Research Mission & National Interest

1. Substantial Intrinsic Merit · The What

The proposed endeavor is the development of operational authority-lifecycle governance architectures for autonomous systems deployed in U.S. national security, defense, and critical-infrastructure environments. The novel contribution is to treat authority itself as a graded, trust-proportional resource governed by a formal lifecycle, assigned, monitored, degraded, revoked, and recovered in real time, rather than a binary on/off control held by either the autonomous system or a safety override. The work addresses a specific and unsolved technical gap: how authority is managed in human-machine teaming systems where operational decisions occur faster than human reaction time. Redundancy-and-voting fails because identical sensors and voters share identical blind spots; runtime assurance offers only a binary handoff to a known-safe controller. This research adds the missing layer, a system that reasons continuously about whether its own inputs and decisions can be trusted, allocates authority in proportion to that trust, and follows a structured recovery path when trust collapses. No standardized authority-lifecycle governance framework currently exists for autonomous systems in defense or critical infrastructure.

The substantial intrinsic merit of the endeavor rests on seven formally specified governance architectures, SATA (sensor trust), HMAA (authority), CARA (recovery), MAIVA (multi-agent trust), FLAME (escalation control), ADARA (deception-aware risk), and ERAM (escalation-risk assessment), built on formal mathematical foundations including Dempster-Shafer trust fusion and four-level authority state machines with hysteresis. Each is demonstrated in deterministic simulation, verified with TLA+ model checking (23,748 states and 8 properties, of which 5 invariants and a liveness property are verified and 2 upgrade-path properties are vacuous at this bound for the reference testbed), and released as open, DOI-registered artifacts. The architectures are demonstrated across ten operational domains on a single governance pipeline, evidence that they encode domain-agnostic safety principles rather than narrow, single-application designs.

The endeavor is instantiated as formally specified, simulation-demonstrated governance architectures with open DOI-registered artifacts, twelve physical research platforms (rover, UAV, BLADE-EDGE defense, BLADE-AV automotive, BLADE-MARITIME maritime, BLADE-INFRA critical infrastructure, BLADE-SPACE orbital, BLADE-CUAS counter-UAS, BLADE-AGENT-HSM agentic-AI hardware root of trust, BLADE-SWARM attritable swarm autonomy, BLADE-INFRA-OT IT/OT bridge governance, BLADE-FINANCE financial-sector governance), a companion software authority-governance layer published on the AUTHREX Systems venture site (AUTHREX-AGENT, AUTHREX-ASSURE, AUTHREX-ICS-GATE, AUTHREX-AGENT-CYBER, AUTHREX-SPACECYBER, and AUTHREX-SANDBOX), and reproducible experimental results. Cross-domain portability, the same governance pipeline operating under DoDD 3000.09 (defense), ISO 26262 ASIL-D (automotive), MIL-STD-810G (maritime), and SIL 3 / NERC CIP (critical infrastructure), demonstrates the architectures are domain-agnostic safety principles, not narrow single-application designs.

The contribution is the integration of three elements that are individually well-established but have not been combined this way. Graded authority, not binary: four authority levels (A0 through A3) that change continuously with computed sensor trust, with downgrades applied in milliseconds and upgrades deliberately delayed to prevent oscillation, rather than a single "in autonomy or not in autonomy" switch. Hardware-anchored trust: sensor trust is computed in an FPGA and cryptographically attested, so an adversary who compromises the software cannot forge the trust score, which is what makes the layer tamper-evident rather than merely another piece of software. A formally verified authority state machine: the authority transitions are model-checked in TLA+ across 23,748 reachable states with no unsafe state reachable, a mathematical proof of the safety invariant rather than a test. The underlying mathematics, Dempster-Shafer trust fusion, Byzantine fault tolerance, and CUSUM anomaly detection, is standard; the novelty is combining hardware-attested heterogeneous sensor reasoning with a formally verified authority state machine and generalizing it across ten operational domains on one pipeline.

Positioning the work against prior art is part of the contribution: this is a synthesis of trust-aware sensor reasoning with formally verified authority governance, not a rejection of existing approaches. It builds on and extends five established research lines. Runtime verification (R2U2, Rozier et al., Iowa State and NASA Ames; arXiv:2110.03506) pioneered FPGA-based runtime verification of temporal-logic specifications; this work shares the FPGA-attested-monitor pattern but adds heterogeneous trust fusion and a graded authority output rather than a binary accept or reject verdict. DARPA HACMS (2012-2016) demonstrated formal-methods hardening of vehicle-control software; this work adopts the same formal-methods-first posture and extends the cyber-defense framing into the runtime-trust layer, defending against active adversary manipulation and not only random sensor failure. DARPA Assured Autonomy advanced runtime monitoring and certification of learning-enabled components; this work extends that line by treating authority itself as the certifiable artifact, degrading it continuously rather than tripping a binary kill switch. Adjustable autonomy and supervisory control (Parasuraman, Sheridan, and Verplanck, 1978-2000) provided the classical theory of graded human-machine authority; this work operationalizes that theory as a runtime function of trust, computed in milliseconds and enforced in hardware. The Simplex architecture and runtime assurance (Sha et al.) switch between a verified safety controller and an unverified performance controller; this work is adjacent but distinct, modulating the authority level of a single autonomy stack continuously and adding heterogeneous sensor reasoning above the monitor layer. This positioning is independent and not affiliated: no government program office, FFRDC, or agency has endorsed, certified, or sponsored the work.

2. National Importance · The Why

The proposed endeavor is a matter of substantial U.S. national importance across five dimensions of the national interest.

1. Economic and financial. Nearly 40,000 Americans die in traffic crashes each year, 94 percent attributed to human error, and NHTSA has documented 1,429 automated-vehicle incidents between 2021 and 2025, a recurring safety and economic burden that verifiably governed autonomy is positioned to reduce. The same authority-lifecycle layer underpins U.S. defense modernization under DoD Directive 3000.09 and JADC2, protects the automated decision systems of the financial sector (BLADE-FINANCE, aligned with the U.S. Treasury Financial Services AI Risk Management Framework and EO 14179), and carries direct federal-market relevance such as the $500M FEMA Counter-UAS Grant Program addressed by BLADE-CUAS. Congress and federal agencies have repeatedly framed leadership in these autonomous-systems markets as a national economic priority.

2. Business model and industry. Authority-lifecycle governance is horizontal infrastructure for the entire autonomous-systems industry, spanning defense, automotive, maritime, critical infrastructure, orbital, counter-UAS, agentic AI, IT/OT, and financial services on one pipeline. New federal action, the SELF DRIVE Act of 2026 (H.R. 7390), Executive Order 14305 and the FY26 NDAA Safer Skies Act, and the CISA, NSA, and Five Eyes agentic-AI guidance, is opening regulated markets that currently lack a standardized governance implementation. The applicant's companion software venture layer on the AUTHREX Systems site (AUTHREX-AGENT, AUTHREX-ASSURE, AUTHREX-ICS-GATE, AUTHREX-AGENT-CYBER, AUTHREX-SPACECYBER, and AUTHREX-SANDBOX), the open CC BY 4.0 licensing of the research artifacts, and cross-domain portability across ten domains are deliberately structured for adoption across industry sectors and standards bodies (NIST, IEEE, SAE) rather than a single product line.

