DETAILED ACTION
Notice of AIA Status
1. 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
2. Applicant’s remarks received on 02/19/2026 with respect to the amended independent claims have been acknowledged but not found persuasive. A new ground of rejection has been introduced necessitated by the corresponding amendment. Currently claims 1-20 are rejected.
With respect to the 101 rejection, Applicant argues that Examiners should not expand “mental process” to encompass limitations that cannot practically be performed in the human mind. Although the statement is valid, the claimed invention would practically encompass mental process given the broadest and reasonable interpretation as the claimed limitation fails to eliminate the possibility of such.
The claimed sign data comprising speed values, transportation mode values, and entity parameters which would by recognized and interpreted by a driver. The driver could read and recognize speed values and icons for car, truck, bus, and etc.; and properly judge whether he/she is heading southbound/northbound or on the left or right side of road. Take an example, when two speed signs on the right side of road with one for maximum speed of a truck and one for minimum speed of a vehicle, a sedan drivers on the right side of the road would ignore the maximum speed sign whereas a truckdriver on the right side would take a heed to both signs. When given multiple speed limit signs associated with different vehicles during work zone or school zone, the drive can still easily identify a proper speed limit for his/her vehicle at present time. After all, signs are designed for human to interpret and would have been meaningless if humans were not able to mentally process them. The added “processor” is only a generic placeholder and/or extra solution activities.
Remarks on 103 rejection are moot in view of a new ground of rejection necessitated by the amendment.
Response to Amendment
Claim Rejections - 35 USC § 101
3. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Regarding claims 1-20 under the broadest reasonable interpretation, the terms of the claims are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skilled in the art. See MPEP 2111.
The claims are directed generating a speed limit data for matching sign data and corresponding transportation mode. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea).
The claims do not have any limitations that are indicative of how to integrate judicial exception into a practical application such as improvements to functioning of a computer or a technical field, using any particular machine, effect a transformation of a particular article to a different state or thing, or apply the judicial exception in any meaningful way beyond generally linking the use to a particular technological environment. Therefore, the claims as a whole do not amount to significantly more than the judicial exception.
A patent may be obtained for “any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof," 35 U.S.C. § 101, but “laws of nature, natural phenomena, and abstract ideas are not patentable.”
Step 1
Claims 1-20 are directed to one of the four statutory categories of eligible subject matter (process): thus, the claim pass Step 1 of the Subject Matter Eligibility Test.
Step 2A, prong 1 analysis
Claims 1-4 and 6 are directed to matching speed limit signs to a transportation mode such as car/truck and generating speed limit data for the car/truck.
The claimed sign data comprising speed values, transportation mode values, and entity parameters which would by recognized and interpreted by a driver. The driver could read and recognize speed values and icons for car, truck, bus, and etc.; and properly judge whether he/she is heading southbound/northbound or on the left or right side of road.
Take an example, when two speed signs on the right side of road with one for maximum speed of a truck and one for minimum speed of a vehicle, a sedan drivers on the right side of the road would ignore the maximum speed sign whereas a truckdriver on the right side would take a heed to both signs. When given multiple speed limit signs associated with different vehicles during work zone or school zone, the drive can still easily identify a proper speed limit for his/her vehicle at present time.
Therefore, any driver can easily differentiate traffic speed limit signs at various location/condition and decide a current speed limit for a car or truck the driver is driving. After all, signs are designed for human to interpret and would have been meaningless if humans were not able to mentally process them.
In claims 5 and 10, a passenger can mark a map to update a speed limit of a work zone and remind the driver a current speed limit based on information from multiple signs.
In claims 7 and 8, a ML model is trained and used as a general computer to recognize current speed limit. Notice a human brain is an example of computational network.
Claim 9 defines parameters or data easily recognized/processed by the driver.
The same rationale above applies to claims 11-20 respectively.
Step 2A, prong 2 analysis
The claims do not have any limitations that are indicative of integration of the judicial exception into a practical application such as improvements to functioning of a computer or a technical field, using any particular machine, effect a transformation of a particular article to a different state or thing, or how to apply the judicial exception in any meaningful way beyond generally linking the use to a particular technological environment.
Step 2B
Further, the claims do not include other additional elements that are beyond what is well-understood, routine, conventional activities in the field and sufficient to amount to significantly more than the judicial exception. The added “processor” is only a generic placeholder and/or extra solution activities.
