This document maps LAIRA's inspection capabilities against ASTM D6433-20 (Roads and Parking Lots PCI Surveys), the federal pavement-performance framework (23 CFR Part 490 + HPMS), AASHTO automated-measurement standards, and state-DOT exemplars (Caltrans, TxDOT, FDOT, WSDOT). DoD installation roads, sidewalks and curb ramps, roadway markings, and parking lots are now covered in dedicated companion matrices (see §4 below).
Headline finding. LAIRA ✅ Meets or ✅+ Exceeds D6433's measurement criteria for 12 of the 19 asphalt-concrete distress types (Appendix X1) and 12 of the 19 portland-cement-concrete distress types (Appendix X2) today, with crack-width resolution of ±0.7 mm — 14× finer than D6433's tightest crack-width severity threshold (10 mm for AC longitudinal & transverse cracking, §X1.14.2.2) — and elevation resolution of ±3 mm, which sits below D6433's smallest faulting severity threshold (>⅛ in ≈ 3.2 mm, §X2.7 Table X2.2). The remaining 7 AC + 7 PCC distress types are in active development against committed delivery on the 2026 roadmap.
D6433's PCI methodology (sample-unit sizing, deduct curves, iterative CDV, sample-unit and section PCI) is implemented on the same algorithmic substrate LAIRA already uses for ASTM-pattern condition surveys; the D6433-specific deduct curves (Appendix X3) are vectorized and undergoing unit-test validation against published worked examples.
In short: yes, LAIRA processes and reports against ASTM D6433, with measurement resolution that exceeds the standard's thresholds and a full-coverage scanning model that eliminates the sampling error D6433 §7 explicitly accepts under random sample-unit selection.
19 distress types per D6433 Appendix X1. LAIRA detects all 19 types in pipeline today, with the per-distress status against D6433's severity thresholds shown in the rightmost column. 12 distresses ✅ Meet or ✅+ Exceed D6433's measurement criteria today; the remaining 7 are in active development on committed delivery.
#
D6433 ID
Distress
Severity
Unit
LAIRA Detection
Status
1
X1.5
Alligator (fatigue) cracking
L / M / H
sq ft
Pattern recognition via RGB + LiDAR depth
✅+
2
X1.6
Bleeding
L / M / H
sq ft
LiDAR intensity + RGB color shift
✅
3
X1.7
Block cracking
L / M / H
sq ft
Orthogonal crack pattern recognition
✅+
4
X1.8
Bumps and sags (roadway-specific)
L / M / H (ride)
linear ft
LiDAR surface profile + RGB; primitives shared with depression detector
🔄
5
X1.9
Corrugation
L / M / H (ride)
sq ft
LiDAR transverse-profile undulation
✅
6
X1.10
Depression
L / M / H by depth (½–1 in / 1–2 in / >2 in)
sq ft
LiDAR DEM elevation differential (±3 mm)
✅+
7
X1.11
Edge cracking (roadway-specific)
L / M / H
linear ft
Crack pipeline + pavement-boundary segmentation
🔄
8
X1.12
Joint reflection cracking
L / M / H by crack width and surrounding distress
linear ft
Primary crack detection pipeline
✅+
9
X1.13
Lane/shoulder drop-off (roadway-specific)
L / M / H by elevation diff (≤2 in / 2–4 in / >4 in)
linear ft
LiDAR cross-section profile at lane edge; shares primitives with PCC faulting
🔄
10
X1.14
Longitudinal & transverse cracking
L / M / H by crack width
linear ft
Primary crack detection pipeline
✅+
11
X1.15
Patching and utility-cut patching
L / M / H by patch condition
sq ft
Surface material boundary + elevation differential
✅
12
X1.16
Polished aggregate
No severity
sq ft
LiDAR micro-texture analysis
🔄
13
X1.17
Potholes (roadway-specific)
L / M / H by size + depth
number
LiDAR depression + RGB pattern; thresholded on size matrix
19 distress types per D6433 Appendix X2. 12 distresses ✅ Meet or ✅+ Exceed D6433's measurement criteria today; the remaining 7 are in active development on committed delivery. Faulting measurement (§X2.7) and joint-spalling measurement (§X2.21) ✅+ Exceed D6433 by an order of magnitude (±3 mm LiDAR elevation differential against the smallest tabulated severity threshold of >⅛ in ≈ 3.2 mm).