3. Technological advancement. The work advances the state of the art beyond redundancy-and-voting and runtime assurance by making authority a graded, trust-proportional resource under a formal lifecycle. It combines Dempster-Shafer trust fusion, four-level authority state machines with hysteresis, TLA+-verified safety invariants (23,748 states and 8 properties, of which 5 invariants and a liveness property are verified and 2 upgrade-path properties are vacuous at this bound for the reference testbed), and a hardware root of trust for the agentic-AI era, BLADE-AGENT-HSM, which places signing keys in an NXP EdgeLock SE051 (CC EAL6+) secure element, holds the authority tier in an Infineon TPM 2.0 (FIPS 140-2 Level 2), and latches to a safe state under a multi-modal tamper cascade. These are controls that software alone cannot provide, because the software is the attack surface.

4. Consumerism and the end consumer. The direct beneficiary is the American public. Governed drive-by-wire authority (BLADE-AV, demonstrated across 1,200 simulation runs with no observed unsafe authority transitions) can cut actuator authority in hardware within the watchdog timeout window when sensor integrity degrades, protecting drivers, passengers, and pedestrians as automated vehicles reach public roads. Governed critical-infrastructure control (BLADE-INFRA, SIL 3 / NERC CIP) and the fail-closed IT/OT boundary appliance (BLADE-INFRA-OT) protect the reliability of the power, water, and transportation systems that citizens depend on every day.

5. Societal benefit and the public good. Keeping verifiable human authority over autonomous action is a public-good problem. Every authority computation, trust score, deliberation window, and recovery transition in the architecture is a deterministic function of documented inputs anchored by an ECDSA-signed, tamper-evident audit chain, providing cryptographically auditable decision chains for post-incident reconstruction and accountability. Through FLAME (U.S. Provisional Patent 64/005,607), the architecture introduces mandatory deliberation windows that hold safety-critical actions for human judgment and prevent AI-driven escalation faster than commanders can intervene, contributing to the responsible and safe deployment of advanced AI across strategic sectors.

This domain has been identified as a national priority by:

• U.S. Department of Defense (DoD Directive 3000.09, autonomous weapons governance, requiring human control mechanisms over autonomous and semi-autonomous weapon systems)
• DARPA Assured Autonomy Program (developing methods to provide safety guarantees for autonomous systems operating in complex environments)
• NASA SBIR 2026 Subtopics INSITU.1.S26B and EXPAND.3.S26B (NASA's FY2026 Small Business Innovation Research solicitation identifies autonomous systems fault management and distributed spacecraft health management as funded research priorities; AUTHREX modules SATA, HMAA, CARA, MAIVA, and ADARA address the published technical requirements for both subtopics, with AUTHREX simulation framework at TRL 3 matching the subtopic Phase I expectation per NASA's published Q&A. EXPAND.3.S26B alignment is demonstrated by the BLADE-SPACE Governance Node - a 91-component 6U+ SmallSat payload module Preliminary Design Phase data package (TRL 2-3): LEO 400-1200 km, 30 krad TID, 5-year mission life, hot-redundant RTG4 FPGA + Aitech S-A1760 Venus SBC compute with <200 ms failover, ECDSA P-256 anchored audit chain, three-fault-tolerant payload/thruster safety interlock, $505K reference BOM, 15 engineering design documents including SRD with 25 traceable requirements, FMEA with 35 failure modes, V&V Plan with 20-test campaign)
• NIST AI Risk Management Framework (AI RMF 1.0, establishing governance, risk mapping, and measurement practices for trustworthy AI systems)
• National Security Commission on Artificial Intelligence (final report, 2021, recommending the U.S. invest in AI-enabled autonomous systems with appropriate safety and governance mechanisms)
• Joint All-Domain Command and Control (JADC2) (human-machine command authority in contested, multi-domain environments requiring trusted autonomous decision-making)
• Presidential Policy Directive 21 (critical infrastructure protection, identifying the need for resilient autonomous systems in infrastructure sectors)
• NHTSA Automated Vehicle Framework (April 2025, establishing three principles, prioritize safety, unleash innovation, enable commercial deployment, with AV STEP safety case requirements and crash reporting mandates)
• NHTSA Docket NHTSA-2026-0265 (Automated Vehicle Safety Public Meeting, March 2026): Technical public comment submitted to active federal AV safety docket proposing trust-proportional authority governance (AUTHREX framework, TLA+ verification, 23,748 states, 8 properties, of which 5 invariants and a liveness property are verified and 2 upgrade-path properties are vacuous at this bound) for runtime authority management in automated driving systems during sensor degradation events. Posted April 27, 2026 by NHTSA on regulations.gov as Comment ID NHTSA-2026-0265-0014 (tracking number moh-5ilb-i5tb), with the AUTHREX white paper attached as part of the permanent federal public record.
• SELF DRIVE Act of 2026 (H.R. 7390, the first federal statute dedicated to autonomous vehicle safety, requiring cybersecurity plans to detect and respond to "false vehicle control commands," safety cases with evidence-based safety arguments, and a National Automated Vehicle Safety Data Repository)
• U.S. traffic safety crisis (nearly 40,000 Americans die in traffic crashes annually, with 94 percent attributed to human error; NHTSA reported 1,429 autonomous vehicle incidents from 2021-2025 under Standing General Order 2021-01, highlighting the need for formal governance architectures in deployed AV systems)

This research addresses documented regulatory gaps, active Congressional legislation, and quantified safety crises affecting U.S. autonomous systems deployment across defense and civilian transportation sectors.

Autonomous Vehicle Safety Crisis

Nearly 40,000 Americans die annually in traffic crashes, with 94 percent attributed to human error. Autonomous vehicles promise to reduce this toll, but NHTSA's Standing General Order 2021-01 has documented 1,429 AV-involved incidents between 2021 and 2025, and the agency opened over 30 investigations in FY2025 alone, including probes into Level 3 and Level 5 ADS systems. Current AV architectures lack standardized, hardware-enforced governance that continuously adjusts drive-by-wire authority based on computed sensor trust. This research provides the missing architectural layer: BLADE-AV demonstrates that a hardware fail-safe relay, governed by formal Dempster-Shafer trust fusion, can cut actuator authority in hardware within the watchdog timeout window, without firmware involvement, when sensor integrity degrades below safety thresholds.

