Obviousness — US Patent 12037004

Obviousness Analysis under 35 U.S.C. § 103 for US Patent 12037004

Under 35 U.S.C. § 103, a patent claim is obvious if "the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains." The analysis requires considering the scope and content of the prior art, the differences between the prior art and the claims at issue, the level of ordinary skill in the pertinent art, and any secondary considerations of non-obviousness.

For US Patent 12037004, the independent claims (Claim 1, 11, and 19) generally describe a system and method for controlling an SDV's driving mode (autonomous or manual) by comparing the competence levels of an on-board SDV control processor and a human driver in the face of an operational anomaly. The control is then assigned to the more competent entity.

The patent itself lists several prior art documents in its "Cross-Reference to Related Applications" section:

U.S. application Ser. No. 17/374,656, filed Jul. 13, 2021
U.S. application Ser. No. 16/997,202, filed Aug. 19, 2020 (issued as U.S. Pat. No. 11,091,171 on Aug. 17, 2021)
U.S. application Ser. No. 16/899,407, filed Jun. 11, 2020
U.S. application Ser. No. 15/955,874, filed Apr. 18, 2018 (issued as U.S. Pat. No. 10,717,446 on Jul. 21, 2020)
U.S. application Ser. No. 15/341,225, filed Nov. 2, 2016 (issued as U.S. Pat. No. 10,029,701 on Jul. 24, 2018)
U.S. application Ser. No. 14/865,393, filed Sep. 25, 2015 (issued as U.S. Pat. No. 9,566,986 on Feb. 14, 2017)

These patents are considered prior art, as they are part of the same patent family and precede the filing date of the application for US12037004B2 (July 17, 2023).

Level of Ordinary Skill in the Art

A person having ordinary skill in the art (POSA) in the context of this patent would likely possess a strong understanding of:

Autonomous vehicle systems, including sensors, control algorithms, and human-machine interfaces.
Software and hardware design for embedded systems in vehicles.
Data analysis and machine learning for evaluating performance and predicting faults.
Safety protocols and risk assessment in vehicle operation.

Potential Combinations of Prior Art and Motivation to Combine

The core inventive step of US12037004 lies in the explicit comparison of control processor competence and human driver competence in the context of an operational anomaly, and then selectively assigning control based on this comparison. Many of the concepts individually are found in the broader field of autonomous vehicles. The key is whether combining these known concepts in the specific manner claimed would have been obvious to a POSA.

Given that US12037004B2 is a continuation of several earlier patents, it is highly probable that elements of the independent claims are individually disclosed or suggested within this family of patents.

Combination 1: US 9,566,986 and general knowledge of driver monitoring systems

US 9,566,986 ("Controlling driving modes of self-driving vehicles"): This patent, from which US12037004B2 claims priority, explicitly discusses detecting vehicle faults and altering driving modes (manual or autonomous) based on these faults. It also mentions a "driver profile" that provides "an indication of the driver's physical or other abilities," which is used to "further determine whether the SDV should be in autonomous or manual mode." The patent describes a fault-remediation table that indicates which mode the vehicle should be driven in when a certain fault is manifested. This patent also mentions a "weighted voting system" to weight variables for decision-making regarding driving modes.
General knowledge of driver monitoring systems: At the priority date of US 9,566,986 (September 25, 2015), driver monitoring systems capable of assessing driver attentiveness, fatigue, and even skill (e.g., based on erratic steering, braking patterns) were well-known in the art. These systems could generate a "human driver competence level" implicitly or explicitly based on observed behavior or pre-stored profiles.

Motivation to Combine: A POSA, faced with a vehicle fault (as taught by US 9,566,986), would be motivated to leverage available driver information (from the driver profile mentioned in US 9,566,986 or general driver monitoring systems) to make a more informed decision about whether to transition to manual or autonomous mode. If the vehicle's autonomous system is struggling with a fault, it is logical to consider if the human driver is also competent (or more competent) to handle that specific anomaly. The explicit mention of a "driver profile" in US 9,566,986, used to "further determine whether the SDV should be in autonomous or manual mode," strongly suggests the idea of evaluating human competence alongside vehicle state. The missing explicit step in US 9,566,986 is the direct comparison of competence levels in the context of an operational anomaly. However, the motivation to compare would stem from the desire to optimize safety and control, a fundamental goal in autonomous vehicle development.

Combination 2: US 10,029,701, US 10,717,446, and US 11,091,171, in conjunction with US 9,566,986

These later patents in the family would have further refined the concepts introduced in US 9,566,986, potentially providing more explicit details regarding competence level determination and comparison. While the full text of these patents is not provided here, their titles and sequential nature suggest they build upon the foundational ideas of controlling driving modes based on vehicle conditions and driver attributes.

US 9,566,986: Provides the foundation for detecting vehicle faults and using driver profiles to influence mode switching. It also describes a "fault-remediation table" and the use of "weighted voting system" for decisions.
US 10,029,701, US 10,717,446, US 11,091,171: As direct continuations, it is highly likely these patents would elaborate on mechanisms for assessing vehicle (control processor) capabilities and human driver capabilities in more detail, particularly concerning specific operational anomalies.

Motivation to Combine: The ongoing development within a patent family inherently demonstrates a motivation to refine and improve upon the initially disclosed invention. A POSA would be motivated to combine the general concept of using driver profiles and fault detection (from US 9,566,986) with any more specific teachings on evaluating and comparing competence levels that may be present in the continuation patents. The natural progression of self-driving technology would lead to more sophisticated decision-making, moving beyond a simple "fault detected, switch mode" to a nuanced "who is better equipped to handle this specific fault under these specific conditions?" This involves a direct comparison of capabilities, which is the crux of the independent claims of US 12037004.

Obviousness Argument for Independent Claim 1, 11, and 19

The independent claims of US 12037004 focus on the steps of:

Receiving sensor readings describing a current operational anomaly.
Determining a control processor competence level for the anomaly.
Receiving a driver profile describing a human driver competence level for the anomaly.
Comparing these two competence levels.
Selectively assigning control based on the comparison.

US 9,566,986 already teaches receiving sensor readings to detect vehicle faults (operational anomalies) and changing driving modes based on them. It also explicitly teaches using a "driver profile" to "further determine whether the SDV should be in autonomous or manual mode." The leap to explicitly defining and comparing "competence levels" for both the autonomous system and the human driver, specifically related to the current operational anomaly, would be an obvious refinement to a POSA seeking to implement a more robust and safer mode-switching mechanism.

The motivation to compare the competence levels stems from the inherent goal of choosing the safest and most efficient driving mode when a fault occurs. If both the human and the autonomous system have varying degrees of capability in handling different faults, a rational system design would necessitate a comparison to select the optimal controller. The concept of a "fault-remediation table" in US 9,566,986, which dictates the mode for a given fault, already implies an assessment of which mode is better suited. Expanding this to explicitly evaluate and compare the competence of the two potential controllers (human vs. AI) in real-time for a specific anomaly would be a logical and obvious enhancement for a POSA in the field of self-driving vehicles aiming for improved safety and reliability.