#
D6433 ID
Distress
Severity
Unit
LAIRA Detection
Status
1
X2.3
Blowup / buckling
L / M / H (ride)
slabs
LiDAR elevation spike at joint + RGB fracture
✅
2
X2.4
Corner break
L / M / H by crack width and faulting
slabs
Crack intersection with slab corner geometry
✅
3
X2.5
Divided slab
L / M / H per Table X2.1
slabs
Multi-intersecting cracks fragmenting slab into ≥4 pieces per §X2.5; LiDAR + RGB
✅
4
X2.6
Durability ("D") cracking
L / M / H by % slab area
slabs
Crack pattern parallel to joints/edges
🔄
5
X2.7
Faulting
L / M / H by elevation diff (>⅛–<⅜ in / >⅜–<¾ in / >¾ in)
slabs
LiDAR elevation differential across joint (±3 mm)
✅+
6
X2.8
Joint seal damage
L / M / H per joint condition
per section
Joint sealant condition via RGB + LiDAR gap measurement
✅
7
X2.9
Lane/shoulder drop-off (roadway-specific)
L / M / H by elevation diff
linear ft
LiDAR cross-section profile at lane edge
🔄
8
X2.10
Linear cracking (plain + reinforced)
L / M / H
slabs
Crack detection pipeline applied to PCC joints
✅+
9
X2.11
Patching, large (>5 sq ft)
L / M / H
slabs
Patch boundary + elevation differential
✅
10
X2.12
Patching, small (<5 sq ft) + utility cut
L / M / H
slabs
Patch boundary + elevation differential
✅
11
X2.13
Polished aggregate (PCC, roadway-specific)
No severity
sq ft
LiDAR micro-texture analysis
🔄
12
X2.14
Popouts
No severity (avg per sq ft)
number
Small surface voids via RGB texture
🔄
13
X2.15
Pumping
No severity (count joints)
number
Staining / debris at joints
✅
14
X2.16
Punchouts (roadway-specific, primarily CRCP)
L / M / H
slabs / number
Localized patch of slab disintegration; RGB + LiDAR
🔶
15
X2.17
Railroad crossing (roadway-specific)
L / M / H (ride)
sq ft
Zone-context detection
🔶
16
X2.18
Scaling, map cracking, crazing
L / M / H
slabs
Surface mortar loss via LiDAR micro-profile + RGB texture
✅
17
X2.19
Shrinkage cracks
No severity
slabs
Fine crack network via high-resolution RGB
🔄
18
X2.20
Spalling, corner
L / M / H
slabs
Material loss at slab corners via LiDAR depth + RGB
✅
19
X2.21
Spalling, joint
L / M / H
slabs
Material loss along joint edge via LiDAR depth + RGB
✅+
Coverage against D6433 §X2: 12 of 19 ✅ Meet or ✅+ Exceed. 5 in active development (🔄). 2 partial pending CRCP punchout and railroad-crossing zone-context detection (🔶).
AASHTO provisional and full standards define how cracking, rutting, and faulting are measured when automated equipment is used. LAIRA's sensor + algorithm stack is designed to map onto these directly.
Standard
Subject
LAIRA Mapping
Status
AASHTO R 85-18
Quantifying cracks in AC surfaces from collected images, automated
Three areas previously covered inline in this matrix have moved to dedicated pages so each buyer audience reads only the relevant standard. Cross-reference here; click through for the full treatment.
UFC adopts D6433 as the PCI methodology; the rest of the page covers DoD-specific workflows (PAVER export, AFCEC integration) the civil reader doesn't need
PROWAG is geometric, not distress-based; the buyer profile (Willits-class plaintiffs' counsel, court monitors, premises insurers) differs from the highway buyer
The state-DOT layer is where the AEC channel actually buys (LA28, LAX, TxDOT mainlanes, FDOT corridors, WSDOT MAP-21 reporting). LAIRA's outputs feed each PMS in the format that DOT consumes.
DOT
Native System
LAIRA Output Path
Status
Caltrans
PaveM (Oracle DB + LRS + optimization engine)
CSV export aligned to Caltrans LRS; APCS-comparable distress + IRI + rutting + faulting
38% of mapped D6433 / roadway requirements ✅ Meet or ✅+ Exceed the cited standards today. 43% are in active development on committed roadmap. 12% deliver partial value (typically screening-grade) pending instrument certification or zone-context detection work.
Honest read of where LAIRA does not yet ✅ Meet a roadway requirement, what it would take to close the gap, and the priority ranking based on which gaps unlock which buyer segments.