Conclusion:
The claims do not include additional elements amount to significantly more in terms of improving functionalities of a computer/device itself, improving another technology or technical field, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine claim to a particular useful application or by use of a particular machine that is unconventional. In conclusion, the claims 1-20 do not comply with the current standards for patent eligible subject matter under 35 USC § 101.
Claim Rejections - 35 USC § 103
4. 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.
51066.. Claims 1-6, 9-16, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al (US Pub: 2021/0287538) and Fowe (US Pub: 2020/0143671); and in further view of Uwabo et al (US Pub: 20240221387).
Regarding claim 1 (currently amended), Zhang et al teaches: A system, comprising: a memory configured to store computer executable instructions; and one or more processors configured to execute the instructions to [p0004]: receive sign data relating to one or more traffic entities [p0014], the sign data comprising at least one of: a set of speed values, a set of transportation mode values, and one or more entity parameters associated with the corresponding one or more traffic entities [p0047, p0068]; generate matching data based on a matching between the set of speed values and the set of transportation mode values, based on the one or more entity parameters [p0083, p0084]; and generate speed limit data based at least on: the matching data, the sign data and a predefined condition associated with transportation mode [p0087, p0088, p0093].
Zhang et al’s transportation mode values can relate to vehicle properties, usage, or road conditions and different speed limits are set for different transportation mode values. For a redundant teaching in the same field of endeavor, Fowe further teaches different speed values associated with different transportation mode values [p0050-p0052]; Wherein the predefined condition comprises using matching pairs of the set of speed values associated with a same transportation mode value to generate the speed limit data [p0075, p0047, p0048 (Generated speed limit value may be transmitted and used for warning.)].
Therefore, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of the two to generate a speed value associated with transportation mode for inclusion of different scenarios.
Zhang et al in view of Fowe does not explicitly state exclusion of speed limit data for different transportation mode value although that would have been obvious because speed data processing for cars or trucks is to avoid applying wrong vehicle class speeds. In the same field of endeavor, Uwabo et al further teaches: wherein the predefined condition excludes generating the speed limit data from the set of speed values associated with different transportation mode values [p0091-p0096]. Therefore, given Uwabo et al’s prescription on including/excluding speed limit signs associated with various transportation mode, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to exclude speed limit data generation associated with unrelated transportation mode value for preventing false recognition.
Regarding claim 2 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Zhang et al in view of Fowe further teaches: The system of claim 1, wherein the processor is further configured to: generate a speed value cluster based on the one or more entity parameters, the speed value cluster comprising a set of speed cluster points corresponding to each of the set of speed values [Zhang: p0040-p0042]; and generate a mode cluster based on the one or more entity parameters, the mode cluster comprising a set of mode cluster points corresponding to each of the set of transportation mode values [Fowe: p0047, p0061, p0068, p0069, p0072 (Forming mode cluster points for detecting vehicles with specific properties within a section with a threshold.)].
Regarding claim 3 (original), the rationale applied to the rejection of claim 2 has been incorporated herein. Zhang et al further teaches: The system of claim 2, wherein the processor is further configured to: generate the matching data comprising one or more matching pairs based on the set of speed cluster points, the mode cluster points and a distance threshold, wherein a matching pair from the one or more matching pairs comprises a first speed cluster point from the set of speed cluster points matched with a corresponding first mode cluster point from the set of mode cluster points, a distance between the first speed cluster point and the first mode cluster point being less than the distance threshold [p0067-p0069 (mode in terms of light-weighted or heavy-weighted vehicles)].
Regarding claim 4 (original), the rationale applied to the rejection of claim 2 has been incorporate herein. Zhang et al in view of Fowe further teaches: The system of claim 2, wherein the predefined condition comprises: generate the speed limit data for a first transportation mode when two or more matching pairs from the matching data are associated with the first transportation mode and a distance between the two or more matching pairs is less than a predefined threshold [Fowe: p0051, p0075; Zhang: p0007, p0008, p0068 (One speed for truck and one speed for car.)]; generate the speed limit data when two or more speed cluster points from the set of speed cluster points are independent of mode cluster points and a distance between the two or more speed cluster points is less than the predefined threshold [Zhang: p0009, p0010 (Multiple speed limit signs for both car and truck)]; and generate the speed limit data for a first mode of transportation when one or more matching pairs from the matching data are associated with the first mode of transportation, one or more speed cluster points from the set of speed cluster points are independent of a mode of transportation and a distance between the one or more matching pairs and the one or more speed cluster points is less than the predefined threshold [Zhang: fig. 5C, p0082, p0083 (509a associated with time within a threshold distance of 509b is independent of mode of transportation.)] .