Alignment with Active Federal Legislation

• SELF DRIVE Act of 2026 (H.R. 7390): Congress requires manufacturers to develop safety cases, structured, evidence-based arguments that a system is acceptably safe. BLADE-AV's Zenodo deposit provides exactly this: a 12-page research paper with formal Dempster-Shafer equations, 1,200 simulation runs with no observed unsafe authority transitions, 62-component BOM, and open engineering artifacts. H.R. 7390 also mandates cybersecurity plans to detect and respond to "false vehicle control commands", the ADARA and SATA modules directly implement this capability through cross-sensor consistency detection and adversarial ML identification.
• NHTSA AV Framework (April 2025): Secretary Duffy's three principles, prioritize safety, unleash innovation, enable commercial deployment. The AV STEP program requires safety cases covering nine competencies including Safety Risk Assessment, Vehicle Fallback and Assistance, and Cybersecurity. The BLADE-AV architecture addresses all three: SATA provides risk assessment through continuous trust scoring, CARA provides deterministic fallback through GREP recovery phases, and the TPM 2.0 + ATECC608B hardware stack provides cryptographic cybersecurity.
• UN Global Technical Regulation on ADS (approved January 2026): The first international standard for autonomous driving, emphasizing the "safety case" approach. BLADE-AV's published safety architecture and open simulation artifacts align with this evidence-based validation framework.
• 25 U.S. states introduced 67 AV-related bills in early 2025 alone, creating a patchwork of regulations. H.R. 7390 aims to establish federal preemption for ADS standards. Standardized governance architectures like BLADE-AV can provide the technical foundation for unified national safety requirements.

AI Accountability & Auditability

When an autonomous vehicle crashes, investigators must determine whether the AI system performed as expected. Current AV architectures provide sensor logs but lack a structured authority decision chain showing why the system acted as it did. This research provides cryptographically auditable authority governance: every HMAA authority computation, every SATA trust score, every FLAME deliberation window, and every CARA recovery transition is a deterministic function of documented inputs, enabling post-incident reconstruction of the exact governance state at any point in time. The ATECC608B hardware authentication and TPM 2.0 secure boot provide tamper-evident provenance for the entire decision chain.

Cross-Domain Safety Portability

The same governance pipeline that prevents a directed-energy weapon from firing without proper authority (BLADE-EDGE, DoDD 3000.09) prevents an autonomous vehicle from executing drive-by-wire commands without verified sensor trust (BLADE-AV, ISO 26262 ASIL-D) and prevents a maritime autonomous surface vehicle from engaging effectors without fused hydroacoustic and MAD trust (BLADE-MARITIME, MIL-STD-810G), and prevents a critical infrastructure controller from authorizing actuator commands without verified sensor trust across ICS/SCADA networks (BLADE-INFRA, SIL 3 / NERC CIP), and prevents an autonomous orbital platform from executing propulsive maneuvers or payload firing without verified rad-tolerant sensor trust beyond ground-loop latency (BLADE-SPACE, NASA EXPAND.3.S26B aligned, TRL 2-3 Preliminary Design). This cross-domain portability, defense, civilian transportation, maritime surveillance, critical infrastructure, and orbital on the same architectural foundation, demonstrates that authority-governed autonomy is a domain-agnostic safety principle. This cross-domain governance portability is not commonly found in publicly documented autonomous systems architectures.

Flash War Prevention & Decision Integrity

In contested military environments, AI-enabled systems compress decision timelines below human reaction time, creating escalation risks that no existing governance framework addresses. FLAME (U.S. Provisional Patent 64/005,607) introduces mandatory deliberation windows into autonomous command chains, forcing a configurable hold period before safety-critical actions, even when the system has computed sufficient authority. This architectural safeguard prevents the scenario where two AI systems autonomously escalate to engagement faster than human commanders can intervene. Published on Zenodo with interactive simulation demonstrating the 5-state Circuit Breaker State Machine.

U.S. Competitiveness in Autonomous Systems

Congress has explicitly identified AV regulatory leadership as a competitive priority. NHTSA's July 2025 Report to Congress states that "the Committee continues to believe it is critical that the NHTSA modernize its rules in a timely manner to ensure that the U.S. can safely deploy this new technology and not cede leadership to global competitors." This research, conducted within U.S. institutions, published through open platforms, and aligned with U.S. regulatory frameworks, contributes governance architecture specifications that strengthen U.S. technical leadership at the moment when the first federal AV safety standards are being established.

3. Advancing the Proposed Endeavor · The How

The applicant has built, over a sustained period of independent research, a complete ecosystem of governance architectures spanning formal mathematical foundations (Dempster-Shafer trust fusion, four-level authority state machines with hysteresis), patent-filed intellectual property (four U.S. provisional applications), open reproducible artifacts (twenty-four Zenodo DOIs, sixteen SSRN papers), hardware platform designs across ten operational domains (defense, automotive, maritime, critical infrastructure, orbital, counter-UAS, agentic AI, swarm, IT/OT, and financial), and nineteen interactive simulations producing 2,800+ structured simulation runs with no observed unsafe authority transitions. This body of work demonstrates not a single publication or proof-of-concept, but a multi-year research program with the technical depth, publication record, and implementation evidence to continue advancing authority-governed autonomy as a field within the United States. The cross-domain portability across ten domains, defense (BLADE-EDGE, DoDD 3000.09), civilian transportation (BLADE-AV, ISO 26262 ASIL-D), maritime surveillance (BLADE-MARITIME, MIL-STD-810G), critical infrastructure (BLADE-INFRA, SIL 3 / NERC CIP), orbital (BLADE-SPACE, NASA EXPAND.3.S26B aligned, TRL 2-3 Preliminary Design), counter-UAS (BLADE-CUAS, EO 14305 and the FY26 NDAA Safer Skies Act), agentic AI (BLADE-AGENT-HSM, the hardware root of trust for autonomous AI agents aligned with the CISA/NSA/Five Eyes agentic-AI guidance and FY26 NDAA Sections 1513 and 6601), and swarm autonomy (BLADE-SWARM, attritable autonomous swarms with Byzantine-fault-tolerant authority governance aligned with DoDD 3000.09, the FY26 NDAA, and the NIST AI RMF), and the IT/OT boundary (BLADE-INFRA-OT, fail-closed cross-boundary OT command adjudication aligned with NIST SP 800-82, ISA/IEC 62443, and NERC CIP), achieved on the same governance pipeline, is evidence that the applicant's architectures address fundamental safety principles, not narrow application-specific designs.

