traffic op• Data kinds: none → any (an op determined by its arguments alone — it takes no image or data input)
• Call: import fullseye as fs; fs.ledger.passing_decision(dist_oncoming: 'float', parked_len: 'float', margin_front: 'float', margin_back: 'float', v_ego: 'float', v_oncoming: 'float', *, lane_change_time: 'float', ego_length: 'float' = 0.0, pet_min: 'float' = 0.0, v_obstacle: 'float' = 0.0) -> 'str' (to call the implementation directly, import drivetraffic; drivetraffic.passing_decision(dist_oncoming: 'float', parked_len: 'float', margin_front: 'float', margin_back: 'float', v_ego: 'float', v_oncoming: 'float', *, lane_change_time: 'float', ego_length: 'float' = 0.0, pet_min: 'float' = 0.0, v_obstacle: 'float' = 0.0) -> 'str'; from the registry, opsdrive.get("passing_decision"))
> This operator's description has not been translated yet. The original text follows as it is.
対向車までの距離 `dist_oncoming`(判断時、自車が x_in にいるとき)で "go" か "wait" を返す。
D ≥ D*(`passing_gap_required の d_required`)なら "go"(境目ちょうどは PET = pet_min で go)。
`dist_oncoming = +inf` は「対向車なし」= "go"(他の引数の検査はする)。−inf・NaN は ValueError。
`v_obstacle > 0 は走っている障害物(passing_gap_required`)。
門: D* ± ε で判断が切り替わる / `passing_simulate` の PET が pet_min になる境目と D* が一致。
• 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.
• poc_driving_traffic — py -3.11 examples/poc_driving_traffic.py
any as input)course_crank · course_s_curve · course_turnaround · course_slope · course_intersection · course_parallel_parking · course_crossing · course_road
traffic)idm_accel · idm_equilibrium_gap · idm_platoon_simulate · driver_style · lateral_wobble · ou_estimate · social_force_step · pedestrian_crossing
*Provenance: drivetraffic.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.