Autonomous Vehicle

Cyngn secures notice of allowance for 24th US autonomous vehicle patent

Press Release, 23 January 2026

Cyngn, the California-based autonomous vehicle technology developer, has received a notice of allowance for its 24th U.S. patent, marking another milestone in its growing intellectual property portfolio focused on AI-powered self-driving systems. The patent, titled System and Method of Adaptive, Real-Time Vehicle System Identification for Autonomous Driving, is expected to be officially issued next month and will advance Cyngn’s capabilities in adaptive vehicle behavior and control.

This latest patent builds on a significant streak of innovation: since August 2023, Cyngn has secured thirteen additional patents, expanding its portfolio and reinforcing its leadership in autonomous mobility technology. According to CEO Lior Tal, these patents reflect the company’s sustained investment in practical, real-world technological advances that differentiate its solutions and help solve pressing operational challenges in industrial settings.

Cyngn’s expanding patent base supports its broader mission of driving the adoption of safe, scalable and flexible autonomous systems across sectors such as manufacturing, logistics and material handling. Central to this strategy is the company’s DriveMod platform, which equips conventional industrial vehicles like tuggers and forklifts with autonomous navigation and advanced perception capabilities. Over the past year, Cyngn has also rolled out new features for DriveMod, expanded its commercial deployments and deepened integrations with major warehouse and manufacturing technologies to streamline operations and improve efficiency.

With 24 U.S. patents on the horizon, Cyngn continues to build a defensible technology foundation that aims to reduce operating costs, enhance safety and deliver tangible value to industrial customers. These innovations not only strengthen the company’s competitive position but also signal growing confidence in autonomous vehicle technologies as operational tools in complex industrial environments.

Compiled using AI

Back to top button