://huggingface.co/datasets/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-camera `camera_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_speed` channel.
* **CAN:** `/can_frame` has 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`](https://huggingface.co/datasets/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_Drive` is not in the paper).
* **`radar_lidar_2020-21`** and 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.
```bibtex
@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.

	---
	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`](https://huggingface.co/datasets/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-camera `camera_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_speed` channel.
	* CAN: `/can_frame` has 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`](https://huggingface.co/datasets/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_Drive` is not in the paper).
	* `radar_lidar_2020-21` and 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.

	```bibtex
	@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.