DETAILED CORRESPONDENCE
This is the first office action regarding application number 18/946,791, filed on 13 November 2024.
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 .
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 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.
Claim Objections
Claim 11 is objected to because of the following informality: the claim recites "a first vehicle" twice. Therefore it is unclear whether there are one or two first vehicles being claimed. For the purpose of compact prosecution, the second recitation of "a first vehicle", will be read as "the first vehicle".
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Regarding Claims 1-20
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-7, 9 and 18 of U.S. Patent No. US 12183203 B2 (and '203 hereinafter). Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of ‘203 include each and every feature of the claims in the instant application, plus additional details. A person having ordinary skill in the art before the effective filing date of the invention would have been more than capable of modifying the claim language of ‘203 to be the same as the claim language of the instant application.
Regarding Claim 1
'203 recites a computer-implemented method (see claim 1) comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see claim 1);
processing, by the first vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see claim 1); and
in response to an event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, the processed driving behavior data to a second detecting entity (see claim 1).
Regarding Claim 2
'203 recites the computer-implemented method of claim 1 (as discussed above in claim 1),
wherein the second detecting entity comprises at least one of a second vehicle and roadside infrastructure (see claim 1).
Regarding Claim 3
'203 recites the computer-implemented method of claim 1 (as discussed above in claim 1),
wherein the event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle comprises a change in positional relationship between the first vehicle and the subject vehicle (see claim 1).
Regarding Claim 4
'203 recites the computer-implemented method of claim 1 (as discussed above in claim 1),
wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, unsafe driving behavior by the subject vehicle based on the collected driving behavior data (see claim 2); and
determining, by the first vehicle, that the detected unsafe driving behavior does not satisfy a threshold factor for unsafe driving behavior that indicates the subject vehicle is driving unsafely (see claim 2).
Regarding Claim 5
'203 recites the computer-implemented method of claim 1 (as discussed above in claim 1),
wherein the collected driving behavior data comprises lane offset measurements for the subject vehicle (see claim 4).
Regarding Claim 6
'203 recites the computer-implemented method of claim 5 (as discussed above in claim 5),
wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, swerving by the subject vehicle based on the lane offset measurements (see claim 3); and
determining, by the first vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely (see claim 3).
Regarding Claim 7
'203 recites the computer-implemented method of claim 1 (as discussed above in claim 1),
wherein the driving behavior data is collected from one or more image and proximity sensors of the first vehicle (see claim 5).
Regarding Claim 8
'203 recites the computer-implemented method of claim 1 (as discussed above in claim 1),
further comprising:
constructing, by the first vehicle, a pseudo-identification for the subject vehicle (see claim 6); and
in response to the event which interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, the pseudo-identification to the second detecting entity (see claim 6).
Regarding Claim 9
'203 recites the computer-implemented method of claim 8 (as discussed above in claim 8),
wherein the pseudo-identification comprises one or more hash values corresponding to at least one of the following:
vehicle type (see claim 7);
vehicle color (see claim 7); and
location of the subject vehicle within a road section (see claim 7).
Regarding Claim 10
'203 recites the computer-implemented method of claim 1 (as discussed above in claim 1),
further comprising:
determining, by the first vehicle, that the subject vehicle is within observable range of the second detecting entity (see claim 18).
Regarding Claim 11
'203 recites a computer-implemented method comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see claim 1);
processing, by a first vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see claim 1); and
in response to detecting a change in positional relationship between the first vehicle and the subject vehicle that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, the processed driving behavior data to a second detecting entity (see claim 1).
Regarding Claim 12
'203 recites the computer-implemented method of claim 11 (as discussed above in claim 11),
wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, unsafe driving behavior by the subject vehicle based on the collected driving behavior data (see claim 2); and
determining, by the first vehicle, that the detected unsafe driving behavior does not satisfy a threshold factor for unsafe driving behavior that indicates the subject vehicle is driving unsafely (see claim 2).
Regarding Claim 13
'203 recites the computer-implemented method of claim 11 (as discussed above in claim 11),
wherein the collected driving behavior data comprises lane offset measurements for the subject vehicle (see claim 4).
Regarding Claim 14
'203 recites the computer-implemented method of claim 13 (as discussed above in claim 13),
wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, swerving by the subject vehicle based on the lane offset measurements (see claim 3); and
determining, by the first vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely (see claim 3).
