Machine Learning System for Modifying ADAS Behavior for Optimum Vehicle Trajectory

USPTO published patent application US20260091794A1 by inventors Nakamura and Kim for a machine learning system that modifies Advanced Driver Assistance Systems (ADAS) behavior to achieve optimum vehicle trajectory. The system uses V2X communication to transmit vehicle-specific customized data and receives individualized optimum behavior data, enabling connected vehicles to implement region-wide optimum behaviors while satisfying individual vehicle needs.

System and Method for Identification of Archaeological Features Using Remotely Sensed Data

The USPTO published patent application US20260092777A1 for an AI-driven system designed to identify gravesites and archaeological features through remote sensing and machine learning. Invented by Nicholas A. Kuncewicz, the technology integrates multimodal data including spectral imagery and LiDAR to detect and classify features. No compliance obligations arise from this patent application publication.

Artificial Intelligence Aiding for Gyrocompassing

Honeywell International Inc. filed patent application US20260092782A1 for an AI-assisted gyrocompassing system. The invention uses a trained machine learning model to predict vehicle attitude, heading, or latitude from inertial measurement unit data, reducing initial alignment time during gyrocompass unit start-up. The application was filed October 1, 2024, and published April 2, 2026.

Automated High Throughput Protorheology

USPTO published patent application US20260092850A1 disclosing methods and systems for automatic, high-throughput estimation of rheological properties of fluidic materials using videography and neural-network processing. The invention enables parallel testing to achieve economical property predictions without expensive rheometric equipment.

Method and Apparatus for Determining Physical State of Object via Neural Network

USPTO published patent application US20260093961A1 for a computer-implemented method using neural networks to determine physical states of objects. The method divides object shapes into sub-shapes, computes local solutions via a neural network model, and derives global solutions representing the object's physical state. Invented by Jianing Huang, Youjia Wu, Kaixuan Zhang, and Ze Cheng. This is an informational publication with no regulatory obligations.

Stealthx Transport LLC - FMCSA Procedural Order

The Federal Motor Carrier Safety Administration (FMCSA) issued a procedural order against Stealthx Transport LLC, a motor carrier. The document, filed as docket FMCSA-2026-0662-0003, appears to address procedural matters related to the carrier's regulatory compliance. Specific details of the order are not available in the filing.

Road Dawg Petition for FMCSA Rulemaking

The Federal Motor Carrier Safety Administration received a petition from Road Dawg requesting regulatory action on commercial vehicle safety and compliance standards. The petition (FMCSA-2023-0257-7006) is filed as part of an ongoing rulemaking docket. No specific compliance requirements or deadlines have been established as FMCSA has not yet acted on the petition.

CDL Drug and Alcohol Clearinghouse Information Collection Request

FMCSA published a notice requesting public comments on a revised Information Collection Request (ICR) for the Commercial Driver's License Drug and Alcohol Clearinghouse. The notice invites comments by June 1, 2026 on the continuing data collection requirements that support querying and reporting of CDL holders who test positive for controlled substances or misuse alcohol. The Clearinghouse was established by the 2016 final rule with a January 6, 2020 compliance date.

Stealthx Transport LLC Operating Authority Procedural Order

FMCSA issued a procedural order regarding Stealthx Transport LLC's operating authority application (Docket FMCSA-2026-0062). The order addresses procedural requirements for the carrier's pending application. This is an administrative action specific to one entity's application before the agency.

Commercial Driver Safety Risk Factors

FMCSA published a notice regarding Commercial Driver Safety Risk Factors on regulations.gov. The document, docket FMCSA-2025-0622, is accessible as an attachment but the main content is not displayed on the landing page. Regulated entities in the commercial trucking industry should review the attached PDF for relevant safety risk factor information.