pedestrian_crossing — DRIVE `traffic` op

• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)

• Call: import fullseye as fs; fs.ledger.pedestrian_crossing(intent: 'str', *, start_xy=(0.0, -3.0), road_width: 'float' = 7.0, speed: 'float' = 1.2, wait_time: 'float' = 3.0, curb_offset: 'float' = 0.3, along_heading: 'float' = 0.0, dt: 'float' = 0.1, t_end: 'Optional[float]' = None) -> 'Dict[str, object]' (to call the implementation directly, import drivetraffic; drivetraffic.pedestrian_crossing(intent: 'str', *, start_xy=(0.0, -3.0), road_width: 'float' = 7.0, speed: 'float' = 1.2, wait_time: 'float' = 3.0, curb_offset: 'float' = 0.3, along_heading: 'float' = 0.0, dt: 'float' = 0.1, t_end: 'Optional[float]' = None) -> 'Dict[str, object]'; from the registry, opsdrive.get("pedestrian_crossing"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

横断の意図を真値に持つ歩行者の軌跡(区分ごとの閉形式。積分しない)。

道路は x 方向、車道 0 ≤ y ≤ road_width、歩道 y < 0 から始める(`start_xy` の y < −curb_offset)。

• `cross`: (x0, y0) → 縁 (x0, −curb_offset) まで歩き、止まらずに向こうの縁 (x0, road_width + curb_offset)

まで横断して止まる。向きは +π/2(車道の方)。

• `wait_then_cross: 縁まで歩き、**縁で車道を向いて** (+π/2) wait_time` 秒止まり、それから横断する。

• `walk_along: 歩道を向き along_heading`(0 か π)で y = y0 のまま歩く(車道に入らない)。

• `stand_no_cross`: 縁まで歩き、縁で車道を向いて (+π/2) 立ち止まったまま渡らない(バス待ち・連れ待ち)。見た目は

`wait_then_cross の待ちと区別がつかない —— 規則で「止まる」と判断すれば誤検出になる真値。t_cross_start` は None。

速さは `speed(既定 WALK_SPEED` = 1.2 m/s、仮定)。

戻り値 dict: `t (K,)、xy (K, 2)、heading (K,)、phase` (K,) の文字列

("approach" / "wait" / "cross" / "done" / "along")、`intent(真値)、t_cross_start・t_cross_end`

(横断しない意図では None)、`speed`。門: 横断にかかる時間 = (road_width + 2·curb_offset)/speed、待つ人は

待ちの間の位置が一定で向きが +π/2、沿って歩く人は全時刻で y < 0、向きは位置の差分の向きと一致。

Raises `ValueError`: 未知の intent、speed ≤ 0、start が歩道上でない、along_heading が 0/π でない。

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_driving_traffic — py -3.11 examples/poc_driving_traffic.py

Ops the type connects to (they accept `table` as input)

course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same

Same category (`traffic`)

idm_accel · idm_equilibrium_gap · idm_platoon_simulate · driver_style · lateral_wobble · ou_estimate · social_force_step · occlusion_reveal_distance

*Provenance: drivetraffic.py — DRIVE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

pedestrian_crossing — DRIVE traffic op