Evidence of positioning to advance this endeavor:

• Independent external citations (5): SSRN paper AI-Enabled Military Decision-Making and Escalation Risk: Human-Machine Command Authority in Great Power Competition (SSRN ID 6082847, January 2026) cited in Hernandez, J. (2026), The Cascade Protocol (Pomona College, Department of Economics), ISBN 979-8195946579, DOI 10.5281/zenodo.20113664, Reference #36 of 36, alongside the U.S. Department of War AI Strategy (January 2026), King's College London, US Army War College, Harvard Law School PILAC, Lieber Institute West Point, Carnegie Endowment for International Peace, Atlantic Council, and NDU Press. Separately, SSRN paper ERAM: Escalation Risk in AI-Enabled Command and Control (SSRN ID 6176802) cited as Reference #4 in "The Ethics of AI in U.S. Warfare," LexAI Journal, University of Toronto Law and Ethics of Artificial Intelligence Students' Association (April 2026). Separately, SSRN paper The strategic convergence: AI has outpaced human clearance models (SSRN ID 5940814) is cited as reference [41] in Baruwal Chhetri et al. (2026), From Frontier to Shadow AI: A Simmering Threat to Assurance and Security in Critical Infrastructure (arXiv:2606.00088). Separately, SSRN paper AI-Enabled Military Decision-Making and Escalation Risk (SSRN ID 6082847) is cited in endnote 39 of Lt Gen (Dr) R S Panwar (2026), Cognition, Agency, and Authority: A Taxonomy of Advanced AI Systems with Military Implications (Academia.edu preprint). Separately, SSRN paper Strategic Subterranean Domain Awareness: A Comprehensive Technical and Operational Evaluation of Next-Generation AI-Fused Counter-Tunnel Architectures (SSRN ID 6046594) is cited as reference [1] in Junaid, Khan & Ahmed (2026), Unsupervised Detection of Underground Tunnels in Ground-Penetrating Radar Using Depth-Restricted Reconstruction Scoring (arXiv:2607.04882, Sir Syed CASE Institute of Technology and University of Strathclyde, July 2026), cited twice in the body. Third-party independent adoption of the applicant's published research within months of release.
• 7 U.S. provisional patent submissions (2026) for original governance architectures (HMAA, CARA, SATA, FLAME)
• 24 DOI-registered research artifacts on Zenodo with Georgetown University affiliation, including 4 full research papers with simulation data and hardware specifications
• 16 published papers on AI governance, autonomous systems, and national security (SSRN)
• 19 interactive technical simulations implementing the governance architectures with real-time computation
• 12 physical research platforms: Authority-Governed Rover Testbed (37 components, ~$484, 350 simulation runs, TLA+ verified), Authority-Governed UAV Platform (52 components, ~$4,200, 250 simulation runs, MAVLink/HIL integration), BLADE-EDGE Governance Node (72 components, ~$139K, defense-grade, MIL-STD-810G), BLADE-AV Governance Node (62 components, ~$16K, ISO 26262 ASIL-D, 1,200 simulation runs), BLADE-MARITIME Governance Node (84 components, ~$43K, IP68/MIL-STD-810G, maritime surveillance with hydroacoustic and MAD), BLADE-INFRA Governance Node (92 components, ~$12K, SIL 3/NERC CIP, ICS/SCADA critical infrastructure protection), BLADE-SPACE Governance Node (91 components, ~$505K, TRL 2-3 Preliminary Design, 6U+ SmallSat, RTG4 FPGA + Aitech SBC hot redundancy, NASA EXPAND.3.S26B aligned)
• BLADE-CUAS Governance Node (counter-UAS authority governance, ~$43.5K reference BOM, TRL 2-3 hardware / 3-4 simulation, sixth BLADE platform): four-tier HMAA (T3/T2/T1/T0) with federal-SLTT handoff, Dempster-Shafer multi-modal consensus across radar, RF, EO/IR, Remote ID, and LIDAR, and an ECDSA P-256 court-admissible evidence chain aligned with the foundation requirements of Fed. R. Evid. 901/902/803(6). Reference implementation positioned for the multi-agency C-UAS authority structure established by Executive Order 14305 and the FY26 NDAA Title LXXXVI Safer Skies Act, with FEMA Counter-UAS Grant Program ($500M) deployment relevance.
• BLADE-AGENT-HSM Hardware Root of Trust (agentic-AI hardware root of trust, ~$199 reference BOM, TRL 2-3 silicon / 3-4 emulator, seventh BLADE platform and the first hardware root of trust in the family): a tamper-evident hardware companion to the AUTHREX-AGENT software shim that signs the agent audit ledger with non-exportable ECDSA P-256/P-384 keys in an NXP EdgeLock SE051 (CC EAL6+) secure element, holds the four-tier HMAA authority state in an Infineon SLB 9670 TPM 2.0 (FIPS 140-2 Level 2) PCR bank, derives per-tool HKDF authorization tokens, and runs a multi-modal tamper cascade (active PCB mesh, voltage-glitch, thermal) that zeroizes keys and latches the device to T0. Five-opcode 64-byte ABI; USB-A stick and M.2 Key-E module from one 4-layer PCB. Verified by an adversarial high-assurance emulator across 275 deterministic checks with a P-384 signed golden-trace anchor. Positioned as a direct response to the CISA, NSA AI Security Center, and Five Eyes joint guidance Careful Adoption of Agentic AI Services (1 May 2026) and FY26 NDAA Sections 1513 and 6601.
• BLADE-SWARM Governance Node (attritable swarm authority governance, ~$1,333 per node reference BOM, TRL 3-4 simulator and formal specification / TRL 2 physical testbed design, eighth BLADE platform): authority governance for decentralized autonomous swarms at N=10 (physical testbed), N=50 (combined operation), and N=500 (DAWG-class). Each agent runs a Byzantine-fault-tolerant two-phase consensus gated by SATA peer trust, the four-tier HMAA authority state, and weighted MAIVA voting before the swarm commits, tolerating up to f = (N-1)/3 compromised agents per quorum with a quorum-intersection safety bound, Sybil resistance, and safe-halt-by-default under denied or degraded RF. Per-node ECDSA P-256 root of trust (ATECC608B) feeds a hash-chained distributed audit ledger; TLA+ formal specification with five safety invariants and three liveness properties. It governs decision authority and audit; it does not govern weapons. Aligned with DoDD 3000.09, the FY26 NDAA, and the NIST AI Risk Management Framework.
• BLADE-INFRA-OT Governance Node (authority-governed IT/OT bridge, ~1U fanless reference design, TRL 2-3 hardware / 3-4 simulation, ninth BLADE platform and the operational-technology companion to BLADE-INFRA): a fail-closed, bump-in-the-wire governance appliance at the segmentation boundary between corporate IT networks and operational-technology control assets, adjudicating each cross-boundary command to propagate, hold for deliberation, or isolate across four OT authority regimes through the AUTHREX pipeline, with a seed-deterministic SHA-256 tamper-evident audit ledger, aligned with NIST SP 800-82, ISA/IEC 62443, and NERC CIP.
• BLADE-FINANCE Governance Node (authority governance for financial-sector AI decision systems, ~$9,228 reference design, TRL 3-4 simulation / TRL 2 hardware, tenth BLADE platform and the first in the economic-security domain): a software-enforced authority-arbitration node that places a hardware-anchored checkpoint between automated transaction-decision models and consequential financial actions, routing each transaction through an eight-stage AUTHREX pipeline to autonomous clearance, supervised review, elevated confirmation, or manual hold across a four-tier authority model, with population-state coordination, a retrospective stigmergic swarm-review module, and a SHA-256 canonical-form evidence chain, aligned with the U.S. Treasury Financial Services AI Risk Management Framework, the NIST AI RMF, and EO 14179; synthetic data only, not deployed in any financial institution.
• 7 governance architectures forming a unified research framework: SATA (trust), HMAA (authority), CARA (recovery), MAIVA (multi-agent), FLAME (escalation), ADARA (deception), ERAM (risk assessment)