Regarding claim 5 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Zhang et al further teaches: The system of claim 1, wherein the processor is further configured to update a map database based on the generated speed limit data; and generate navigation instructions based on the updated map database [p0073].
Regarding claim 6 (original), the rationale applied to claim 1 has been incorporated herein. Zhang et al further teaches: The system of claim 1, wherein the generated speed limit data indicates a decreasing speed limit data [fig. 5C: 509c].
Regarding claim 9 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Zhang et al in view of Fowe further teaches: The system of claim 1, wherein the one or more entity parameter comprises: at least one of: corresponding distance, corresponding heading, corresponding side of a road, and corresponding link ID relating to the corresponding one or more traffic entities [Zhang: p0045, p0046; Fowe: p0049-p0051].
Regarding claim 10 (original), the rationale applied to the rejection of claim 6 has been incorporated herein. Zhang et al further teaches: The system of claim 6, wherein the processor is further configured to: determine roadwork zone based on the speed limit data, the speed limit data indicating an end speed limit less than a speed threshold; and generate navigation instructions based on the determine roadwork zone [p0047, fig. 5C: 509a (Speed limit zone due to time and location is on obvious alternative to a work zone.)].
Claims 11 (currently amended) and 12-16 (original) have been analyzed and rejected with regard to claims 1-6 respectively.
Claims 19 (currently amended) and 20 (original) have been analyzed and rejected with regard to claims 12 and 13 respectively and in accordance with Zhang et al’s further teaching on: A computer program product comprising at least one non-transitory computer- readable storage medium having stored thereon computer-executable program code instructions which when executed by a computer, cause the computer to carry out operations [p0015].
61066.. Claims 7, 8, 17, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al (US Pub: 2021/0287538), Fowe (US Pub: 2020/0143671), and Uwabo et al (US Pub: 20240221387); and in further view of Barathi (US Pub: 2022/0121691) and Chen et al (US Pub: 2018/0335307).
Regarding claim 7 (original), the rationale applied to the rejection of claim 1 has been incorporated herein. Zhang et al in view of Fowe and Uwabo et al does not specify machine learning. In the same field of endeavor, Barathi teaches: The system of claim 1, wherein the processor is further configured to: generate the matching data and the speed limit data using a trained machine-learning based computational network, wherein the trained machine-learning based computational network is trained based on a set of vehicle features, a set of entity features and a set of map features [p0040-p0043].
And for a redundant teaching in the same field of endeavor, Chen et al further trains the network based on a set of vehicle, entity, and map features [p0126] Therefore, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to train a ML model based on set of features for recognizing signs and updating navigation map with improved accuracy.
Regarding claim 8 (original), the rationale applied to the rejection of claim 7 has been incorporated herein. Barathi and Chen et al further teach: The system of claim 7, wherein, to train the machine-learning based computational network, the processor is further configured to: receive training data comprising a set of vehicle features of one or more vehicles [Chen: p0036], a set of entity features of one or more traffic entities, a set of map features and ground truth data associated with valid speed limit data and invalid speed limit data; determine a plurality of features corresponding to the valid speed limit data and the invalid speed limit data, using the training data [Barathi: p0032, p0033, p0053, p0069 (Invalid speed limit data can be negative observation of a speed limit/feature.)]; and train the machine-learning based computational network to generate test speed limit data for one or more test sign data, using the plurality of features and the set of training data [Barathi: p0041; Chen: p0126]. Therefore, given Barathi and Chen et al’s teaching on training ML model with varies feature data for recognition, and Zhang et al in view of Fowe’s teaching on generating test speed limit data, it would have been obvious for an ordinary skilled in the art before the effective filing date of the claimed invention to combine the teaching of all to generate test speed limit data for test sign data using ML model for improving efficiency and accuracy.
Regarding claims 17 and 18, the rationale applied to the rejection of claim 11 has been incorporated herein. Claims 17 and 18 have been analyzed and rejected with regard to claims 7 and 8 respectively.
Conclusion
7. There is a new ground of rejection necessitated by the corresponding amendment presented in this Office Action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP 706.07(a).
Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Contact
8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to FAN ZHANG whose telephone number is (571)270-3751. The examiner can normally be reached on Mon-Fri 9:00-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benny Tieu can be reached on 571-272-7490. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Fan Zhang/
Patent Examiner, Art Unit 2682
Prosecution Insights