Regarding Claim 15
'203 recites the computer-implemented method of claim 11 (as discussed above in claim 11),
wherein the driving behavior data is collected from one or more image and proximity sensors of the first vehicle (see claim 5).
Regarding Claim 16
'203 recites the computer-implemented method of claim 11 (as discussed above in claim 11),
further comprising:
constructing, by the first vehicle, a pseudo-identification for the subject vehicle; and
in response to detecting the change in positional relationship between the first vehicle and the subject vehicle that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, the pseudo-identification to a second vehicle (see claim 6).
Regarding Claim 17
'203 recites the computer-implemented method of claim 16 (as discussed above in claim 16),
wherein the pseudo-identification comprises one or more hash values corresponding to at least one of the following:
vehicle type (see claim 7);
vehicle color (see claim 7); and
location of the subject vehicle within a road section (see claim 7).
Regarding Claim 18
'203 recites the computer-implemented method of claim 11 (as discussed above in claim 11),
further comprising:
determining, by the first vehicle, that the subject vehicle is within observable range of the second detecting entity (see claim 18).
Regarding Claim 19
'203 recites a first vehicle comprising:
one or more processers including machine executable instructions in non-transitory memory to cause the first vehicle to:
collect driving behavior data associated with a subject vehicle (see claim 9);
process the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see claim 9); and
in response to an event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring the processed driving behavior data to a second detecting entity (see claim 9).
Regarding Claim 20
'203 recites the first vehicle of claim 19 (as discussed above in claim 19),
wherein the event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle comprises a change in positional relationship between the first vehicle and the subject vehicle (see claim 9).
Claim Rejections - 35 USC § 103
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-4, 7-12 and 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Yang (US 20200008028 A1 and Yang hereinafter), in view of Bletzer et al. (US 20180096600 A1 and Bletzer hereinafter).
Regarding Claim 1
Yang teaches a computer-implemented method (see all Figs; [0003]) comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see all Figs.; [0003 "A sensing vehicle may comprise one or more sensors on-board the vehicle. The one or more sensors may collect behavior data about one or more surrounding vehicles within a detectable range of the sensing vehicle ... Such information may be used to generate a safe driving index for the one or more surrounding vehicles, and/or the sensing vehicle."], [0028], [0057] and [0117]-[0120]; the sensing vehicle corresponds to the claimed "first vehicle" and the surrounding vehicle(s)/target vehicle(s) corresponds to the claimed "subject vehicle");
processing, by the first vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see [0003], [0028 "The behavior data of the one or more surrounding vehicles and/or the sensing vehicle may be collected and/or aggregated, and analyzed. The analyzed behavior may be used to detect safe or unsafe driving behavior by the one or more surrounding vehicles and/or the sensing vehicle. A safe driving index may be generated and associated with a vehicle identifier of a corresponding vehicle and/or driver identifier of a driver operating the corresponding vehicle."]-[0029], [0116], [0125]-[0126] and [0163]); and
transferring, by the first vehicle, the processed driving behavior data to a second detecting entity (see [0102], [0116]-[0118 "The first and second sensing vehicles may share the information gathered about the target vehicle ... Alternatively or in addition, the first and second sensing vehicles may transit the information to a data center."] and [0127]-[0129]).
Yang is silent regarding transferring the processed driving behavior data in response to an event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle.
Bletzer teaches a computer-implemented method (see all Figs.; [0003]-[0007]) comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see Fig. 12, "What vehicle B can see" from vehicle C to B; [0072]; Vehicle B corresponds to the claimed "first vehicle" and Vehicle D corresponds to the claimed "subject vehicle".); and
in response to an event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, processed driving behavior data to a second detecting entity (see Fig. 10, all; Fig. 12, "Vehicle B Composite" from vehicle B to A; [0067], [0070 "In FIG. 10, Vehicle B 1008 has been drawn at a location where it is visible to Vehicle A 1004 but cannot directly see Vehicle D 1002 hidden by the truck."] and [0072 "In FIG. 12 the Composite view built up by Vehicle B 1008 will include Vehicle D 1002 by virtue of data received from Vehicle C and this data is shared with Vehicle A—so Vehicle D 1002 is no longer hidden from Vehicle A 1004."]; Vehicle A corresponds to the claimed "second detecting entity").
