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 .
Response to Arguments
The applicant has argued that Onica (US 2016/0325740) does not teach or suggest “generating…factor analysis data that corresponds to the sound evaluation data” by “analyzing a causal factor of the sudden braking…”. This argument is not persuasive because Onica, in Paragraph [0047], teaches analyzing causal factors for the sudden braking by asking relevant questions and correlating causal factors based on driver reply and analyzes said reply alongside driving data to determine contributing factors to the event.
The applicant has argued that the newly amended limitations of the independent claims overcome the currently rendered prior art rejections. This argument is moot, however, as a new grounds of rejection has been identified in a renewed search necessitated by said amendments.
Status of Claims
Claims 1-14 are rejected under 35 U.S.C. 103 as being unpatentable over Moustafa (US 2022/0126878) in view of Onica (US 2016/0325740) in view of Lowe (US 2023/0017550).
Priority
The priority date for this application is 01/26/2022.
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 1-14 are rejected under 35 U.S.C. 103 as being unpatentable over Moustafa (US 2022/0126878) in view of Onica (US 2016/0325740) in view of Lowe (US 2023/0017550). These references are analogous as they are all related to autonomous vehicle management.
As per Claim 1:
Moustafa discloses the following limitations:
“A processing method executed by a processor to execute a process associated with automated driving of a moving body, the processing method comprising: extracting, from dynamic data embedded in association with traveling points of the moving body on a digital map, automated driving data representing an automated driving state of the moving body at an analysis traveling point and sound evaluation data representing evaluation by a sound from an operator regarding the automated driving state identifying an autonomous-driving maneuver performed by an automated driving system at the analysis traveling point…”
Moustafa Paragraph [0061] discloses utilizing sensors to identify a vehicle system status, which would include driving state, which includes a voice recognition sensor
“and generating the factor analysis data based on the selected automated driving data.”
Moustafa Paragraphs [0179]-[0180] discloses identifying risks and analyzing risk factors when planning a route based on vocal input from a driver and the state of the vehicle.
Moustafa does not disclose the following limitations that Onica teaches:
“…including an evaluation that the automated driving system has performed a sudden braking, a sharp turn, or a rapid deceleration at the analysis traveling point”
Onica Paragraph [0047] teaches a feedback system based on noise provided by the driver about performance of autonomous driving features including braking events.
“and generating, based on the automated driving data, factor analysis data that corresponds to the sound evaluation data by of analyzing a causal factor of the sudden braking, the sharp turn, or the rapid deceleration made by the moving body during the automated driving, as the automated driving state at the analysis traveling point, wherein generating of the factor analysis data includes: selecting the automated driving data correlated with the sound evaluation data”
Onica Paragraph [0047] teaches identifying the causal factor of events, i.e. asking if a pedestrian was on a sidewalk.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the system disclosed by Moustafa with the sound evaluation taught by Onica. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to make the system more effective by considering user feedback.
Moustafa in view of Onica does not teach the following limitations that Lowe teaches:
“wherein in the extracting of the automated driving data and the sound evaluation data, when a reference parameter at the analysis traveling point is outside a tolerable range, the automated driving data and the sound evaluation data corresponding to the analysis traveling point is extracted, the reference parameter beyond the tolerable range is used as a starting criterion of factor analysis, as the reference parameter, an actual parameter indicating an actual behavior of the moving body, or a deviation of the actual parameter from a target parameter is used, the actual parameter includes at least one of a trajectory of the moving body, a position of the moving body, a speed of the moving body, an acceleration of the moving body, a deceleration of the moving body, a yaw angle of the moving body, a yaw rate of the moving body, a steering angle of the moving body, or a margin between the moving body and another road user”
Lowe Paragraph [0045] teaches initiating feedback requests to the driver based on accelerations and yaw actions outside of a tolerable range. The driver can respond in voice (See Paragraph [0069]), said responses then used for analysis.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the system taught by Moustafa in view of Onica with the triggering characteristics for feedback taught by Lowe. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to make the system more effective by providing targeted feedback for vehicular systems.
With regards to Claim 2, Moustafa in view of Onica in view of Lowe discloses all of the limitations of Claim 1 and further discloses the following limitations:
“further comprising displaying risk identification data, which identifiably indicates a risk level based on the generated factor analysis data, in a superimposed manner on the digital map.”
