DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office action is in response to the amendments filed on June 07, 2026. Claims 1-9 are currently pending, with Claim 2 being amended.
Response to Amendments
In response to Applicant’s amendments, filed June 07, 2026, the Examiner withdraws the previous objections to the drawings, withdraws the previous 35 U.S.C. 112 rejections, and maintains the previous 35 U.S.C. 102 and 103 rejections.
Response to Arguments
In response to Applicant’s arguments, filed June 07, 2026, regarding the teachings of “a road-segment-by-road-segment” driver assist method (see pages 7-8 of instant arguments), the Examiner is unpersuaded. Baig teaches a method for associating risk for a section of road, which includes an intersection, where the edge computing device may be associated with a defined region of the vehicle transportation network, such as a lane, a road segment, a contiguous group of road segments, an intersection, or a defined geographic region (see at least Paragraphs [0038], [0061], [0076] of Baig). A road segment includes a defined section of a roadway, including as described by Baig. Baig also teaches that each region (i.e., road segment) may include an intersection, which may be scored based on near miss incidents, and the driver-assistance system may be enabled based on the score/ risk level indicators of that intersection, to alert the driver, control vehicle actions, etc., for example the system may classify near miss candidates for an intersection on the road segment the vehicle is traveling, and assign a score indicative of the risk at that intersection, and may then cause an ADAS system to use safe mode when navigating a higher risk intersection (see at last Paragraphs [0040], [0062], [0094] of Baig). In other words, Baig teaches that an assist region is set based on the score/ risk level determined based on a frequency of near miss events at that intersection. As such, Baig, teaches the features of the claims as they are currently written. The Examiner is unpersuaded and maintains the corresponding rejections.
The remaining arguments are essentially the same as those addressed above and/or below and are unpersuasive for essentially the same reasons. Therefore, the corresponding rejections are maintained.
Claim Rejections - 35 USC § 102
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 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.
Claims 1 and 4-9 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Publication No. 2023/0054974 A1, to Baig, et al (hereinafter referred to as Baig; previously of record).
As per Claim 1, Baig discloses the features of a driver assist system (e.g. Paragraph [0059]; where the one or more vehicles may be a vehicle with no automation, with driver assist, partial automation, conditional automation, etc.) comprising:
a plurality of vehicles at which predetermined driver assist is performed (e.g. Paragraphs [0036], [0065], [0078], [0091]; Figure 5; where the system estimates driver risk levels for connected vehicles, which can receive messages within a defined broadcast range); and
a server configured to be able to communicate with the vehicles (e.g. Paragraph [0061]; Figures 2, 3; where the communication network can provide for communication between the vehicles and one or more compute devices, such as a cloud computing platform (2400) or edge computing device (2410)), wherein the server is configured to:
set an assist region for making the vehicles perform driver assist (e.g. Paragraphs [0040], [0061], [0064]; where the edge computing device (2410) may be associated with a defined region of the vehicle transportation network such as a lane, a road segment, a contiguous group of road segments, a road, an intersection, or a defined geographic region, such as a block, neighborhood, a district, etc. (i.e., an assist region) to alert a user of the risk level at the intersection) and
set as an assist road segment a road segment with a high frequency of occurrence of at least one of accidents and near misses from among the road segments of intersections in that assist region, based on predetermined information stored in the server (e.g. Paragraphs [0038], [0040], [0076]; where the vehicle transportation network (3100) may include multiple regions, wherein each region may include an intersection (3110, 3120, 3130), and the system may assign a score based on frequency or near misses at an intersection such that the driver can be aided with vehicle planning, or implementation of an ADAS system to use a safe mode when navigating a higher risk intersection); and
send information relating to a specific intersection having that assist road segment to the vehicles (e.g. Figure 5; where the risk indicator level for an intersection is sent to the connected vehicles), and the vehicles are configured to:
receive information relating to that specific intersection from the server (e.g. Paragraphs [0062], [0065]; Figure 5; where the risk indicator level for an intersection is sent to the connected vehicles); and
perform the driver assist when running on the assist road segment (e.g. Paragraphs [0062], [0094]; where the vehicle may receive intersection risk indicator levels from the cloud computing platform (2400), which may be used to alert a driver, control vehicle actions, impact driver assistance systems, and the intersection risk indicator level may be provided at an update rate to plan steering and braking actions).
As per Claim 4, Baig discloses the features of Claim 1, and Baig further discloses the features of wherein the server is configured to
set a driver assist level for each assist road segment based on a frequency of occurrence of at least one of accidents and near misses of the assist road segment (e.g. Paragraphs [0034], [0040]; where the system can determine an intersection risk level indicator based on the number of near misses, and the near miss score and driver distraction score can be combined in an exponential moving average (EMA) expression to determine intersection risk indicator scores, where each intersection risk indicator score may be associated with an intersection risk level indicator, such as high, medium, or low), and the vehicles are configured to
change a mode, control quantity, or timing of performance of the driver assist based on the driver assist level (e.g., Paragraph [0040]; where the system can provide the intersection risk indicator levels to the connected vehicles to aid driver alertness, vehicle planning, cause the ADAS systems to use safe mode when navigating a higher risk intersection).
As per Claim 5, Baig discloses the features of Claim 1, and Baig further discloses the features of wherein the driver assist is driver assist performing at least one of reporting to a driver of a vehicle, brake assist, and automatic braking in accordance with need when running on the assist road segment (e.g. Paragraphs [0062], [0094]; where the vehicle may receive intersection risk indicator levels from the cloud computing platform (2400), which may be used to alert a driver, control vehicle actions, impact driver assistance systems, and the intersection risk indicator level may be provided at an update rate to plan steering and braking actions).