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process of Yang to include instructions for transferring the processed driving behavior data to a second detecting entity in response to an event which interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, as taught by Bletzer, in order to enable the second detecting entity to “see through” an obstruction on the road.
Regarding Claim 2
Modified Yang teaches the computer-implemented method of claim 1 (as discussed above in claim 1),
Yang further teaches wherein the second detecting entity comprises at least one of a second vehicle and roadside infrastructure (see Fig. 6, sensing vehicles 610 and data center 630; [0049], [0118 "The first and second sensing vehicles may share the information gathered about the target vehicle ... Alternatively or in addition, the first and second sensing vehicles may transit the information to a data center."], [0127], [0141] and [0151]; the first/second sensing vehicle(s) and/or the data center correspond to the second vehicle or roadside infrastructure).
Bletzer additionally teaches wherein the second detecting entity comprises a second vehicle (see Fig. 12, "Vehicle B Composite" from vehicle B to A; [0072 "In FIG. 12 the Composite view built up by Vehicle B 1008 will include Vehicle D 1002 by virtue of data received from Vehicle C and this data is shared with Vehicle A—so Vehicle D 1002 is no longer hidden from Vehicle A 1004."]; Vehicle A corresponds to the claimed "second detecting entity").
Regarding Claim 3
Modified Yang teaches the computer-implemented method of claim 1 (as discussed above in claim 1),
Yang is silent regarding wherein the event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle comprises a change in positional relationship between the first vehicle and the subject vehicle.
Bletzer teaches wherein the event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle comprises a change in positional relationship between the first vehicle and the subject vehicle (see Fig. 10, all; [0003], [0007] and [0070]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process of Yang to include instructions for transferring the processed driving behavior data to a second detecting entity in response to a change in positional relationship between the first vehicle and the subject vehicle, as taught by Bletzer, in order to enable the second detecting entity to “see through” an obstruction on the road.
Regarding Claim 4
Modified Yang teaches the computer-implemented method of claim 1 (as discussed above in claim 1),
Yang further teaches wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, unsafe driving behavior by the subject vehicle based on the collected driving behavior data (see [0003], [0028 "The behavior data of the one or more surrounding vehicles and/or the sensing vehicle may be collected and/or aggregated, and analyzed. The analyzed behavior may be used to detect safe or unsafe driving behavior by the one or more surrounding vehicles and/or the sensing vehicle. A safe driving index may be generated and associated with a vehicle identifier of a corresponding vehicle and/or driver identifier of a driver operating the corresponding vehicle."]-[0029], [0116], [0125]-[0126] and [0163]); and
determining, by the first vehicle, that the detected unsafe driving behavior does not satisfy a threshold factor for unsafe driving behavior that indicates the subject vehicle is driving unsafely (see [0171]-[0172 "If the safe driving index does not exceed a particular threshold, the UBI may not offer any insurance for that vehicle."]).
Regarding Claim 7
Modified Yang teaches the computer-implemented method of claim 1 (as discussed above in claim 1),
Yang further teaches wherein the driving behavior data is collected from one or more image and proximity sensors of the first vehicle (see [0047 "The one or more sensors 110 carried by the sensing vehicle may include, but are not limited to location sensors (e.g., global positioning system (GPS) sensors, mobile device transmitters enabling location triangulation), vision sensors (e.g., imaging devices capable of detecting visible, infrared, or ultraviolet light, such as cameras), proximity sensors (e.g., ultrasonic sensors, lidar, time-of-movement cameras),..."] and [0062]).
Regarding Claim 8
Modified Yang teaches the computer-implemented method of claim 1 (as discussed above in claim 1),
Yang further teaches further comprising:
constructing, by the first vehicle, a pseudo-identification for the subject vehicle (see Figs. 8 and 11, all; [0028], [0129 "For instance, a label indicating “speeding” may take less memory than a still image or video clip showing the vehicle speeding. The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity. For examples they may include category of behavior (e.g., speeding, running red light, unsafe merge, unsafe lane change, not stopping for stop sign, not yielding to pedestrians, etc.), time at which the behavior occurred, location at which the behavior occurred, and/or information about the vehicle performing the behavior (e.g., vehicle identifier such as license plate, color of vehicle, make of vehicle, mode of vehicle, vehicle brand, vehicle type)."], [0144]-[0146], [0175]-[0181]); and
transferring, by the first vehicle, the pseudo-identification to the second detecting entity (see [0102], [0116]-[0118] and [0127]-[0129 "The sensing vehicle may only transmit descriptions to a data center that are indicative of instances of unsafe or safe driving behaviors, or other categories of behavior, as described elsewhere herein. The sensing vehicle may only transmit descriptions that may seem relevant to the other functions or applications of the vehicle monitoring system as described elsewhere herein. This may also apply to descriptions that may be transmitted to and/or shared with other vehicles in addition to or as an alternative to the descriptions transmitted to the data center."]).