Moustafa Paragraph [0090] discloses identifying troublesome sections on digital maps based on handover information gathered in part based on vocal input received from a user.
With regards to Claim 3, Moustafa in view of Onica in view of Lowe discloses all of the limitations of Claim 2 and further discloses the following limitations:
“further comprising, instructing selection of a planned traveling route along which the moving body is planned to travel while the risk identification data is being displayed when generating the digital map.”
Moustafa Paragraph [0179]-[0180] discloses planning a route in accordance with the risk factor determined in part from voice information received from a user.
As per Claim 4: this claim is substantially similar to Claim 3 and is therefore rejected using the same references and rationale.
With regards to Claim 5, Moustafa in view of Onica in view of Lowe discloses all of the limitations of Claim 4 and further discloses the following limitations:
“ adding, to the digital map, traveling route data indicating the selected planned traveling route and the risk identification data to the digital map; and providing, to the moving body, the traveling route data and the risk identification data, which are added to the digital map.”
Moustafa Paragraph [0090] discloses identifying troublesome sections on digital maps based on handover information gathered in part based on vocal input received from a user.
With regards to Claim 7, Moustafa in view of Onica in view of Lowe discloses all of the limitations of Claim 1 and further discloses the following limitations:
“wherein generating the factor analysis data includes generating the factor analysis data based on the reference parameter.”
Moustafa Paragraphs [0179]-[0180] discloses identifying risks and analyzing risk factors when planning a route based on vocal input from a driver and the state of the vehicle.
With regards to Claim 8, Moustafa in view of Onica in view of Lowe discloses all of the limitations of Claim 1 and further discloses the following limitations:
“further comprising storing the generated factor analysis data in a storage medium.”
Moustafa Paragraph [0048] discloses storing data on a storage medium
As per Claim 9: this claim is substantially similar to Claim 1 and is therefore rejected using the same references and rationale.
As per Claim 10: this claim is substantially similar to Claim 3 and is therefore rejected using the same references and rationale.
As per Claim 11: this claim is substantially similar to Claim 1 and is therefore rejected using the same references and rationale.
As per Claim 12: this claim is substantially similar to Claim 3 and is therefore rejected using the same references and rationale.
With regards to Claim 13, Moustafa in view of Onica in view of Lowe teaches all of the limitations of Claim 1 and further teaches the following limitations:
“the sound evaluation data indicates a content of sound evaluation made by an operator boarded on the moving body on an actual behavior of the moving body, which is performing the automated driving, at the analysis traveling point in a traveling scene.”
Onica Paragraph [0047] teaches a feedback system based on noise provided by the driver about performance of autonomous driving features including braking events.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the system disclosed by Moustafa with the sound evaluation taught by Onica. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to make the system more effective by considering user feedback.
With regards to Claim 14, Moustafa in view of Onica in view of Lowe teaches all of the limitations of Claim 13 and further teaches the following limitations:
“wherein the traveling scene includes at least one of (i) an existence of an obstacle relative to the moving body, (ii) a state of traffic light involved in traveling of the moving body, or (iii) a type of traveling environment at the analysis traveling point, and the sound evaluation on the actual behavior of the moving body, which is performing the automated driving, includes an evaluation on at least one of the sudden braking, the sharp turn, or the rapid deceleration made by the moving body.”
Onica Paragraph [0047] teaches a feedback system based on noise provided by the driver about performance of autonomous driving features including braking events. It would be obvious to one of ordinary skill in the art that braking events would include traffic light events.
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the system disclosed by Moustafa with the sound evaluation taught by Onica. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to make the system more effective by considering user feedback.
Related References
Shiga (US 2020/0079383)
Related to driving evaluation systems.
Huang (US 2019/0250620)
Related to autonomous drive systems.
Breed (US 2007/0005609)
Related to vehicular communication systems.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Examiner Godfrey Maciorowski, whose telephone number is (571) 272-4652. The examiner can normally be reached on Monday-Friday from 7:30am to 5:00pm EST.
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If attempts to reach examiner by telephone are unsuccessful the examiner’s supervisor, Thomas Worden can be reached on (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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/GODFREY ALEKSANDER MACIOROWSKI/Examiner, Art Unit 3658
