Cyngn Secures its 22nd U.S. Patent: for its AI-Powered Autonomous Vehicle Technologies
Since August 2023, Cyngn has been granted twelve additional patents, bringing the total U.S. patents granted to 22.
MENLO PARK, Calif., April 3, 2025 /PRNewswire/ -- Cyngn Inc. (the "Company" or "Cyngn") (NASDAQ:CYN) announced the official granting of a new patent, 12,246,733, for the Company's innovative autonomous vehicle (AV) solutions.
The patent, System and Methods of Off-Board Centric Autonomous Driving Computation, introduces a cloud-based approach to autonomous vehicle operation, distributing computing tasks between the vehicle and the cloud to significantly reduce onboard hardware requirements. Vehicles transmit sensor data to cloud servers, where functions like environment mapping, decision-making, and route planning are processed before driving commands are sent back for execution. This allows the vehicle to prioritize safety-critical and time-sensitive functions.
The significance of this patent lies in its ability to enable lighter, more cost-effective autonomous vehicles while enabling sophisticated driving algorithms. Furthermore, the patent includes fleet management functionality, facilitating seamless coordination of multiple autonomous vehicles through a centralized cloud infrastructure.
"Since August 2023, we've been granted twelve additional patents, bringing our total to 22 U.S. patents," said Lior Tal, CEO of Cyngn. "This milestone reflects our ongoing commitment to driving innovation and advancing autonomous technology, as we continue to build out a robust patent portfolio to protect our intellectual property. Each new patent represents the hard work of our team and our dedication to developing real-world solutions that are transforming material handling."
The grant of this patent marks a significant milestone in Cyngn's intellectual property strategy, further bolstering its position in the AV industry. This success follows Cyngn's recent patent issuance announcement of its 21st patent.
Cyngn provides its customers a seamless way to adopt self-driving technology into their operations without high upfront costs.
Previous patents include:
Patent Number | Title | Publication Date | |
22. | US-12,246,733-B2 | SYSTEM AND METHOD OF OFF-BOARD CENTRIC AUTONOMOUS DRIVING COMPUTATION | 3/11/2025 |
21. | US-12,039,867-B2 | ADAPTIVE OBJECT-BASED DECISION MAKING SYSTEM | 7/16/2024 |
20. | US-12,032,099-B2 | ADAPTIVE MOTION COMPENSATION OF PERCEPTION CHANNELS | 7/09/2024 |
19. | US-11,851,074-B2 | SYSTEM AND METHODS OF LARGE-SCALE AUTONOMOUS DRIVING VALIDATION | 12/26/2023 |
18. | US-11,837,090-B2 | SYSTEM AND METHODS OF ADAPTIVE TRAFFIC RULE-BASED DECISION MAKING FOR AUTONOMOUS DRIVING | 12/5/2023 |
17. | US-11,837,089-B2 | MODULAR EXTENSIBLE BEHAVIORAL DECISION SYSTEM FOR AUTONOMOUS DRIVING | 12/5/2023 |
16. | US-11,767,034-B2 | SYSTEM AND METHOD OF COMPUTATION ACCELERATION FOR AUTONOMOUS DRIVING SYSTEMS | 9/26/2023 |
15. | US-11,760,368-B2 | SYSTEM AND METHOD OF SAME-LOOP ADAPTIVE SIMULATION FOR AUTONOMOUS DRIVING | 9/19/2023 |
14. | US-11,747,454-B2 | GRANULARITY-FLEXIBLE EXISTENCE-BASED OBJECT DETECTION | 9/5/2023 |
13. | US-11,745,762-B2 | SYSTEM AND METHODS OF ADAPTIVE TRAJECTORY PREDICTION FOR AUTONOMOUS DRIVING | 9/5/2023 |
12. | US-11,745,747-B2 | SYSTEM AND METHOD OF ADAPTIVE DISTRIBUTION OF AUTONOMOUS DRIVING COMPUTATIONS | 9/5/2023 |
11. | US-11,745,750-B2 | SYSTEM AND METHOD OF LARGE-SCALE AUTOMATIC GRADING IN AUTONOMOUS DRIVING USING A DOMAIN-SPECIFIC LANGUAGE | 9/5/2023 |
10. | US-11,679,726-B2 | VEHICLE SENSOR SYSTEMS | 6/20/2023 |
9. | US-11,673,577-B2 | SYSTEM AND METHODS OF ADAPTIVE RELEVANCY PREDICTION FOR AUTONOMOUS DRIVING | 6/13/2023 |
8. | US-11,668,833-B2 | OBSTACLE DETECTION SYSTEMS | 6/6/2023 |
7. | US-11,651,583-B2 | MULTI-CHANNEL OBJECT MATCHING | 5/16/2023 |
6. | US-11,614,527-B2 | SELF-ADAPTIVE LIDAR-CAMERA SYNCHRONIZATION SYSTEM | 3/28/2023 |
5. | US-11,592,565-B2 | FLEXIBLE MULTI-CHANNEL FUSION PERCEPTION | 2/28/2023 |