Yang is silent regarding transferring the pseudo-identification in response to the event which interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle.
Bletzer teaches further comprising:
constructing, by the first vehicle, a pseudo-identification for the subject vehicle (see [0007], [0036] and [0042]); and
in response to the event which interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, the pseudo-identification to the second detecting entity (see Fig. 10, all; Fig. 12, "Vehicle B Composite" from vehicle B to A; [0067], [0070 "In FIG. 10, Vehicle B 1008 has been drawn at a location where it is visible to Vehicle A 1004 but cannot directly see Vehicle D 1002 hidden by the truck."] and [0072 "In FIG. 12 the Composite view built up by Vehicle B 1008 will include Vehicle D 1002 by virtue of data received from Vehicle C and this data is shared with Vehicle A—so Vehicle D 1002 is no longer hidden from Vehicle A 1004."]; Vehicle A corresponds to the claimed "second detecting entity").
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process of Yang to include instructions for transferring the pseudo-identification to a second vehicle in response to an event which interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, as taught by Bletzer, in order to enable the second detecting entity to “see through” an obstruction on the road.
Regarding Claim 9
Modified Yang teaches the computer-implemented method of claim 8 (as discussed above in claim 8),
Yang further teaches wherein the pseudo-identification comprises one or more hash values corresponding to at least one of the following:
vehicle type (see [0072] and [0129 "The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity ... information about the vehicle performing the behavior (e.g., vehicle identifier such as license plate, color of vehicle, make of vehicle, mode of vehicle, vehicle brand, vehicle type)."]);
vehicle color (see [0072] and [0129 "The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity ... information about the vehicle performing the behavior (e.g., vehicle identifier such as license plate, color of vehicle, make of vehicle, mode of vehicle, vehicle brand, vehicle type)."]); and
location of the subject vehicle within a road section (see [0072] and [0129 "The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity. For examples they may include category of behavior (e.g., speeding, running red light, unsafe merge, unsafe lane change, not stopping for stop sign, not yielding to pedestrians, etc.), time at which the behavior occurred, location at which the behavior occurred..."]).
Regarding Claim 10
Modified Yang teaches the computer-implemented method of claim 1 (as discussed above in claim 1),
Yang further teaches further comprising:
determining, by the first vehicle, that the subject vehicle is within observable range of the second detecting entity (see Fig. 4, all; [0092 "A sensing vehicle 400 may have a detectable range 405. The detectable range may be relative to the sensing vehicle and/or an inertial reference frame. In one example, the detectable range may include areas in front of and behind the sensing vehicle. One or more of the surrounding vehicles may fall within the detectable range, such as vehicles 410, 420, 430."]-[0096], [0102], [0117]-[0118]).
Regarding Claim 11
Yang teaches a computer-implemented method (see all Figs; [0003]) comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see all Figs.; [0003 "A sensing vehicle may comprise one or more sensors on-board the vehicle. The one or more sensors may collect behavior data about one or more surrounding vehicles within a detectable range of the sensing vehicle ... Such information may be used to generate a safe driving index for the one or more surrounding vehicles, and/or the sensing vehicle."], [0028], [0057] and [0117]-[0120]; the sensing vehicle corresponds to the claimed "first vehicle" and the surrounding vehicle(s)/target vehicle(s) corresponds to the claimed "subject vehicle");
processing, by a first vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see [0003], [0028 "The behavior data of the one or more surrounding vehicles and/or the sensing vehicle may be collected and/or aggregated, and analyzed. The analyzed behavior may be used to detect safe or unsafe driving behavior by the one or more surrounding vehicles and/or the sensing vehicle. A safe driving index may be generated and associated with a vehicle identifier of a corresponding vehicle and/or driver identifier of a driver operating the corresponding vehicle."]-[0029], [0116], [0125]-[0126] and [0163]); and
transferring, by the first vehicle, the processed driving behavior data to a second detecting entity (see [0102], [0116]-[0118 "The first and second sensing vehicles may share the information gathered about the target vehicle ... Alternatively or in addition, the first and second sensing vehicles may transit the information to a data center."] and [0127]-[0129]).
