Transportation regulations, machine-readable
Deontica transforms transportation laws into structured, computable rule sets for autonomous vehicle compliance, ML training, and verification & validation.
From legal text to computable rules
A structured pipeline that turns transportation regulations into assets your engineering teams can actually use.
Ingest from authoritative sources
We pull the canonical text directly: eCFR XML for federal regulations, official state portals for TxDOT/CA/AZ/FL, UNECE for international harmonized standards. No re-typed copy, no drift.
Classify & decompose
Every section is tagged behavioral, definitional, administrative, informational, or reference. Behavioral sections become Rules with atomic conditions, actions, parameters, and maneuvers. Definitions become a typed Glossary. Recordkeeping/reporting/certification flow into Compliance Obligations.
Export as code
OpenSCENARIO XML scenarios, Python validators (V&V harness included), and ML constraint/violation functions — generated from the same canonical rule. The runtime is a single import; no glue code to maintain.
Plug into your pipeline
Use the V&V harness to grade trace data and produce CSV reports your CI can fail on. Use the ML functions as differentiable constraints in training. Use the dashboard to track coverage as you expand to new ODDs.
Built for AV engineering teams
Everything you need to integrate regulatory compliance into your development and validation workflows.
Rule Explorer
Tree-view across 1,495 rules grouped by chapter, jurisdiction, category, or modality. Project mode scopes the view to your archetype.
Atomic decomposition
Every rule decomposes into reusable Actions (A-NNN), Conditions (C-NNN), Parameters (P-NNN), and Maneuvers (M-NNN). 439 atoms, 298 parameters, 21 maneuvers.
Typed Glossary
360 entity Atoms (E-NNN) extracted from definitional sections — "commercial motor vehicle", "anchor point", "intermodal equipment provider" — with parameter slots populated.
Compliance Obligations
Recordkeeping, reporting, certification, retention, and inspection requirements — extracted with frequency, retention period, evidence required, and owner role.
V&V vs ML evaluators
Per-rule charts overlay the V&V binary violation curve against the ML continuous magnitude across all 12 violation categories. One canonical rule, two coordinated runtimes.
Multi-format export
OpenSCENARIO XML, Python validator package, ML constraint/violation functions, and a runnable V&V harness. Single zip, single import, no glue code.
Rule relationships
Precedence chains, exception links, and cross-jurisdiction transposition graph (UNECE → EU → national). Visible in the graph view.
Six jurisdictions live
TxDOT, FMCSA (49 CFR 383/392/393/396), FMVSS (49 CFR 571), UNECE (R140/R152/R155/R157), California, Arizona, Florida. eCFR XML adapter for fast new-part ingest.
AI-assisted decomposition
Chapter-level pipeline using Claude Haiku — atom dedup via embeddings, validation gates, and a full audit log per run with token cost tracking.
See the math run in your browser
Drag the speed slider. The same violation_speed primitive that ships in Deontica's downloadable Python bundle runs in your browser via Pyodide. The smooth severity curve is what an AV planner trains against — and the same code doubles as a crisp V&V validator and a regulator-friendly compliance check.
Try it live — R-079 speed limit
The actual ML-mode violation primitive from dt_eval_categories.violation_speed, running in your browser via Pyodide. Slide the predicted speed past the threshold and watch the smooth severity curve respond — this is the gradient signal an AV planner trains against.
dt_eval_categories.violation_speed from the bundled Python runtime — same primitives the downloadable bundle uses.Who is Deontica for?
Purpose-built for the teams making autonomous vehicles safe, legal, and deployable.
Problem: Reading raw statute text, tracking obligations across jurisdictions, and arguing about scope with engineering
Project-scoped Rule Explorer + Glossary + Compliance Obligations dashboard. Every claim links back to the source section, with an immutable change log behind every applicability decision.
Problem: Hand-authoring scenarios per rule and writing compliance graders that drift from the regulation
Export ships an OpenSCENARIO scenario per rule plus a runnable V&V harness (`dt_vv_runner.py`) that grades a directory of trace JSON and emits per-rule + per-trace CSVs ready for CI gating.
Problem: Translating regulatory text into differentiable constraints — and keeping V&V and training in sync as rules change
ML loss functions and the V&V harness emit from one canonical rule definition. The graph view overlays the V&V step curve against the ML continuous magnitude so you can confirm they agree before training.
Problem: Sizing the regulatory delta when expanding into a new state, country, or operational domain
Compare rule sets and obligation tallies across the 6 live jurisdictions. Project mode filters everything — Statutes, Rules, Atoms, Glossary, Obligations — to the regulators relevant to your ODD.
Simple, seat-based pricing
All regulations available on every plan. Pay for the tools your team needs.
Explorer
Browse and understand regulations
- Tree-view across all 1,495 rules
- Glossary + Compliance Obligations
- Read-only on the full library
- All 6 jurisdictions
- Public sandbox (Pyodide-based)
Builder
Export rules as code for your pipeline
- Everything in Explorer
- Project mode + scoped views
- OpenSCENARIO + Python + ML export
- V&V harness with CSV reporting
- Compliance dashboard
- API access (50K calls/mo)
Team
For teams building production AV systems
- Everything in Builder
- Team management & RLS roles
- Immutable audit log on every write
- Unlimited API calls
- Priority support
- Custom rule + obligation curation
Enterprise
For OEMs, AV deployers, regulators
- Everything in Team
- SSO / SAML
- Custom integrations
- Dedicated support & SLA
- On-premise / private cloud
- Custom jurisdiction onboarding
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