Cyngn Secures 24th U.S. Patent for Adaptive Autonomous Vehicle System

Mar 9, 2026
Cyngn has received its 24th U.S. patent for a system that enables adaptive, real-time vehicle modeling for autonomous driving, supporting versatile deployment across different vehicle types.

Cyngn Inc. has been granted its 24th U.S. patent for autonomous driving technology, announced in a press release. The new patent, titled “System and Method of Adaptive, Real-Time Vehicle System Identification for Autonomous Driving,” covers technology that enables vehicles to generate gear-specific models and adjust control commands in real time.

The patented system builds dynamic vehicle models to produce precise control signals, validates those signals through simulation before execution, and adapts as hardware components degrade. This approach allows Cyngn’s software to operate across diverse vehicle types without requiring platform-specific redesigns.

Additional features include fleet-wide synchronization of model updates, collective data sharing for improved control accuracy, and monitoring of wear on components such as tires and brakes. These capabilities aim to enhance reliability and performance across industrial fleets.

Cyngn’s DriveMod technology, already deployed on Motrec MT-160 Tuggers and BYD Forklifts, enables customers in manufacturing and logistics to integrate autonomous functionality without major infrastructure changes.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Robotics Brief or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Robotics Brief

Weekly coverage of AI-driven robotics advances in industrial automation, autonomous vehicles, and robotic systems.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.