Yang is silent regarding transferring the processed driving behavior data in response to detecting a change in positional relationship between the first vehicle and the subject vehicle that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle.
Bletzer teaches a computer-implemented method (see all Figs.; [0003]-[0007]) comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see Fig. 12, "What vehicle B can see" from vehicle C to B; [0072]; Vehicle B corresponds to the claimed "first vehicle" and Vehicle D corresponds to the claimed "subject vehicle".); and
in response to detecting a change in positional relationship between the first vehicle and the subject vehicle that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, processed driving behavior data to a second detecting entity (see Fig. 10, all; Fig. 12, "Vehicle B Composite" from vehicle B to A; [0067], [0070 "In FIG. 10, Vehicle B 1008 has been drawn at a location where it is visible to Vehicle A 1004 but cannot directly see Vehicle D 1002 hidden by the truck."] and [0072 "In FIG. 12 the Composite view built up by Vehicle B 1008 will include Vehicle D 1002 by virtue of data received from Vehicle C and this data is shared with Vehicle A—so Vehicle D 1002 is no longer hidden from Vehicle A 1004."]; Vehicle A corresponds to the claimed "second detecting entity").
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process of Yang to include instructions for transferring the processed driving behavior data to a second detecting entity in response to a change in positional relationship between the first vehicle and the subject vehicle, as taught by Bletzer, in order to enable the second detecting entity to “see through” an obstruction on the road.
Regarding Claim 12
Modified Yang teaches the computer-implemented method of claim 11 (as discussed above in claim 11),
Yang further teaches wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, unsafe driving behavior by the subject vehicle based on the collected driving behavior data (see [0003], [0028 "The behavior data of the one or more surrounding vehicles and/or the sensing vehicle may be collected and/or aggregated, and analyzed. The analyzed behavior may be used to detect safe or unsafe driving behavior by the one or more surrounding vehicles and/or the sensing vehicle. A safe driving index may be generated and associated with a vehicle identifier of a corresponding vehicle and/or driver identifier of a driver operating the corresponding vehicle."]-[0029], [0116], [0125]-[0126] and [0163]); and
determining, by the first vehicle, that the detected unsafe driving behavior does not satisfy a threshold factor for unsafe driving behavior that indicates the subject vehicle is driving unsafely (see [0171]-[0172 "If the safe driving index does not exceed a particular threshold, the UBI may not offer any insurance for that vehicle."]).
Regarding Claim 15
Modified Yang teaches the computer-implemented method of claim 11 (as discussed above in claim 11),
Yang further teaches wherein the driving behavior data is collected from one or more image and proximity sensors of the first vehicle (see [0047 "The one or more sensors 110 carried by the sensing vehicle may include, but are not limited to location sensors (e.g., global positioning system (GPS) sensors, mobile device transmitters enabling location triangulation), vision sensors (e.g., imaging devices capable of detecting visible, infrared, or ultraviolet light, such as cameras), proximity sensors (e.g., ultrasonic sensors, lidar, time-of-movement cameras),..."] and [0062]).
Regarding Claim 16
Modified Yang teaches the computer-implemented method of claim 11 (as discussed above in claim 11),
Yang further teaches further comprising:
constructing, by the first vehicle, a pseudo-identification for the subject vehicle (see Figs. 8 and 11, all; [0028], [0129 "For instance, a label indicating “speeding” may take less memory than a still image or video clip showing the vehicle speeding. The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity. For examples they may include category of behavior (e.g., speeding, running red light, unsafe merge, unsafe lane change, not stopping for stop sign, not yielding to pedestrians, etc.), time at which the behavior occurred, location at which the behavior occurred, and/or information about the vehicle performing the behavior (e.g., vehicle identifier such as license plate, color of vehicle, make of vehicle, mode of vehicle, vehicle brand, vehicle type)."], [0144]-[0146], [0175]-[0181]); and
transferring, by the first vehicle, the pseudo-identification to a second vehicle (see [0102], [0116]-[0118] and [0127]-[0129 "The sensing vehicle may only transmit descriptions to a data center that are indicative of instances of unsafe or safe driving behaviors, or other categories of behavior, as described elsewhere herein. The sensing vehicle may only transmit descriptions that may seem relevant to the other functions or applications of the vehicle monitoring system as described elsewhere herein. This may also apply to descriptions that may be transmitted to and/or shared with other vehicles in addition to or as an alternative to the descriptions transmitted to the data center."]).