4. | US-11,555,928-B2 | THREE-DIMENSIONAL OBJECT DETECTION WITH GROUND REMOVAL INTELLIGENCE | 1/17/2023 |
3. | US-11,372,115-B2 | VEHICLE LOCALIZATION | 6/28/2022 |
2. | US-11,186,234-B2 | VEHICLE SENSOR SYSTEMS | 11/30/2021 |
1. | US-11,169,271-B2 | OBSTACLE DETECTION SYSTEMS | 11/9/2021 |
For a comprehensive view of Cyngn's patents focused on modularity and flexibility of autonomous vehicle systems with multiple sensor modalities and configurations, please visit the USPTO.
About Cyngn
Cyngn develops and deploys scalable, differentiated autonomous vehicle technology for industrial organizations. Cyngn's self-driving solutions allow existing workforces to increase productivity and efficiency. The Company addresses significant challenges facing industrial organizations today, such as labor shortages, costly safety incidents, and increased consumer demand for eCommerce.
Cyngn's DriveMod Kit can be installed on new industrial vehicles at end of line or via retrofit, empowering customers to seamlessly adopt self-driving technology into their operations without high upfront costs or the need to completely replace existing vehicle investments.
Cyngn's flagship product, its Enterprise Autonomy Suite, includes DriveMod (autonomous vehicle system), Cyngn Insight (customer-facing suite of AV fleet management, teleoperation, and analytics tools), and Cyngn Evolve (internal toolkit that enables Cyngn to leverage data from the field for artificial intelligence, simulation, and modeling). For all terms referenced within, please refer to the Company's annual report on Form 10-K with the SEC filed on March 6, 2025.
Where to find Cyngn:
- Website: https://cyngn.com
- X: https://x.com/cyngn
- LinkedIn: https://www.linkedin.com/company/cyngn
- YouTube: https://www.youtube.com/@cyngnhq
Investor Contact:
Donald Alvarez, CFO
[email protected]
Media Contact:
Luke Renner, Head of Marketing
[email protected]
Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Any statement that is not historical in nature is a forward-looking statement and may be identified by the use of words and phrases such as "expects," "anticipates," "believes," "will," "will likely result," "will continue," "plans to," "potential," "promising," and similar expressions. These statements are based on management's current expectations and beliefs and are subject to a number of risks, uncertainties and assumptions that could cause actual results to differ materially from those described in the forward-looking statements, including the risk factors described from time to time in the Company's reports to the Securities and Exchange Commission (SEC), including, without limitation the risk factors discussed in the Company's annual report on Form 10-K filed with the SEC on March 6, 2025. Readers are cautioned that it is not possible to predict or identify all the risks, uncertainties and other factors that may affect future results. No forward-looking statement can be guaranteed, and actual results may differ materially from those projected. Cyngn undertakes no obligation to publicly update any forward-looking statement, whether as a result of new information, future events, or otherwise.
This new patent of System and Methods of Off-Board Centric Autonomous Driving Computation enables autonomous vehicles to operate with reduced onboard computing hardware by offloading heavy computing tasks to the cloud. The vehicles send sensor data to cloud servers, which handle complex tasks like environment mapping, decision-making, and route planning. The cloud then sends back driving commands to the vehicle for execution, which allows the vehicle to focus on safety-critical and time-sensitive functions.
The significance in this patent lies in the fact that it allows for lighter, more cost-effective autonomous vehicles while enabling more sophisticated and safer driving algorithms. Moreover, the patent also supports fleet management capabilities, allowing multiple vehicles to be coordinated through the same cloud infrastructure.
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