predict_amber_onset — DRIVE decide op

• Data kinds: table → table

• Call: import fullseye as fs; fs.ledger.predict_amber_onset(observations, *, flash_duration: 'Optional[float]' = None, crossing_length: 'Optional[float]' = None, walk_speed: 'float' = 1.0, ped_red_to_amber: 'float' = 2.0, t_now: 'Optional[float]' = None) -> 'Dict[str, object]' (to call the implementation directly, import drivedecide; drivedecide.predict_amber_onset(observations, *, flash_duration: 'Optional[float]' = None, crossing_length: 'Optional[float]' = None, walk_speed: 'float' = 1.0, ped_red_to_amber: 'float' = 2.0, t_now: 'Optional[float]' = None) -> 'Dict[str, object]'; from the registry, opsdrive.get("predict_amber_onset"))

Usage

Estimates the start of the vehicle amber from observations of the parallel pedestrian signal ((t, state) in time order, state ∈ green / flash / red).

> The detailed description below is the original text — the summary and the headings are translated.

F = flash_duration(無ければ crossing_length / walk_speed)、Δ = ped_red_to_amber。観測の切り替わり(green→flash、flash→red)ごとに黄の時刻が入る区間を作り、その 積 をとる:

green→flash(最後の green t_g、最初の flash t_f): 黄 ∈ [t_g + F + Δ, t_f + F + Δ]

flash→red (最後の flash t_f'、最初の red t_r): 黄 ∈ [t_f' + Δ, t_r + Δ]

返り値: amber_onset(区間の中点)、lo / hi、half_width(誤差の上限)、remaining = amber_onset − t_now(既定 = 最後の観測時刻)、basis(使った切り替わり)。切り替わりが 1 つも無ければ ValueError(青が続いているだけでは「いつ点滅するか」は分からない)。区間が空(観測と F・Δ が矛盾)も ValueError。

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_decisions — py -3.11 examples/poc_driving_decisions.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 (decide)

mirror_reflection_matrix · mirror_virtual_camera · mirror_aim_normal · convex_mirror_fov · mirror_blind_zone · check_sequence_score · signal_phase_plan · signal_state


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

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.