Yang is silent regarding transferring the pseudo-identification in response to detecting the change in positional relationship between the first vehicle and the subject vehicle that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle.
Bletzer teaches further comprising:
constructing, by the first vehicle, a pseudo-identification for the subject vehicle (see [0007], [0036] and [0042]); and
in response to detecting the change in positional relationship between the first vehicle and the subject vehicle that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring, by the first vehicle, the pseudo-identification to a second vehicle (see Fig. 10, all; Fig. 12, "Vehicle B Composite" from vehicle B to A; [0067], [0070 "In FIG. 10, Vehicle B 1008 has been drawn at a location where it is visible to Vehicle A 1004 but cannot directly see Vehicle D 1002 hidden by the truck."] and [0072 "In FIG. 12 the Composite view built up by Vehicle B 1008 will include Vehicle D 1002 by virtue of data received from Vehicle C and this data is shared with Vehicle A—so Vehicle D 1002 is no longer hidden from Vehicle A 1004."]; Vehicle A corresponds to the claimed "second detecting entity").
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process of Yang to include instructions for transferring the pseudo-identification to a second vehicle in response to a change in positional relationship between the first vehicle and the subject vehicle, as taught by Bletzer, in order to enable the second detecting entity to “see through” an obstruction on the road.
Regarding Claim 17
Modified Yang teaches the computer-implemented method of claim 16 (as discussed above in claim 16),
Yang further teaches wherein the pseudo-identification comprises one or more hash values corresponding to at least one of the following:
vehicle type (see [0072] and [0129 "The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity ... information about the vehicle performing the behavior (e.g., vehicle identifier such as license plate, color of vehicle, make of vehicle, mode of vehicle, vehicle brand, vehicle type)."]);
vehicle color (see [0072] and [0129 "The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity ... information about the vehicle performing the behavior (e.g., vehicle identifier such as license plate, color of vehicle, make of vehicle, mode of vehicle, vehicle brand, vehicle type)."]); and
location of the subject vehicle within a road section (see [0072] and [0129 "The descriptions may be stored as text or in any other format. The descriptions may include any level of specificity. For examples they may include category of behavior (e.g., speeding, running red light, unsafe merge, unsafe lane change, not stopping for stop sign, not yielding to pedestrians, etc.), time at which the behavior occurred, location at which the behavior occurred..."]).
Regarding Claim 18
Modified Yang teaches the computer-implemented method of claim 11 (as discussed above in claim 11),
Yang further teaches further comprising:
determining, by the first vehicle, that the subject vehicle is within observable range of the second detecting entity (see Fig. 4, all; [0092 "A sensing vehicle 400 may have a detectable range 405. The detectable range may be relative to the sensing vehicle and/or an inertial reference frame. In one example, the detectable range may include areas in front of and behind the sensing vehicle. One or more of the surrounding vehicles may fall within the detectable range, such as vehicles 410, 420, 430."]-[0096], [0102], [0117]-[0118]).
Regarding Claim 19
Yang teaches a first vehicle (see all Figs; [0003]) comprising:
one or more processers including machine executable instructions in non-transitory memory (see [0004] and [0151]) to cause the first vehicle to:
collect driving behavior data associated with a subject vehicle (see all Figs.; [0003 "A sensing vehicle may comprise one or more sensors on-board the vehicle. The one or more sensors may collect behavior data about one or more surrounding vehicles within a detectable range of the sensing vehicle ... Such information may be used to generate a safe driving index for the one or more surrounding vehicles, and/or the sensing vehicle."], [0028], [0057] and [0117]-[0120]; the sensing vehicle corresponds to the claimed "first vehicle" and the surrounding vehicle(s)/target vehicle(s) corresponds to the claimed "subject vehicle");
process the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see [0003], [0028 "The behavior data of the one or more surrounding vehicles and/or the sensing vehicle may be collected and/or aggregated, and analyzed. The analyzed behavior may be used to detect safe or unsafe driving behavior by the one or more surrounding vehicles and/or the sensing vehicle. A safe driving index may be generated and associated with a vehicle identifier of a corresponding vehicle and/or driver identifier of a driver operating the corresponding vehicle."]-[0029], [0116], [0125]-[0126] and [0163]); and
transferring the processed driving behavior data to a second detecting entity (see [0102], [0116]-[0118 "The first and second sensing vehicles may share the information gathered about the target vehicle ... Alternatively or in addition, the first and second sensing vehicles may transit the information to a data center."] and [0127]-[0129]).
