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.passing_simulate(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, dt: 'float' = 0.01, v_obstacle: 'float' = 0.0) -> 'Dict[str, float]' (to call the implementation directly, import drivetraffic; drivetraffic.passing_simulate(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, dt: 'float' = 0.01, v_obstacle: 'float' = 0.0) -> 'Dict[str, float]'; from the registry, opsdrive.get("passing_simulate"))
Runs the "go" case forward in time and returns the PET (difference between the time the ego vehicle has fully returned from the oncoming lane and the time the oncoming vehicle reaches that point).
> The detailed description below is the original text — the summary and the headings are translated.
閉形式と独立な経路: 自車の 横位置 を、x_in〜x_out の間は対向車線(y = 1)、x_out を過ぎたら y(τ) = 1 − smoothstep(τ / T_lc)(τ = x_out を過ぎてからの時間)で戻すとして刻み dt で進め、y が 0 になった刻みを探して刻み内を二分法で詰めた時刻を戻り切った時刻とする(T_lc = 0 なら x_out を過ぎた時刻)。対向車は x = D から −v_on で進め、戻り切った地点を通る刻みを探して線形補間する。v_on = 0 なら PET = inf。
v_obstacle > 0: 障害物の前端の外(x_out)も v_obstacle で進む(走っている自転車の追い越し)。
戻り値 dict: t_clear、x_clear、t_oncoming(対向車が x_clear に着く時刻)、pet。
• 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
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
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.