The maturity of each component is stated openly. The governance architectures are at TRL 3 to 4 and the hardware platforms at TRL 2 to 4, self-assessed by the author against published, public-domain definitions (DoD 5000.02 Appendix B, Technology Readiness Assessment Guidance, and the NASA TRL definitions); these levels have not been externally validated by an FFRDC, government program office, or independent technical-evaluation team. HMAA and SATA are the most mature at TRL 4, lab-demonstrated with a 42-file Python package, 98 automated tests, and a TLA+ specification (HMAA) and Dempster-Shafer cross-sensor attestation (SATA); the remaining architectures are at TRL 3 proof-of-concept. The program targets TRL 6, system demonstration in a relevant environment, by Q2 2027. Every result is externally checkable: each cited DOI resolves to a public Zenodo record, all sixteen SSRN papers are open-access, and the published code, configuration files, and test artifacts are sufficient for an outside evaluator to reproduce the simulation results independently. Validation is organized around canonical adversarial scenarios, GPS spoofing, adversarial camera patches, AIS spoofing, CAN-bus injection, and SCADA replay, with the honest limitation that the current evidence is simulation-based and browser-based simulations do not provide real-time scheduling guarantees.

4. Positioning · The Who

The applicant is uniquely positioned to carry the endeavor forward. The work draws on a rare combination of formal computer-science engineering training, graduate business proficiency measured at the 99th percentile, a substantial independent publication record, hands-on hardware implementation across ten domains, and faculty-level academic collaboration, all sustained over a multi-year independent research program conducted within U.S. institutions. This combination of technical depth, cross-domain breadth, and demonstrated capacity to build and publish, rather than any single credential, is what positions the applicant, and few others, to advance authority-governed autonomy as a field in the United States.

• Cited by name in the U.S. Federal Register: the applicant's public comment (Docket NHTSA-2026-0529-0007) is referenced by name in the U.S. Federal Register (NHTSA, Incident Reporting for Automated Driving Systems (ADS) and Level 2 ADAS, 91 FR 30789, May 26, 2026), among the public comments cited in the notice alongside submissions from Virginia DOT, the Alliance for Automotive Innovation, and Consumer Reports, independent recognition of the specific research by a U.S. federal agency.
• Faculty co-authored research: "Authority-Governed Drive-by-Wire Safety Architecture for Autonomous Vehicles: A Cross-Domain Governance Framework with Industry Validation", co-authored with Dr. Victor Lian (Lynn University), published on SSRN (Abstract ID 6657819), with both authors verifiable on the public SSRN record, demonstrating collaborative research with academic faculty in the autonomous-vehicle safety domain
• Standardized academic assessment: Peregrine Global Services MBA Outbound Examination, 94.62% / 99th percentile against the U.S. comparison data pool (sample sizes 23,490-59,790 MBA graduates per topic, four-year rolling cohort), administered May 10, 2026; 99th percentile in 14 of 16 topic areas including Business Finance, Strategic Management, Quantitative Research and Statistics, Legal Environment of Business, and Global Dimensions of Business, demonstrating cross-domain business proficiency relevant to managing the proposed research endeavor at scale
• Elected Georgetown University leadership role: Elected Outreach & Partnerships Officer, Georgetown University Cybersecurity Society (GUCS), 2026-2027 academic year, confirmed May 11, 2026 by Georgetown School of Continuing Studies. Peer-elected role at the Georgetown SCS student cybersecurity organization, providing institutional engagement at Georgetown ahead of M.P.S. Applied Intelligence matriculation and aligning the applicant's external research program (AUTHREX governance for autonomous systems) with the Georgetown cybersecurity community.
• Published books: Ten-volume technical reference series across three book series, The Authority Equation (3 volumes), The Authority Discipline (4 volumes), and Autonomous Authority (3 volumes), released under the Authority & Architecture publisher imprint, distributed via Amazon and IngramSpark in print and ebook formats. All volumes assigned ISBNs registered through Bowker, and the series carries Library of Congress Control Number 2026912260. The Authority Equation trilogy demonstrated across 8,415 simulation runs spanning 101 scenario configurations. Full catalog at authority-architecture.me
• M.P.S. Applied Intelligence, Georgetown University (STEM-designated, in progress)
• B.Sc. Computer Science Engineering (USF) and MBA (Lynn University, 4.0 GPA)
• Hayes Memorial Scholarship awarded by The Institute of World Politics Admissions Committee (April 27, 2026), a competitive merit-based award per the official offer letter "awarded to the best applicants in the incoming class," for the M.A. Strategic Intelligence Studies program at IWP, a Washington, D.C. graduate school of national security, intelligence, and international affairs
• Authorized to work in the United States, with employment in ITAR/EAR-regulated U.S. cloud infrastructure
• 140+ professional credentials from 25+ institutions (IEEE #102193505, AIAA #1936005, ACM #9952787, AAAI #656504, INFORMS #2009712, NDIA #1700222, Sigma Beta Delta Lifetime #2007930, plus NIST, CompTIA, and CISSP credentials)
• Active industry engagement across defense, manufacturing, and technology sectors: SHOT Show (2024, 2026), EMO Hannover 2023 (Germany), SupplySide West 2025, Israel Tech Week 2025, Miami AI Hub community, NBAA Regional Forums (2024, 2025, 2026), Defense Technology Alliance Roundtable at Israel Tech Week Miami 2026 (registration confirmed), and three abstract submissions to defense-relevant technical conferences: NDIA 2026 Emerging Technologies for Defense Conference & Exhibition (Washington, D.C., September 9-10, 2026, registration confirmed; abstract submitted under "Game-Changing Emerging Technologies" track, Submission ID 2421887), AIAA SciTech Forum 2027 (Orlando, FL, January 11-15, 2027; technical paper submitted under "Uncrewed and Autonomous Systems: Certification Concepts" track, Control ID 4555075, notification expected August 24, 2026), and SpaceCom 2027 (speaker submission for "Trust-Proportional Authority: Solving the Governance Gap for Autonomous Space Systems")

Benefit to the United States · Why a Waiver Serves the National Interest

Governance architectures for autonomous systems are increasingly important for U.S. national security, critical infrastructure resilience, and responsible deployment of advanced AI systems. Developing technical frameworks that maintain human oversight while enabling advanced automation contributes to safe adoption of autonomous technologies across strategic sectors.

