Asphalt-edge notches: vegetation, real damage, or detector artifacts?

2026-08-01 · AI3D-337 z-range evidence work · sample of 65 adjudicated notches from a mined population of 2825 (depth ≥ 0.30 m, length ≥ 0.5 m) across A1–A4/5

TL;DR — the sketch had a third answer. At the sampled notch locations, the single most common cause is neither a real notch nor vegetation: in 38% of cases the detected edge polyline is simply not on the physical pavement boundary at all — it dives onto lane markings, scan seams, or intensity boundaries while the asphalt continues unbroken underneath (detector artifact). Among notches with a physical cause at the edge (40 of 65), vegetation is the dominant mode: 16 vegetation overhang + 8 object/boulder + 4 pure dropout vs 12 genuine notches in the pavement. So when the top-down view shows a big inward bite: roughly 38% detector artifact · 25% vegetation over the edge · 18% real irregular pavement · 12% object on the edge · 6% data dropout.

Percentages

38%
25 of 65
Detector artifact
25%
16 of 65
Vegetation overhang
18%
12 of 65
Real notch / irregular edge
12%
8 of 65
Object on edge
6%
4 of 65
Data dropout
Detector artifact Vegetation overhang Real notch / irregular edge Object on edge Data dropout

Note on "detector artifact": the adjudication taxonomy had five classes (vegetation / real notch / object / dropout / unclear). All 25 "unclear" verdicts turned out to be the same phenomenon, stated independently by each judge: continuous flat asphalt across the whole notch with the true edge metres further out — the detector latched onto a lane marking, scan-strip seam, intensity boundary, or gore-area paint. These are shown as their own class above (raw taxonomy counts: unclear 25 · vegetation_overhang 16 · real_notch 12 · object_on_edge 8 · dropout 4).

Per dataset

UnitnDetectorVegetationRealObjectDataUnclear
A1 branch 00020963200
A1 branch 0018312200
A211540020
A311440300
A4/515417120

Per sampling stratum

StratumnDetectorVegetationRealObjectDataUnclear
Deepest-20 (depth-ranked)201500410
Random (≥0.4 m depth)3551211430
A1-central supplement10541000

The deepest notches are overwhelmingly detector artifacts — a >2 m "bite" almost never has a physical cause. Random-stratum notches (0.4–1 m deep) are where real vegetation and edge damage live.

Pavement visible under/behind the notch?

pavement_under_canopyn%
yes4671%
no1218%
no_data711%

Combination verdicts (primary + secondary)

combinationn
vegetation_overhang + real_notch5
vegetation_overhang + dropout3
real_notch + vegetation_overhang3
unclear + dropout3
object_on_edge + dropout3
real_notch + object_on_edge1
object_on_edge + vegetation_overhang1
vegetation_overhang + unclear1
object_on_edge + unclear1

How to read the evidence (worked example)

Candidate a1_b000_s001_L_027.25 — a vegetation + dropout combination, the exact "both at once" mode the experiment was designed to detect:

1. Raster RGB the detector saw — red line = detected edge, notch visible
2. True-RGB point top-down: grey road → green vegetation band → magenta (zero returns)
3. Canopy-stripped (only points ≤15 cm above road): is there pavement under the green?
4. Cross-sections: does the flat surface continue past the red dashed detected edge?
5. RGB perspective zoom: what the scene actually looks like

Reading: grey road, then a thin dark-green vegetation band exactly where the detected edge spikes inward, then magenta (zero returns) behind it. The canopy-stripped view shows no pavement-height returns under the green — LiDAR could not see under this particular canopy — and the cross-sections show the road plane with a curtain of vegetation points above the edge. Verdict: vegetation overhang with occlusion dropout behind it.

CloudCompare click-through (battlebox)

Three of the deepest A4/5 candidates were exported as 15×15 m RGB PLY crops and inspected interactively in CloudCompare by a computer-use agent (top view → oblique → grazing side view → under-canopy close-up).

a4_5_s025_L_037.00

01 top
02 oblique
03 grazing
04 under canopy close

a4_5_s027_L_012.25

01 top
02 oblique
03 grazing
04 under canopy close
05 below edge

a4_5_s135_R_005.75

01 top
02 oblique
03 grazing
04 under canopy close
05 dropout close

Session recording (cropped to the CloudCompare window, 24 min): cloudcompare_session.mp4 (10 MB).

Method & caveats

Data paths