Yang is silent regarding transferring the processed driving behavior data in response to an event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle.
Bletzer teaches a first vehicle (see all Figs.; [0003]-[0007]) comprising:
one or more processers including machine executable instructions in non-transitory memory (see [0077]-[0078]) to cause the first vehicle to:
collect driving behavior data associated with a subject vehicle (see Fig. 12, "What vehicle B can see" from vehicle C to B; [0072]; Vehicle B corresponds to the claimed "first vehicle" and Vehicle D corresponds to the claimed "subject vehicle".); and
in response to an event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, transferring processed driving behavior data to a second detecting entity (see Fig. 10, all; Fig. 12, "Vehicle B Composite" from vehicle B to A; [0067], [0070 "In FIG. 10, Vehicle B 1008 has been drawn at a location where it is visible to Vehicle A 1004 but cannot directly see Vehicle D 1002 hidden by the truck."] and [0072 "In FIG. 12 the Composite view built up by Vehicle B 1008 will include Vehicle D 1002 by virtue of data received from Vehicle C and this data is shared with Vehicle A—so Vehicle D 1002 is no longer hidden from Vehicle A 1004."]; Vehicle A corresponds to the claimed "second detecting entity").
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the processor of Yang to include instructions for transferring the processed driving behavior data to a second detecting entity in response to an event which interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle, as taught by Bletzer, in order to enable the second detecting entity to “see through” an obstruction on the road.
Regarding Claim 20
Modified Yang teaches the first vehicle of claim 19 (as discussed above in claim 19),
Yang is silent regarding wherein the event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle comprises a change in positional relationship between the first vehicle and the subject vehicle.
Bletzer teaches wherein the event that interrupts the first vehicle from collecting additional driving behavior data associated with the subject vehicle comprises a change in positional relationship between the first vehicle and the subject vehicle (see Fig. 10, all; [0003], [0007] and [0070]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the processor of Yang to include instructions for transferring the processed driving behavior data to a second detecting entity in response to a change in positional relationship between the first vehicle and the subject vehicle, as taught by Bletzer, in order to enable the second detecting entity to “see through” an obstruction on the road.
Claims 5-6 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Yang (as modified by Bletzer) as applied to claims 1 and 11 above, and further in view of Pipe et al. (US 20210049908 A1 and Pipe hereinafter).
Regarding Claim 5
Modified Yang teaches the computer-implemented method of claim 1 (as discussed above in claim 1),
Yang is silent regarding wherein the collected driving behavior data comprises lane offset measurements for the subject vehicle.
Pipe teaches a computer-implemented method (see all Figs.; [0005]) comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see Fig. 2, step 206; [0005 "The hazard detection system includes a second sensor configured to detect second sensor data associated with a surrounding environment of the vehicle. The second sensor data includes driving patterns of one or more other vehicles."], [0022] and [0048]; the vehicle corresponds to the claimed "first detecting vehicle" and the other vehicles/surrounding vehicles corresponds to the claimed "subject vehicle"); and
processing, by the first vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see Fig. 2, steps 208-210; [0005 "The electronic control unit is configured to obtain the first sensor data and the second sensor data. The electronic control unit is configured to determine that a hazardous condition is present based on the driver behavior patterns or the driving patterns of the one or more other vehicles."]-[0006] and [0050]-[0052]);
wherein the collected driving behavior data comprises lane offset measurements for the subject vehicle (see [0068 "For example, the hazard detection system 100 may measure the lateral motion of the vehicle in front of the vehicle 102 and when the lateral motion is greater than a threshold amount, the hazard detection system 100 may determine that the vehicle in front is swerving in and out of the lane of the roadway.'] and [0090]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process of modified Yang to include instructions to measure lane offset of the subject vehicle for detecting swerving of the subject vehicle, as taught by Pipe, in order to alert a driver of the detecting vehicle of the hazardous subject vehicle.