The United States benefits from this work because:

• Fills a critical gap identified by Congress and NHTSA: The SELF DRIVE Act of 2026 (H.R. 7390) requires manufacturers to maintain cybersecurity plans addressing "false vehicle control commands", but no standardized, hardware-enforced governance architecture exists to implement this requirement. BLADE-AV provides an open, simulation-demonstrated reference architecture with formal Dempster-Shafer trust fusion, hardware fail-safe relay gating, and 1,200 simulation runs with no observed unsafe authority transitions that directly addresses the safety case, cybersecurity, and fallback behavior requirements outlined in H.R. 7390 and NHTSA's AV STEP framework.
• Supports U.S. defense modernization, automotive safety, maritime security, critical infrastructure resilience, and orbital autonomy: Architectures address DoD Directive 3000.09 (defense), JADC2 command authority, NIST AI Risk Management Framework, ISO 26262 ASIL-D functional safety (BLADE-AV), NHTSA ADS requirements, MIL-STD-810G / MIL-STD-461G maritime defense standards (BLADE-MARITIME), SIL 3 / NERC CIP / FIPS 140-2 critical infrastructure standards (BLADE-INFRA), and NASA SBIR EXPAND.3.S26B autonomous spacecraft health management alignment (BLADE-SPACE, TRL 2-3). Cross-domain portability across ten domains (defense ↔ automotive ↔ maritime ↔ critical infrastructure ↔ orbital ↔ counter-UAS ↔ agentic AI ↔ financial) on the same governance pipeline demonstrates the architectures are domain-agnostic safety principles.
• Enables resilient autonomous operations: SATA, HMAA, and CARA provide structured trust evaluation, authority control, and recovery enforcement applicable to contested-environment platforms including autonomous vehicles, UAVs, maritime autonomous surface vehicles, and robotic systems.
• Prevents autonomous escalation risk: FLAME introduces mandatory deliberation windows in autonomous command chains, directly relevant to preventing AI-driven conflict escalation in multi-domain military operations.
• Protects against adversarial AI manipulation: ADARA detects deceptive inputs in command-and-control systems, mitigating the risk of adversarial sensor spoofing and AI manipulation in safety-critical environments.
• Demonstrated through physical systems across ten domains: Twelve research platforms spanning defense (BLADE-EDGE, ~$139K, MIL-STD-810G), civilian transportation (BLADE-AV, ~$16K, ISO 26262 ASIL-D), maritime surveillance (BLADE-MARITIME, ~$43K, IP68, MIL-STD-810G, hydroacoustic + MAD), critical infrastructure (BLADE-INFRA, ~$12K, SIL 3, NERC CIP, ICS/SCADA), orbital (BLADE-SPACE, ~$505K, TRL 2-3 Preliminary Design, NASA EXPAND.3.S26B aligned), counter-UAS (BLADE-CUAS, ~$43.5K, EO 14305 / FY26 NDAA Safer Skies Act), and agentic AI (BLADE-AGENT-HSM, ~$199, a tamper-evident hardware root of trust for autonomous AI agents and the hardware companion to the AUTHREX-AGENT software shim, aligned with the CISA/NSA/Five Eyes agentic-AI guidance and FY26 NDAA Sections 1513 and 6601), and swarm autonomy (BLADE-SWARM, ~$1,333/node, attritable autonomous swarms with Byzantine-fault-tolerant authority governance, TRL 3-4), the IT/OT boundary (BLADE-INFRA-OT, ~1U fanless, fail-closed cross-boundary OT command adjudication, TRL 2-3 hardware / 3-4 simulation), the financial sector (BLADE-FINANCE, ~$9K BOM, authority governance for financial-sector AI decisions under the U.S. Treasury FS AI RMF, TRL 3-4 simulation / 2 hardware), plus rover and UAV testbeds, with nineteen interactive simulations producing 2,800+ structured simulation runs and no observed unsafe authority transitions. Ten domain instantiations on the same governance pipeline, defense weapons governance, civilian drive-by-wire authority, maritime autonomous surface vehicle governance, critical infrastructure protection, and orbital governance, demonstrate cross-domain portability across ten distinct operational domains on a single architectural foundation.
• Anchors autonomy authority in hardware for the agentic-AI era: In 2026 the United States and its closest partners moved from encouraging agentic AI to governing it. The CISA, NSA AI Security Center, and Five Eyes joint guidance Careful Adoption of Agentic AI Services (1 May 2026) and FY26 NDAA Sections 1513 and 6601 call for hardware-anchored identity, non-repudiable audit, and least-privilege authority for autonomous AI agents, controls that software alone cannot satisfy because the software is the attack surface. This research contributes a two-piece answer: the AUTHREX-AGENT software shim runs the authority lifecycle, and the BLADE-AGENT-HSM hardware root of trust makes that lifecycle non-forgeable by moving the signing keys, the authority tier, and the audit ledger into tamper-evident silicon. A hardware root of trust for the authority of autonomous AI is a matter of substantial national interest, and this contribution is offered as an open, reproducible reference design at research-demonstrator maturity (TRL 2-3 silicon / 3-4 emulator) with no claim of any government endorsement, certification, or affiliation.
• Addresses the U.S.-China autonomous vehicle competition: Transportation Secretary Duffy has stated "America must lead the way in transportation innovation. If we don't, our adversaries will fill the void." This research, conducted within the United States, published through open platforms, and aligned with U.S. regulatory frameworks, contributes governance architecture specifications that strengthen U.S. technical leadership in autonomous systems safety, from autonomous vehicles (BLADE-AV) to maritime surveillance (BLADE-MARITIME) to defense weapons governance (BLADE-EDGE), at a critical moment when Congress and federal agencies are establishing new safety and governance standards.
• Grounded in U.S. institutions: Research is conducted within Georgetown University (STEM-designated program), published through U.S.-accessible platforms (Zenodo, SSRN), and aligned with U.S. regulatory frameworks (NIST, DoD, IEEE, NHTSA, ISO 26262, MIL-STD-810G, MIL-STD-461G).
• Independent contribution: Independent research enables continued advancement of this nationally important domain across multiple sectors without dependency on a single employer's narrower scope.

Broader National Benefit: This research addresses urgent public benefit and public safety needs that no single employer could reasonably sponsor. The work spans defense (DoDD 3000.09 autonomous weapons), automotive safety (NHTSA data on 1,429 AV incidents 2021-2025), maritime security, and critical infrastructure protection simultaneously. As independent research crossing multiple sectors, the work is intrinsically cross-employer in scope. Independent, cross-domain research enables the continued development of safety-critical governance infrastructure that benefits the American public across all ten domains.

