How Autonomous Trucks Predict and Handle Tire Blowouts
This patent describes how an autonomous vehicle uses real-time sensor data, road conditions, and a dynamic model to predict tire failure and take corrective actions like adjusting its path or pulling over.
Original patent title: “Prevention, detection and handling of the tire blowouts on autonomous trucks”
This patent describes how an autonomous vehicle uses real-time sensor data, road conditions, and a dynamic model to predict tire failure and take corrective actions like adjusting its path or pulling over. Owned by Waymo with 23 claims and 28 forward citations, and it is expected to expire in 2039.
Coverage
What does this patent actually cover?
This patent outlines a method for an autonomous vehicle to evaluate its tires and prevent or handle failures. First, the vehicle's processors obtain baseline information about its tires (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1). While driving, it receives real-time sensor data, such as tire pressure, temperature, or shape (Claim 5), potentially from a tire pressure monitoring system (Claim 6) or even cameras and lidar (Claim 7). This data updates a 'dynamics model' that represents how the tires behave (Claim 1). The system also considers external factors like roadway conditions (e.g., obstacles like potholes (Claim 2, 3)) or environmental conditions (e.g., ambient temperature (Claim 4)). Based on the updated model and these conditions, the processors determine if the chance of a tire failure, such as a blowout, slow leak, or tread damage (Claim 10), exceeds a set limit. If it does, the autonomous vehicle takes a corrective action. For example, if a pothole is detected ahead and the system predicts a high risk of tire damage, the vehicle might adjust its position within the lane to avoid the impact (Claim 9). Other actions could include pulling over, changing its route, or notifying a remote service (Claim 11).
The gap
What does this patent NOT cover?
- Does not cover tire monitoring systems in vehicles that are solely human-driven, as the claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more → specifically refer to an 'autonomous vehicle'.
- Does not cover systems that only provide a simple alert (e.g., 'low tire pressure') without updating a 'dynamics model' to predict future failure based on multiple factors.
- Does not cover systems where a human driver makes all decisions for corrective action, as the claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more → state the processors 'causing the autonomous vehicle to take a corrective action'.
- Does not cover systems that only use internal tire sensor data without also considering external 'roadway condition' or 'environmental condition' information.
- Does not cover a system that only detects a tire failure after it has occurred without attempting to predict the possibility beforehand.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The cleverness lies in combining diverse data sources—baseline tire characteristics, real-time tire sensor readings, and predictive environmental/roadway conditions—into a dynamic model. This allows the autonomous vehicle to proactively assess the risk of tire failure and take specific, automated corrective actions *before* a problem escalates or even occurs, rather than just reacting to an existing failure.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Waymo autonomous trucks
Aurora Innovation self-driving trucks
TuSimple autonomous freight solutions
Future autonomous commercial delivery fleets
Why it matters
The bigger picture
Tire blowouts on large trucks can be extremely dangerous, leading to accidents and significant downtime. For autonomous trucks, predicting and handling these events without human intervention is critical for safety, reliability, and public trust. This technology helps ensure that self-driving vehicles can operate safely and efficiently, even when facing potential mechanical issues or challenging road conditions.
Filed
December 16, 2019
Market context
Who's building on this
Companies in this space
Waymo LLC, the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is a leading developer of autonomous driving technology and is actively working on autonomous trucking. Other companies like Aurora Innovation and TuSimple are also heavily invested in developing and deploying self-driving heavy-duty vehicles. These companies are all building robust safety and predictive maintenance systems, which would likely include advanced tire evaluation capabilities similar to those described in this patent.
Market impact
This technology directly addresses a significant safety and operational challenge for the emerging autonomous trucking industry. By enabling proactive tire maintenance and immediate, automated responses to potential failures, it can reduce the likelihood of accidents, improve vehicle uptime, and lower operational costs. This capability is essential for building confidence in autonomous fleets and accelerating their widespread adoption, making them a more viable and attractive option for logistics and transportation companies.
Claim 1 — Plain English
What this patent covers
This patent outlines a method for an autonomous vehicle to evaluate its tires and prevent or handle failures. First, the vehicle's processors obtain baseline information about its tires (Claim 1). While driving, it receives real-time sensor data, such as tire pressure, temperature, or shape (Claim 5), potentially from a tire pressure monitoring system (Claim 6) or even cameras and lidar (Claim 7). This data updates a 'dynamics model' that represents how the tires behave (Claim 1). The system also considers external factors like roadway conditions (e.g., obstacles like potholes (Claim 2, 3)) or environmental conditions (e.g., ambient temperature (Claim 4)). Based on the updated model and these conditions, the processors determine if the chance of a tire failure, such as a blowout, slow leak, or tread damage (Claim 10), exceeds a set limit. If it does, the autonomous vehicle takes a corrective action. For example, if a pothole is detected ahead and the system predicts a high risk of tire damage, the vehicle might adjust its position within the lane to avoid the impact (Claim 9). Other actions could include pulling over, changing its route, or notifying a remote service (Claim 11).
The clever bit
The cleverness lies in combining diverse data sources—baseline tire characteristics, real-time tire sensor readings, and predictive environmental/roadway conditions—into a dynamic model. This allows the autonomous vehicle to proactively assess the risk of tire failure and take specific, automated corrective actions *before* a problem escalates or even occurs, rather than just reacting to an existing failure.
What it does not cover
- Does not cover tire monitoring systems in vehicles that are solely human-driven, as the claims specifically refer to an 'autonomous vehicle'.
- Does not cover systems that only provide a simple alert (e.g., 'low tire pressure') without updating a 'dynamics model' to predict future failure based on multiple factors.
- Does not cover systems where a human driver makes all decisions for corrective action, as the claims state the processors 'causing the autonomous vehicle to take a corrective action'.
- Does not cover systems that only use internal tire sensor data without also considering external 'roadway condition' or 'environmental condition' information.
- Does not cover a system that only detects a tire failure after it has occurred without attempting to predict the possibility beforehand.
Patent timeline
Application submitted to the patent office
Patent enters public domain
PatentBrief Score
Impact Score
Moderate
Citation count
29/40
Moderately cited
Claim breadth
15/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
0/20
Older than 20 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$126K – $404K
Midpoint $253K · 13.3 yr remaining · industry ×0.9
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
23 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Grossman, W., & Patnaik, V. How Autonomous Trucks Predict and Handle Tire Blowouts (U.S. Patent No. 20,210,181,737). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/20210181737/prevention-detection-and-handling-of-the-tire-blowouts-on-autonomous-trucks
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Autonomous Trucks Predict and Handle Tire Blowouts cover?
This patent describes how an autonomous vehicle uses real-time sensor data, road conditions, and a dynamic model to predict tire failure and take corrective actions like adjusting its path or pulling over.
Who owns patent US 20210181737?
This patent is owned by Waymo.
When does this patent expire?
This patent is expected to expire on December 16, 2039, when the invention enters the public domain.
What is patent US 20210181737 cited by?
This patent has been cited by 28 later patents that build on its ideas.
What problem does this patent solve?
Tire blowouts on large trucks can be extremely dangerous, leading to accidents and significant downtime. For autonomous trucks, predicting and handling these events without human intervention is critical for safety, reliability, and public trust. This technology helps ensure that self-driving vehicles can operate safely and efficiently, even when facing potential mechanical issues or challenging road conditions.
What does this patent NOT cover?
Does not cover tire monitoring systems in vehicles that are solely human-driven, as the claims specifically refer to an 'autonomous vehicle'.
Patent monitoring