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 .
There is no 35 U.S.C. 101 rejection because the data is acquired using a particular sensor to scan the environment, and this data is then transformed into a data packet and transmitted. This is a practical application.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Fairfield 20190171202.
Regarding claims 1, 15, and 17, Fairfield discloses a computer-implemented method, product, and system, the method comprising:
scanning, with at least one sensor, an environment of an autonomous vehicle on which the at least one sensor is connected to collect environment data (P43 discloses the computer vision system 140 could include hardware and software operable to process and analyze images in an effort to determine objects, important environmental features (e.g., stop lights, road way boundaries, etc.), and obstacles. The computer vision system 140 could use object recognition, Structure From Motion (SFM), video tracking, and other algorithms used in computer vision, for instance, to recognize objects, map an environment, track objects, estimate the speed of objects, etc.);
analyzing, with at least one processor, the environment data using a machine learning model, wherein the machine learning model has been trained using historical data to recognize a plurality of emergency situations, wherein the analyzing comprises identifying at least a portion of the environment data as corresponding to a first emergency situation of a plurality of emergency situations (P70 discloses a microphone may capture the sound of the siren of an emergency vehicle. A processing system may be able to identify that the captured audio signal is indicative of an emergency vehicle. In another example, the microphone may capture the sound of an exhaust of another vehicle, such as that from a motorcycle. A processing system may be able to identify that the captured audio signal is indicative of a motorcycle. The data captured by the microphone may form a portion of the sensor data collected from the environment. P40 discloses a sensor fusion algorithm 138 could include, for instance, a Kalman filter);
in response to identifying the first emergency situation, generating a data packet comprising the environment data corresponding to the first emergency situation; and transmitting the data packet to a report center external to the vehicle to report the first emergency situation (P50 discloses a data storage 114 may contain instructions 115 (e.g., program logic) executable by the processor 113 to execute various functions of vehicle 100, including those described above in connection with FIG. 1. Data storage 114 may contain additional instructions as well, including instructions to transmit data to, receive data from, interact with, and/or control one or more of the propulsion system 102, the sensor system 104, the control system 106, and the peripherals 108. Regarding the new amendment, the entire purpose of the Fairfield is remote assistance. P4 states that assistance is requested from a remote operator. This means external to the vehicle); and
in response to identifying the first emergency situation, activating a capture task to capture data associated with the at least one sensor (P54 discloses the camera 130 could capture a plurality of images that could represent information about a state of an environment of the vehicle 100 operating in an autonomous mode. Further, as discussed in the limitation directly above, P70 discloses a microphone may capture the sound of the siren of an emergency vehicle. Regarding this limitation for claim 15, P84 discloses any scenario with ill-defined precedence for the vehicle to follow may be included as well. This means that the capture task may be for any scenario, either the triggering or elimination of a signal). Note: regarding claim 17, while the new limitations add new material with respect to claim 17, these are mirror limitations of claims 6-8, which are addressed below. Specifically, while these new limitations include a first and second sensor with first and second data, this is disclosed in the explanation above from P57 and P70 showing at least a microphone and a camera, which are two different sensors capturing two different types of data.
Regarding claim 2, Fairfield discloses wherein the at least one sensor is integrated into an autonomous driving system of the vehicle or is independent from the autonomous driving system (P4- discloses the computer vision system is part of the control system. P51 discloses that the vehicle is autonomous).
Regarding claim 3, Fairfield discloses in response to identifying the first emergency situation, causing the autonomous vehicle to automatically execute at least one avoidance action (P62 teaches an obstacle avoidance system).
Regarding claim 4, Fairfield discloses identifying a pattern of sounds and/or images in the environment data; and matching the pattern to a pattern known to the machine learning model as corresponding to the first emergency situation (See P70).
Regarding claim 5, P60 discloses data transmission methods, all of which are digitized. Secure is a very broad term, and as such, the types of communications listed could be considered secure absent any narrowing and defining of the term secure.
Regarding claims 6-13, Fairfield these claims detail audio or visual sensors, particular information, and identifiers which are all disclosed by the paragraphs referenced for the sensors in the rejection to claim 1. Regarding claim 12, because the sensors capture images and sounds based on an actual image or sound situation existing, the capture signal will not happen (i.e. be deactivate) based on the signal not happening.
Regarding claim 14, P43 discloses detecting light.
All other dependent claims are mirror claims.
Response to Arguments
Applicant’s arguments are fully considered but are deemed unpersuasive. Regarding points 1 and 2, Applicant states that the transmission of communication is triggered by navigation assistance, not an emergency situation. The Examiner disagrees. The claims recite that the data packet is generated in response to identifying the first emergency situation, but they do not recite that absent this emergency situation, a data packet cannot be generated. That is, whether an autonomous vehicle captures images or sounds that only occur with emergency situations or that there is an emergency situation and the data packet is generated consisting of the emergency situation, the data packet is still generated “in response” to the emergency situation.
Regarding point 3, a Kalman filter operates by using a previous state estimate to update its current state estimate. This is historical data.
Regarding point 4, please see explanation for points 1 and 2.
Regarding points 5 and 6, these are addressed in the rejection to claims 1 and 17 above.
Regarding point 7, this is a summation of points 1-6.
Regarding the dependent claims, Applicant merely states that Fairfield does not disclose certain elements, which amount to conclusory statements.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARYAN E WEISENFELD whose telephone number is (571)272-6602. The examiner can normally be reached M-F 9-5.
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ARYAN E. WEISENFELD
Primary Examiner
Art Unit 3689
/ARYAN E WEISENFELD/Primary Examiner, Art Unit 3663
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