The following sections provide supporting detail behind the four prongs above: the individual research programs, the multi-year research roadmap, and potential U.S. deployment scenarios.

Research Programs

The proposed endeavor consists of eight structured research programs, each with associated patent filings, technical reports, and published research:

• Authority Lifecycle Governance (HMAA): A system for managing the delegation, monitoring, and revocation of operational authority within autonomous decision systems. Research platform: 42-file Python package with 98 tests, 7 adversarial experiments (camera occlusion, LiDAR spoofing, RF jamming, IMU drift, compound attack, cross-sensor validation, recovery dynamics), TLA+ formal verification (23,748 states, 8 properties, of which 5 invariants and a liveness property are verified and 2 upgrade-path properties are vacuous at this bound), Dempster-Shafer trust fusion, deterministic simulation. Applications: defense systems, automated infrastructure management, high-reliability AI operations. Patent: U.S. Provisional 63/999,105.
• Fail-Safe Control Recovery (CARA): Deterministic recovery protocol for authority lockout events with a terminal non-compensatory policy gate. Applications: autonomous weapons safety, nuclear-adjacent platform governance. Patent: U.S. Provisional 64/000,170.
• Decision Integrity Monitoring (SATA): Hardware-anchored sensor trust computation providing continuous attestation verification for autonomous mission authority. Applications: sensor fusion governance, unmanned systems trust. Patent: U.S. Provisional 64/002,453.
• Escalation Risk Assessment Model (ERAM): Quantitative framework for decision-time compression and escalation pathway modeling in AI-enabled command-and-control environments. Published on SSRN.
• Flash War Latency Control (FLAME): Deterministic latency injection middleware for preventing autonomous escalation in multi-domain command architectures. Implements Strategic Latency as a formal engineered system with a 5-state Circuit Breaker State Machine, Dynamic Delay Function D(A, tier, domain), and Keep-Alive heartbeat protocol. Patent: U.S. Provisional 64/005,607. Published on Zenodo: DOI 10.5281/zenodo.19015618. Interactive simulation live.
• Multi-Agent Trust Verification (MAIVA): Byzantine-resilient swarm trust aggregation architecture extending HMAA to multi-agent environments. Implements trimmed weighted median aggregation resistant to f adversaries in 3f+1 rosters, three-layer CUSUM-augmented anomaly detection, graduated escalation with per-level action permissions, and DoDD 3000.09 action gate classification. 37 self-tests, TLA+ formal specification. Published on Zenodo: DOI 10.5281/zenodo.19015517. Interactive simulation live.
• Adversarial Deception-Aware Risk (ADARA): Proactive deception prior architecture that adjusts operational authority downward pre-emptively based on the probability that current inputs are adversarially manipulated. Implements a Deception Probability Engine computing P(adversarial) from input distribution anomalies, temporal correlation patterns, cross-sensor consistency scores, and Bayesian update over mission history. Deception-Adjusted Authority Formula: A_adj = A_hmaa × (1 - λ × P_deception). Includes Phantom Fleet detection module. Published on Zenodo: DOI 10.5281/zenodo.19043924. Interactive simulation live.
• Cross-Domain Authority Governance (BLADE Platform Family): Hardware platform implementations demonstrating that the governance pipeline is domain-agnostic. BLADE-EDGE (defense, ~$139K, 72 components, MIL-STD-810G), BLADE-AV (automotive, ~$16K, 62 components, ISO 26262 ASIL-D), BLADE-MARITIME (maritime, ~$43K, 84 components, IP68/MIL-STD-810G, hydroacoustic + MAD), BLADE-INFRA (critical infrastructure, ~$12K, 92 components, SIL 3/NERC CIP, ICS/SCADA), BLADE-SPACE (orbital, ~$505K, 91 components, 6U+ SmallSat, 30 krad TID, RTG4 FPGA + Aitech SBC hot redundancy, NASA EXPAND.3.S26B aligned, TRL 2-3 Preliminary Design Phase), and BLADE-CUAS (counter-UAS, ~$43.5K, four-tier HMAA federal-SLTT handoff, EO 14305 / FY26 NDAA Safer Skies Act, TRL 2-3) share the same SATA-ADARA-HMAA-MAIVA-FLAME-CARA governance pipeline with hardware-enforced safety interlock gating; BLADE-AGENT-HSM (agentic AI, ~$199, TRL 2-3 silicon / 3-4 emulator) extracts the trust anchor into a standalone tamper-evident hardware root of trust for autonomous AI agents, the hardware companion to the AUTHREX-AGENT software shim, with non-exportable ECDSA keys in a CC EAL6+ secure element, TPM 2.0 authority-tier state, and a tamper-evident audit ledger. BLADE-SWARM (swarm autonomy, ~$1,333/node, TRL 3-4 simulator / spec, TRL 2 testbed) extends the same pipeline to decentralized multi-agent swarms with Byzantine-fault-tolerant sub-quorum consensus and a hash-chained distributed audit ledger, governing decision authority and audit across N=10/50/500 attritable autonomous agents. BLADE-INFRA-OT (IT/OT boundary, ~1U fanless, TRL 2-3 hardware / 3-4 simulation) extends the same pipeline to the IT/OT segmentation boundary, adjudicating each cross-boundary OT command to propagate, hold, or isolate across four OT authority regimes and failing closed on malformed input. Combined 2,800+ simulation runs across 47+ attack/fault scenarios on the four published platforms (BLADE-SPACE V&V campaign specified, not yet executed) with no observed unsafe authority transitions. Published on Zenodo: BLADE-EDGE DOI 10.5281/zenodo.19177472, BLADE-AV DOI 10.5281/zenodo.19232130, BLADE-MARITIME DOI 10.5281/zenodo.19246785, BLADE-INFRA DOI 10.5281/zenodo.19277887, BLADE-SPACE DOI 10.5281/zenodo.20183269, BLADE-CUAS DOI 10.5281/zenodo.20299604, BLADE-AGENT-HSM DOI 10.5281/zenodo.20299821, BLADE-SWARM DOI 10.5281/zenodo.20351198, and BLADE-INFRA-OT DOI 10.5281/zenodo.20342067.

Future Research Roadmap

The following roadmap outlines a sustained, multi-year research agenda to be conducted in the United States. Each phase builds on the current body of work, seven provisional patent applications, twenty-four Zenodo deposits, twelve hardware research platforms, 2,800+ structured simulation runs, and advances the governance architectures toward physical validation, formal certification, standards adoption, and production deployment across U.S. defense and autonomous transportation sectors.