Regarding Claim 6
Modified Yang teaches the computer-implemented method of claim 5 (as discussed above in claim 5),
Yang is silent regarding wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, swerving by the subject vehicle based on the lane offset measurements; and
determining, by the first vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely.
Pipe teaches wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, swerving by the subject vehicle based on the lane offset measurements (see [0068 "For example, the hazard detection system 100 may measure the lateral motion of the vehicle in front of the vehicle 102 and when the lateral motion is greater than a threshold amount, the hazard detection system 100 may determine that the vehicle in front is swerving in and out of the lane of the roadway."] and [0090]); and
determining, by the first vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely (see [0068 "For example, the hazard detection system 100 may measure the lateral motion of the vehicle in front of the vehicle 102 and when the lateral motion is greater than a threshold amount, the hazard detection system 100 may determine that the vehicle in front is swerving in and out of the lane of the roadway."] and [0090]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process of modified Yang to include instructions to detect swerving by the subject vehicle based on lane offset measurements and determine that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely, as taught by Pipe, in order to alert a driver of the detecting vehicle of the hazardous subject vehicle.
Regarding Claim 13
Modified Yang teaches the computer-implemented method of claim 11 (as discussed above in claim 11),
Yang is silent regarding wherein the collected driving behavior data comprises lane offset measurements for the subject vehicle.
Pipe teaches a computer-implemented method (see all Figs.; [0005]) comprising:
collecting, by a first vehicle, driving behavior data associated with a subject vehicle (see Fig. 2, step 206; [0005 "The hazard detection system includes a second sensor configured to detect second sensor data associated with a surrounding environment of the vehicle. The second sensor data includes driving patterns of one or more other vehicles."], [0022] and [0048]; the vehicle corresponds to the claimed "first detecting vehicle" and the other vehicles/surrounding vehicles corresponds to the claimed "subject vehicle"); and
processing, by a first vehicle, the collected driving behavior data to determine whether the subject vehicle is driving unsafely (see Fig. 2, steps 208-210; [0005 "The electronic control unit is configured to obtain the first sensor data and the second sensor data. The electronic control unit is configured to determine that a hazardous condition is present based on the driver behavior patterns or the driving patterns of the one or more other vehicles."]-[0006] and [0050]-[0052]);
wherein the collected driving behavior data comprises lane offset measurements for the subject vehicle (see [0068 "For example, the hazard detection system 100 may measure the lateral motion of the vehicle in front of the vehicle 102 and when the lateral motion is greater than a threshold amount, the hazard detection system 100 may determine that the vehicle in front is swerving in and out of the lane of the roadway.'] and [0090]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process of modified Yang to include instructions to measure lane offset of the subject vehicle for detecting swerving of the subject vehicle, as taught by Pipe, in order to alert a driver of the detecting vehicle of the hazardous subject vehicle.
Regarding Claim 14
Modified Yang teaches the computer-implemented method of claim 13 (as discussed above in claim 13),
Yang is silent regarding wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, swerving by the subject vehicle based on the lane offset measurements; and
determining, by the first vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely.
Pipe teaches wherein processing the collected driving behavior data to determine whether the subject vehicle is driving unsafely comprises:
detecting, by the first vehicle, swerving by the subject vehicle based on the lane offset measurements (see [0068 "For example, the hazard detection system 100 may measure the lateral motion of the vehicle in front of the vehicle 102 and when the lateral motion is greater than a threshold amount, the hazard detection system 100 may determine that the vehicle in front is swerving in and out of the lane of the roadway."] and [0090]); and
determining, by the first vehicle, that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely (see [0068 "For example, the hazard detection system 100 may measure the lateral motion of the vehicle in front of the vehicle 102 and when the lateral motion is greater than a threshold amount, the hazard detection system 100 may determine that the vehicle in front is swerving in and out of the lane of the roadway."] and [0090]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process of modified Yang to include instructions to detect swerving by the subject vehicle based on lane offset measurements and determine that the detected swerving does not satisfy a threshold swerving factor that indicates the subject vehicle is driving unsafely, as taught by Pipe, in order to alert a driver of the detecting vehicle of the hazardous subject vehicle.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TANNER LUKE CULLEN whose telephone number is (303)297-4384. The examiner can normally be reached Monday-Friday 9:00-5:00 MT.
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/TANNER L CULLEN/Examiner, Art Unit 3656 /KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656