README.md

metadata

license: other
license_name: upstream-assets-see-acknowledgements
pretty_name: munich2drive
task_categories:
  - video-classification
tags:
  - autonomous-driving
  - trajectory-prediction
  - motion-planning
  - carla
  - commonroad
  - sumo
  - surround-view
  - munich
size_categories:
  - n<1K
dataset_info:
  features:
    - name: mp4
      dtype: video
    - name: clip_id
      dtype: string
    - name: scenario_id
      dtype: int64
    - name: ego_id
      dtype: int64
    - name: version
      dtype: string
    - name: map
      dtype: string
    - name: weather
      dtype: string
    - name: sun_altitude_deg
      dtype: float64
    - name: precipitation
      dtype: float64
    - name: wetness
      dtype: float64
    - name: night
      dtype: bool
    - name: n_agents
      dtype: int64
    - name: agents_by_type
      struct:
        - name: CAR
          dtype: int64
        - name: TRUCK
          dtype: int64
        - name: BUS
          dtype: int64
        - name: BICYCLE
          dtype: int64
        - name: MOTORCYCLE
          dtype: int64
    - name: horizon_steps
      dtype: int64
    - name: dt_s
      dtype: float64
    - name: audit_clean
      dtype: bool
    - name: max_pose_error_m
      dtype: float64
    - name: max_height_dev_m
      dtype: float64
    - name: ground_layer_corrections
      dtype: int64
    - name: actors_inherited
      dtype: int64
    - name: actors_surviving_cleanup
      dtype: int64
    - name: ego_blueprint
      dtype: string
    - name: ego_collision_events
      dtype: int64
    - name: ego_collisions
      list:
        - name: time_step
          dtype: int64
        - name: other
          dtype: string
        - name: other_id
          dtype: int64
        - name: impulse
          dtype: float64
    - name: trajectory
      struct:
        - name: t
          list: int64
        - name: x
          list: float64
        - name: 'y'
          list: float64
        - name: carla_x
          list: float64
        - name: carla_y
          list: float64
        - name: yaw
          list: float64
        - name: v
          list: float64
        - name: a
          list: float64
        - name: yaw_rate
          list: float64
    - name: n_states
      dtype: int64
    - name: path_length_m
      dtype: float64
    - name: speed_mps
      struct:
        - name: mean
          dtype: float64
        - name: max
          dtype: float64
    - name: ego_length_m
      dtype: float64
    - name: ego_width_m
      dtype: float64
    - name: trajectory_source
      dtype: string
  splits:
    - name: train
      num_bytes: 5646498356
      num_examples: 500
  download_size: 5646727502
  dataset_size: 5646498356
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

munich2drive

Surround-camera driving clips from a real Munich HD map built by SimForge, each paired with the ego vehicle's full trajectory. Every clip is a nine-panel video -- six surround cameras at the ego's real sensor extrinsics, a chase view, a bird's-eye view, and the frame-locked CommonRoad ground truth -- so what the model sees and what the data says are visible side by side.

• 500 clips over 50 base scenarios (500 sumo)
• 61,200 agent-replays, 79-161 agents per clip
• 12 weather / time-of-day conditions, 20 at night
• ego paths 10.64-232.85 m (median 108.96 m)

Each row

field
mp4	the 3x3 grid clip (1920x1080, 10 fps, 120 frames)
json	everything below, as one record
trajectory	parallel arrays: t, x, y, carla_x, carla_y, yaw, v, a, yaw_rate
path_length_m, speed_mps	trajectory summary
weather, sun_altitude_deg, precipitation, wetness, night	conditions
n_agents, agents_by_type	surrounding traffic
ego_collision_events, ego_collisions	ego collision-sensor events with impulses
audit_clean, max_pose_error_m, max_height_dev_m	per-clip verification, below

x/y are the CommonRoad map frame -- the frame the CommonRoad panel of the video is drawn in. carla_x/carla_y are the same states in the CARLA world frame, via the verified transform (carla_x = lx, carla_y = -ly after reprojecting EPSG:3857 to the map's local transverse-Mercator frame; crdesigner emits 3857, which is ~1.5x scale-distorted at 48N, so this conversion is not optional).

The trajectory is given in world coordinates; ego-relative future waypoints follow from the state at any t by the usual rigid transform.

Verification

Rendering audits each clip against its scenario file at 14 time steps and ships the result, so these are measurements, not claims:

• audit_clean: 500 / 500
• agent pose error vs CommonRoad: median 0.003 m, p99 0.022 m, max 1.297 m
• height deviation: median 0.034 m, p99 0.248 m, max 0.302 m
• clips rendered with actors inherited from a previous run: 0; with actors surviving cleanup: 0
• clips with at least one ego collision event: 6 of 500. Of the 11 events, 7 are contacts with static traffic signs and 4 with vehicles -- the sensor reports contact with anything, so this is not a vehicle-collision rate

Known limitations

• Traffic is replayed kinematically from recorded SUMO trajectories and does not react to the ego. The ego collisions present are therefore predominantly rear-end contacts caused by non-reactive traffic, not ego-at-fault conflicts.
• Where SUMO placed two footprints overlapping, the render shows them interpenetrating.
• The ego is rendered with a stand-in mesh (vehicle.volkswagen.t2_2021), identical across all clips. Its footprint throughout the CommonRoad and SUMO data is the real EDGAR size, 4.973 x 1.941 x 2.320 m, so the trajectories are unaffected.

Acknowledgements

Munich HD map from SimForge; ego vehicle and motion planner from TUM-AVS (EDGAR digital twin, Frenetix); built on CARLA, CommonRoad and SUMO. Observe the upstream licences of the HD map, simulator assets and vehicle models.