PTAB

IPR2025-00943

Tesla Inc v. Granite Vehicle Ventures LLC

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Petition
petition

1. Case Identification

2. Patent Overview

  • Title: Fault Remediation for Self-Driving Vehicles
  • Brief Description: The ’402 patent discloses a computer system for a self-driving vehicle (SDV) that receives sensor readings to monitor the vehicle's operational state. The system determines if a fault has occurred and, if the fault exceeds a danger threshold, it uses a "fault-remediation table" to identify and implement an associated corrective action.

3. Grounds for Unpatentability

Ground 1: Claims 1 and 3 are obvious over Attard and Frazer

  • Prior Art Relied Upon: Attard (Patent 9,406,177) and Frazer (Patent 9,494,926).
  • Core Argument for this Ground:
    • Prior Art Mapping: Petitioner argued that Attard teaches nearly all limitations of independent claim 1, including an autonomous vehicle that uses a "system of sensors" to generate "confidence assessments" indicating whether the vehicle should operate autonomously. Petitioner asserted that when a confidence assessment falls below a threshold, this constitutes the determination of a "fault," which prompts a corrective action like ceasing autonomous operations. Petitioner contended that Frazer supplies the sole missing element: a "fault-remediation table." Frazer discloses an "event table" for an autonomous vehicle that explicitly maps a set of conditions (faults) in one column to a corresponding instruction or action in another column, which performs the same function as the claimed table.
    • Motivation to Combine: A Person of Ordinary Skill in the Art (POSITA) would combine Attard's fault detection system with Frazer's table-based action-selection method to improve the system's efficiency and reliability. Using a lookup table is a well-known and logical technique for organizing conditional logic, which would reduce latency in selecting a corrective action and improve overall vehicle safety compared to an unorganized list of fault responses.
    • Expectation of Success: A POSITA would have had a high expectation of success because the combination involved applying a known data-structuring technique (Frazer's table) to a known type of autonomous control system (Attard's) to achieve the predictable result of faster and more organized fault response.

Ground 2: Claim 4 is obvious over Attard and Hampiholi

  • Prior Art Relied Upon: Attard (Patent 9,406,177) and Hampiholi (Application # 2016/0267335).
  • Core Argument for this Ground:
    • Prior Art Mapping: Petitioner argued that Attard’s overall confidence assessment (designated as "Capital Φ") meets the limitation of determining a "competence level of the processor" (CPCL), as it reflects the system's confidence in its ability to operate autonomously. To meet the further limitation of determining a "competence level of a human driver," Petitioner relied on Hampiholi. Hampiholi explicitly teaches a system for determining a human driver's competence by measuring their distraction level (e.g., talking on the phone, not looking ahead) and assigning a corresponding "severity rank." The combination of Attard's CPCL and Hampiholi's human competence level was argued to render claim 4 obvious.
    • Motivation to Combine: A POSITA would combine these teachings to create a safer and more robust SDV. The motivation was to account for two distinct sources of risk: system-based faults (per Attard) and human-based inattentiveness (per Hampiholi). Hampiholi expressly states a goal of increasing safety, providing a clear reason to integrate its driver monitoring capabilities into a comprehensive autonomous system like Attard's.
    • Expectation of Success: The combination was predictable, as it involved integrating known sensor inputs and analysis methods (for driver state) into a control system already designed to process multiple sensor inputs for safety decisions.

Ground 3: Claim 6 is obvious over Attard, Hampiholi, McNew, and Scofield

  • Prior Art Relied Upon: Attard (Patent 9,406,177), Hampiholi (Application # 2016/0267335), McNew (Patent 10,377,303), and Scofield (Patent 11,040,725).

  • Core Argument for this Ground:

    • Prior Art Mapping: This ground builds upon the Attard/Hampiholi combination to meet additional limitations in claim 6. Petitioner introduced McNew to teach a sensor system that detects a "physical state of the human driver" by using a "steering wheel grip sensor" to determine if the driver's hands are on the wheel. Petitioner introduced Scofield to teach determining the processor's competence level using "active learning data," which Scofield describes as aggregated sensor data from other vehicles traveling the same road segment to assess its complexity.
    • Motivation to Combine: A POSITA would add McNew's steering wheel sensors to the Attard/Hampiholi system to provide a more direct and reliable input for determining the driver's physical state and readiness to take control. A POSITA would incorporate Scofield's use of crowd-sourced "active learning data" into Attard's processor competence calculation to make safer, more informed decisions based on conditions (e.g., a traffic jam ahead) that its own sensors might not yet detect.
    • Expectation of Success: Success was expected because these modifications represented incremental improvements using known sensor technologies and data sources to enhance an existing safety framework, leading to the predictable benefits of more accurate driver-state assessment and more context-aware system competence evaluation.

  • Additional Grounds: Petitioner asserted additional obviousness challenges based on combinations including Grimm (for weighted voting), Dolgov (for vehicle maintenance sensors), and Zhu (for using cameras to determine weather conditions) to meet limitations of various dependent claims.

4. Relief Requested

  • Petitioner requests the institution of an inter partes review and the cancellation of claims 1, 3-4, 6, 8-11, and 13-24 of Patent 11,597,402 as unpatentable.