lateral_wobble — DRIVE traffic op

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

• Call: import fullseye as fs; fs.ledger.lateral_wobble(n: 'int', dt: 'float', *, theta: 'float', sigma: 'float', seed: 'Optional[int]', x0: 'Optional[float]' = None) -> 'np.ndarray' (to call the implementation directly, import drivetraffic; drivetraffic.lateral_wobble(n: 'int', dt: 'float', *, theta: 'float', sigma: 'float', seed: 'Optional[int]', x0: 'Optional[float]' = None) -> 'np.ndarray'; from the registry, opsdrive.get("lateral_wobble"))

Usage

Exact discretization of the Ornstein–Uhlenbeck process dX = −θ X dt + σ dW (a sequence of length n, step dt).

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

x_{k+1} = x_k e^{−θ dt} + σ sqrt((1 − e^{−2θ dt}) / (2θ)) ξ_k, ξ_k ~ N(0, 1) 独立

遷移分布が厳密なので dt に依らず定常分散 σ²/(2θ)、自己相関 corr(x_k, x_{k+j}) = e^{−θ j dt}(門は長い系列の標本で、許容幅は AR(1) の標本誤差から決める)。x0 = None なら定常分布 N(0, σ²/(2θ)) から引く(最初から定常)。seed は np.random.default_rng(seed)(None も可だが非決定的)。

Raises ValueError: n < 1、dt ≤ 0、θ ≤ 0、σ < 0。

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 signal as input)

flight_vacuum · magnus_lift_coefficient · drag_coefficient_sphere · restitution_from_apexes · restitution_from_intervals · fit_parabola · flight_fit · fit_aero

Same category (traffic)

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


*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.