DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-6 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Anderson et al (US 2017/0137023).
Regarding claim 1, Anderson discloses an information processing device comprising a processor configured to:
calculate, for each of a plurality of combinations of a predetermined number of pieces of sensor information among a plurality of pieces of sensor information included in a vehicle (when a particular situation exists based on sensor data, active steering and suspension components induce predetermined motion, see at least [0042, 0065]), data for controlling a wheel speed and an inclination of each of four wheels of the vehicle (see at least [0035, 0047, 0136, 0139, etc.] which teaches real time wheel speed and active suspension data comparisons to look for issues, or comparing to data collected at an earlier time and stored in a lookup table, or preloaded data from when the vehicle was new. Each of the four wheels inclination are controlled via four wheel steering per at least [0077]), and
suspensions that support the wheels (see at least figure 7A) for each of the wheel speed, the inclination, and the suspension, and calculates control variables for each of the wheel speed, the inclination, and the suspension by aggregating the index values (as noted previously, all information is combined to control the vehicle suspension and steering output at all four wheels (see at least [0132, 0137, 0161 etc.]) see also at least [0177] which teaches combining all data, even redundant sources, to provide greater accuracy of the system); and
control autonomous driving on the basis of the control variables (see at least [0161, 0162, figure 7B, etc.]).
However, Anderson does not appear to explicitly disclose the dynamic vehicle data is “index values” per se. Based on the description in the instant specification however, it appears that the real time data alone or combined with lookup tables described in Anderson are at least functionally equivalent to the claimed “index values” via at least the data acquisition, e.g. using the data from various sensors per at least [0069] of Anderson to acquire the relevant information to control the active steering and suspension.
Regarding claim 2, Anderson teaches the processor controls the autonomous driving in units of millionths of a second on the basis of the control variables (Anderson teaches a response time as low as 10 milliseconds or microseconds). However, Anderson does not explicitly disclose a processor fast enough to control the vehicle in units of a billionth of a second or a nanosecond.
Although this way of claiming processor speeds is somewhat vague, it is widely well known that modern processors capable of processing at speeds on the nanosecond scale exist. As applicant does not appear to have invented any new such type of processor in the instant disclosure, the limitation is being considered as an obvious design choice. Therefore, the Examiner contends it would have been obvious to one having ordinary skill in the art at the time of the filing of the invention to use a processor capable of performing operations per second on the nanosecond scale in order to provide even more computing power which could provide an even safer autonomous vehicle control system, with obvious limitations being cost and size. In other words, the choosing of a fast processor by design and manufacture does not generally constitute patentable subject matter, including in the instant scenario.
Regarding claim 3, Anderson teaches the processor selects a combination of the plurality of pieces of sensor information for autonomous driving control targets including at least a wheel speed, an inclination, and a suspension, and calculates a predetermined number of index values (index values as addressed in claim 1 rejection) for each autonomous driving control target by the combination of the selected pieces of sensor information. Anderson teaches predetermined thresholds for objectional behavior in 0042. See also at 0065-0069 which teach further scenarios where predetermined outputs are made based on sensor data used to determine a desired control aka target. See also at least [0122, 0138]).
Regarding claim 4, Anderson teaches the processor calculates a predetermined number of index values for each autonomous driving control target on the basis of the combination of the plurality of pieces of sensor information changed according to a traveling status of the vehicle (as the only addition to claim 4 is the recited “changed” sensor information, see the rejection to claim 3 above and note that the scenarios described in Anderson are scenarios where erratic or undesired driving situations arise and create the need for changing automatic steering, suspension, and braking control).
Regarding claims 5 and 9, the scope of the claims is similar to that of rejected claims 1 and Anderson teaches the limitations of the claims 1, 3, and 4 and are thus rejected under the same rationale.
Regarding claim 6, Anderson teaches the processor weights the mutually used control variables of the autonomous driving control target (bias control per [0138] is interpreted as being equivalent to the claimed “weights”. It is noted this limitation is very thinly disclosed in the instant specification. Should applicant disagree, it is noted secondary reference Soltani cited below teaches vehicle sensors use fusion weights assigned to various data sources).
Regarding claim 8, Anderson teaches the inclination includes a steering angle and a camber angle (see at least [0017, 0047, 0134] which teaches forces on the wheels are measured and calculated via steering angle, slip angle and yaw and a tilt in the road surfaces as inputs. The Examiner contends these calculations are at least functionally equivalent to teaching of the calculation of the camber angle knowing the camber angle would help in the slip angle calculation).
Regarding claim 10, Anderson teaches a non-transitory recording medium storing a program for causing a computer to function as the information processing device according to claim 1 (programmed via software algorithms/models, see at least [0016, 0022, 0048, 0067, etc.).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Anderson et al (US 2017/0137023) in view of Soltani Bozchalooi et al. (US 2021/0097783).
Regarding claim 7, Anderson teaches the processor calculates the control variable from the index value by multivariate analysis by an integration method (at least [0177] reads on this limitation under BRI by integrating active suspension with other sensors and systems of the vehicle. See also at least [0178-0181] which teach output calculations are based on sensor fusion, which is essentially what appears to be broadly claimed here. If the claim is intended to use “integration method” as in a mathematical formula, it is noted that it would be obvious to use suitable mathematical formulae to calculate the required system outputs.
However, Anderson does not appear to explicitly disclose using deep learning or any types of language models. Soltani teaches a sensor fusion system for a vehicle having autonomous driving modes wherein a deep neural network is used to evaluate each vehicle data sources to help combine sensor information and control output of the vehicle (see at least [0029, 0032, 0034, 0039, etc.] and figure 4). Therefore, from the teaching of Soltani, it would have been obvious to one having ordinary skill in the art at the time of the filing of the invention to provide the vehicle of Anderson with higher processing power similar to that of the reinforcement learning deep neural network of Soltani in order to more quickly process surroundings for autonomous driving thus potentially increasing safety.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See attached 892 form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON HOLLOWAY whose telephone number is (571)270-5786. The examiner can normally be reached M-F 9-5:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tommy Worden can be reached at 571-272-4876. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JASON HOLLOWAY/Primary Examiner, Art Unit 3658
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