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The JWT signature verification failed. Check the signing key and the algorithm.
Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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SimLingo CARLA Dataset (Raw, 4Hz)

Raw driving data from CARLA simulator. No transformations or derived fields - all original measurements preserved as-is.

Dataset Summary

  • Source: SimLingo (CVPR 2025)
  • Scale: 228,757 frames (23 shards)
  • Frame Rate: 4 FPS
  • Resolution: 1024x512 RGB
  • Routes: Complete driving episodes (routes never split across shards)

Column Schema

Core Fields

Column Type Description
route_id string Route identifier
frame_idx int32 Frame index within route
image bytes Original JPEG image bytes

Control Signals (Raw)

Column Type Description
steer float32 Steering [-1, 1]
throttle float32 Throttle [0, 1]
brake bool Brake applied

Vehicle State

Column Type Description
speed float32 Current speed (m/s)
target_speed float32 Target speed
speed_limit float32 Speed limit
theta float32 Heading angle
angle float32 Angle to target

Navigation

Column Type Description
command int32 Navigation command
next_command int32 Next navigation command
pos_global string (JSON) Global position [x, y]
target_point string (JSON) Target point
target_point_next string (JSON) Next target point
aim_wp string (JSON) Aim waypoint
route string (JSON) Planned route waypoints
route_original string (JSON) Original route waypoints
changed_route bool Route was changed

Hazards & Environment

Column Type Description
junction bool In junction
vehicle_hazard bool Vehicle hazard detected
vehicle_affecting_id int32 ID of affecting vehicle
walker_hazard bool Pedestrian hazard
walker_affecting_id int32 ID of affecting pedestrian
light_hazard bool Traffic light hazard
stop_sign_hazard bool Stop sign hazard
stop_sign_close bool Stop sign nearby
walker_close bool Pedestrian nearby
walker_close_id int32 ID of nearby pedestrian
speed_reduced_by_obj_type string Object type causing speed reduction
speed_reduced_by_obj_id int32 Object ID causing speed reduction
speed_reduced_by_obj_distance float32 Distance to speed-reducing object
control_brake bool Control brake applied

Augmentation (from SimLingo)

Column Type Description
augmentation_translation float32 Translation augmentation
augmentation_rotation float32 Rotation augmentation

Transforms

Column Type Description
ego_matrix string (JSON) 4x4 ego vehicle transform matrix
boxes string (JSON) 3D bounding boxes for all objects

Commentary (Optional)

Column Type Description
commentary string Natural language commentary
commentary_data string (JSON) Full commentary object with metadata

Usage

from datasets import load_dataset
import json

ds = load_dataset("TESS-Computer/carla-simlingo-raw", split="train")

sample = ds[0]
print(sample['route_id'])
print(sample['steer'], sample['throttle'], sample['brake'])
print(sample['speed'])

# Parse JSON fields
pos = json.loads(sample['pos_global'])
boxes = json.loads(sample['boxes']) if sample['boxes'] else []

Data Collection

  • Simulator: CARLA 0.9.15 (Leaderboard 2.0)
  • Expert: PDM-Lite (rule-based, 100% route completion)
  • Scenarios: Single-scenario routes with random weather
  • Towns: Towns 1-13

Citation

@inproceedings{renz2025simlingo,
  title={SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment},
  author={Renz, Katrin and Chen, Long and Arani, Elahe and Sinavski, Oleg},
  booktitle={CVPR},
  year={2025},
}

License

MIT (dataset processing code). Original data subject to SimLingo and CARLA licenses.

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