Near Term (1-3 years): Physical Validation & Formal Verification

• Formal verification: Complete TLA+ and UPPAAL model checking of HMAA, CARA, SATA, FLAME, and MAIVA governance invariants across all authority state transitions. Current TLA+ verification covers 23,748 states and 8 properties, of which 5 invariants and a liveness property are verified and 2 upgrade-path properties are vacuous at this bound for the rover testbed; the target is full-pipeline verification for BLADE-EDGE and BLADE-AV configurations.
• Rover and UAV physical builds: Complete assembly and integration testing of both platforms (37 and 52 components respectively). Conduct physical flight testing with Cube Orange+ autopilot and MAVLink/HIL bridge. Validate simulation predictions against real sensor data under adversarial and degraded conditions.
• BLADE-EDGE prototype fabrication: Commission RTL implementation of the FPGA governance bitstream (SATA-FLAME-on-Silicon). Fabricate the dual Jetson AGX Orin + dual Zynq UltraScale+ carrier board. Conduct MIL-STD-810G environmental qualification testing.
• BLADE-AV vehicle integration: Integrate ROS 2 perception pipeline with Gazebo vehicle physics simulation. Conduct hardware-in-the-loop testing with the 9-module governance pipeline. Validate KILOVAC LEV200 relay actuation timing against the 25ms electromechanical model used in simulation. Begin ISO 26262 ASIL-D decomposition documentation.
• Academic completion: Complete Georgetown University M.P.S. Applied Intelligence program (STEM-designated). Submit formal verification results for peer-reviewed publication.

Mid Term (3-5 years): Certification, Standards Engagement & Pilot Deployment

• BLADE-AV certification pathway: Fabricate 4-layer controlled-impedance carrier board PCB. Complete ISO 26262 ASIL-D functional safety assessment at an accredited facility. Pursue NHTSA AV STEP program participation with safety case documentation built on the published Zenodo research artifacts and simulation evidence.
• BLADE-EDGE field evaluation: Conduct operational testing with U.S. defense partners for directed-energy weapon governance and counter-UAS applications. Validate governance pipeline performance under real-world electromagnetic, thermal, and kinematic conditions.
• Standards body engagement: Submit governance architecture specifications to NIST, IEEE, and SAE for standardization consideration. Contribute to the development of federal AV safety standards being established under the SELF DRIVE Act (H.R. 7390) and NHTSA's AV Framework, specifically the safety case, cybersecurity, and fallback behavior requirements that this research directly addresses.
• Critical infrastructure pilots: Develop deployment frameworks for integrating SATA-HMAA-CARA governance into U.S. critical infrastructure control systems (power grid SCADA, water treatment automation, transportation management). Conduct pilot implementations in defense-adjacent operational environments.
• Peer-reviewed publication: Submit formal verification results, physical validation data, and cross-domain portability analysis to IEEE, ACM, and domain-specific safety journals.

Long Term (5+ years): Industry Adoption & National Standards

• Autonomous vehicle production deployment: License BLADE-AV governance architecture to commercial autonomous vehicle programs. The open CC BY 4.0 research artifacts and published engineering specifications enable U.S. manufacturers to adopt the governance pipeline for ISO 26262 / SAE J3016 compliance without starting from scratch, accelerating safe AV deployment on U.S. roads.
• Defense program integration: Transition BLADE-EDGE governance architecture into U.S. defense acquisition programs for autonomous weapons governance, counter-UAS systems, and JADC2 command authority management. Provide the technical foundation for DoDD 3000.09 compliance verification.
• Authority lifecycle governance as a discipline: Establish authority-governed autonomy as a recognized engineering discipline with standardized specifications adopted across U.S. defense, intelligence, critical infrastructure, and autonomous transportation sectors. Publish open reference implementations enabling broad U.S. industry adoption.
• SBIR/STTR and grant-funded research: Pursue Small Business Innovation Research (SBIR) Phase II proposals and federal research grants to fund advanced development, operational testing, and technology transition activities within the U.S. defense and transportation innovation ecosystem.

This research agenda will be conducted entirely within the United States, published through U.S.-accessible platforms, and aligned with U.S. regulatory frameworks. The applicant's continued presence in the United States is essential to advancing this work, proximity to U.S. defense partners, NHTSA regulatory processes, standards bodies (NIST, IEEE, SAE), and academic collaborators at Georgetown University cannot be replicated from abroad.

Potential U.S. Deployment Scenarios

The governance architectures developed in this research program address concrete operational needs across U.S. strategic sectors. The following deployment scenarios illustrate how these systems would function in real-world environments:

• Autonomous Defense Systems: HMAA provides real-time authority computation for unmanned combat platforms, ensuring that weapons engagement authority follows a verifiable chain from human commander through automated decision layers, with CARA providing deterministic recovery if authority lockout occurs during a mission. The BLADE-EDGE Governance Node implements the complete 9-module pipeline in a MIL-STD-810G ruggedized edge device for directed-energy weapon governance.
• Critical Infrastructure Automation: Power grid, water treatment, and transportation systems using autonomous controllers require SATA-style continuous sensor attestation to verify that the data feeding automated decisions has not been tampered with or degraded.
• AI Command and Control (JADC2): Multi-domain military operations increasingly rely on AI-assisted decision-making. ERAM provides escalation risk quantification that allows commanders to understand how decision-time compression affects authority integrity across interconnected systems.
• Autonomous Ground Vehicles: The BLADE-AV Governance Node applies the governance pipeline to civilian drive-by-wire authority gating under ISO 26262 ASIL-D, SAE J3016 Level 4, and NHTSA ADS requirements. As NHTSA reported 1,429 autonomous vehicle incidents (2021-2025) and Congress requires cybersecurity plans for "false vehicle control commands" under H.R. 7390, BLADE-AV provides a hardware-enforced solution: SATA sensor trust fusion detects spoofing, ADARA identifies adversarial ML attacks, and a three-leg redundant fail-safe circuit (Zynq GPIO + dual MAX16161 watchdog) drives a normally-open KILOVAC relay that cuts drive-by-wire authority in hardware, without firmware involvement, when computed trust falls below thresholds. 1,200 simulation runs, 12 attack scenarios, no observed unsafe authority transitions.
• Maritime Surveillance & ASV Governance: The BLADE-MARITIME Governance Node extends the governance pipeline to autonomous surface vehicles with hydroacoustic sonar, magnetic anomaly detection (MAD), and AIS spoofing detection. Sea-state authority damping α(H) dynamically adjusts governance authority based on wave height. Acoustic-delay-aware Byzantine consensus enables multi-ASV coordination over underwater acoustic modems. 84-component platform targets MIL-STD-810G / IP68 for contested maritime environments.
• Industrial Safety Systems: Aerospace manufacturing, petrochemical operations, and nuclear-adjacent facilities use autonomous monitoring systems that require formal governance over when automated systems can act independently versus when human authorization is mandatory.
• Intelligence Community Applications: Automated intelligence processing and AI-augmented analysis systems require governance architectures that maintain auditable authority chains, ensuring that AI-assisted assessments can be traced back to human-authorized parameters.