ou_estimate — DRIVE `traffic` op

• Data kinds: signal → table

• Call: import fullseye as fs; fs.ledger.ou_estimate(x, dt: 'float') -> 'Dict[str, float]' (to call the implementation directly, import drivetraffic; drivetraffic.ou_estimate(x, dt: 'float') -> 'Dict[str, float]'; from the registry, opsdrive.get("ou_estimate"))

Usage

Reads the parameters of lateral wander (an OU process with mean 0 dX = −θX dt + σ dW) from a sequence of observations at uniform spacing dt.

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

厳密離散化 x_{k+1} = φ x_k + ε_k(φ = e^{−θ dt}、ε ~ N(0, q²)、q² = σ²(1 − φ²)/(2θ))の条件つき最尤:

φ̂ = Σ x_k x_{k+1} / Σ x_k², q̂² = mean((x_{k+1} − φ̂ x_k)²), θ̂ = −ln φ̂ / dt, σ̂ = q̂ sqrt(2θ̂ / (1 − φ̂²))

(Euler の (1 − φ̂)/dt でなく ln を使うので dt が粗くても偏らない)。標準誤差は漸近式: se(φ̂) = sqrt((1 − φ²)/n)、se(q̂) = q/sqrt(2n)、θ̂・σ̂ はデルタ法。sigma_increment = sqrt(mean(Δx²)/dt) は θ を使わない粗い推定(E[Δx²] = σ²(1 − φ)/θ なので θ dt → 0 で σ。相関時間の長い系列を短く見るとき、位置の標本 SD より σ を安定に読める)。

戻り値 dict: theta, sigma, sd(定常 SD σ/√(2θ))、phi, q, n(増分の数)、se_theta, se_sigma, sigma_increment。

Raises ValueError: 1-D でない・3 点未満・非有限、dt ≤ 0、φ̂ ∉ (0, 1)(この dt では平均へ戻る過程に見えない)。

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 · 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).*

ou_estimate — DRIVE traffic op