As per Claim 6, Baig discloses the features of Claim 1, and Baig further discloses the features of wherein
the server is configured to collect predetermined information from the vehicles (e.g. Paragraphs [0032], [0034]; Figure 5; where the system receives, obtains, or collects intersection data from vehicles), and
the predetermined information includes at least one of data enabling judgment of whether a collision has occurred at the vehicles and data enabling judgment of whether a collision avoiding operation has been performed for avoiding a collision at the vehicles (e.g. Paragraphs [0034]; where the system determines an intersection risk indicator by assessing the intersection safety using the driver distraction/ attention score with the penalty for a detected near miss or crash).
As per Claim 7, Baig discloses the features of Claim 6, and Baig further discloses the features of wherein the predetermined information includes data for a driver of a vehicle to be forewarned of danger and enabling judgment of whether a danger forewarning operation has been performed by the driver for preventing that in advance (e.g. Paragraph [0016]; where the system determines a driver risk score for each connected vehicle, for each intersection, and for each of the one or more connected vehicles, provides intersection risk indicator levels to facilitate control decisions by each of the one or more connected vehicles (i.e., a driver is forewarned)).
As per Claim 8, Baig discloses the features of a driver assist server (e.g. Paragraph [0061]; Figures 2, 3; where the communication network can provide for communication between the vehicles and on or more compute devices, such as a cloud computing platform (2400) or edge computing device (2410)) comprising:
a communication part configured to be able to communicate with vehicles (e.g. Paragraph [0061]; Figures 2, 3; where the communication network can provide for communication between the vehicles and one or more compute devices, such as a cloud computing platform (2400) or edge computing device (2410));
a storage part for storing information; and a processing part (e.g. Paragraphs [0082]-[0083]; where the compute node can include an intersection database, memory or storage; and where the compute node can be the cloud computing platform (2400)), wherein the processing part is configured to:
set an assist region for making the vehicles perform predetermined driver assist based on predetermined information stored in the storage part assist (e.g. Paragraphs [0040], [0061], [0064]; where the edge computing device (2410) may be associated with a defined region of the vehicle transportation network such as a lane, a road segment, a contiguous group of road segments, a road, an intersection, or a defined geographic region, such as a block, neighborhood, a district, etc. (i.e., an assist region) to alert a user of the risk level at the intersection);
set, as an assist road segment where the driver assist is performed, a road segment with a high frequency of occurrence of at least one of accidents and near misses from among the road segments of intersections in that assist region based on predetermined information server (e.g. Paragraphs [0038], [0040], [0076]; where the vehicle transportation network (3100) may include multiple regions, wherein each region may include an intersection (3110, 3120, 3130), and the system may assign a score based on frequency or near misses at an intersection such that the driver can be aided with vehicle planning, or implementation of an ADAS system to use a safe mode when navigating a higher risk intersection); and
send information relating to a specific intersection having that assist road segment to the vehicles (e.g. Figure 5; where the risk indicator level for an intersection is sent to the connected vehicles).
As per Claim 9, Baig discloses the features of a driver assist method of vehicles (e.g. Paragraph [0059]; where the one or more vehicles may be a vehicle with no automation, with driver assist, partial automation, conditional automation, etc.), the driver assist method
setting an assist region for making the vehicles perform predetermined driver assist (e.g. Paragraphs [0040], [0061], [0064]; where the edge computing device (2410) may be associated with a defined region of the vehicle transportation network such as a lane, a road segment, a contiguous group of road segments, a road, an intersection, or a defined geographic region, such as a block, neighborhood, a district, etc. (i.e., an assist region) to alert a user of the risk level at the intersection) based on
predetermined information stored in a server (e.g. Paragraph [0061]; Figures 2, 3; where the communication network can provide for communication between the vehicles and on or more compute devices, such as a cloud computing platform (2400) or edge computing device (2410)),
setting, as an assist road segment, a road segment with a high frequency of occurrence of at least one of accidents and near misses from among the road segments of intersections in that assist region based on predetermined information (e.g. Paragraphs [0038], [0040], [0076]; where the vehicle transportation network (3100) may include multiple regions, wherein each region may include an intersection (3110, 3120, 3130), and the system may assign a score based on frequency or near misses at an intersection such that the driver can be aided with vehicle planning, or implementation of an ADAS system to use a safe mode when navigating a higher risk intersection), and
making the vehicles perform that driver assist when the vehicles are running on that assist road segment (e.g. Paragraphs [0062], [0094]; where the vehicle may receive intersection risk indicator levels from the cloud computing platform (2400), which may be used to alert a driver, control vehicle actions, impact driver assistance systems, and the intersection risk indicator level may be provided at an update rate to plan steering and braking actions).
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 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over by U.S. Patent Publication No. 2023/0054974 A1, to Baig, et al (hereinafter referred to as Baig; previously of record), in view of U.S. Patent Publication No. 2025/0100548 A1, to Kobashi, et al (hereinafter referred to as Kobashi; previously of record).
As per Claim 2, Baig discloses every feature of Claim 1, but Baig fails to disclose every feature of wherein the server is configured to, in response to (i) an intersecting road segment intersecting the assist riad segment at the specific intersection being present, and (ii) the intersecting road segment being not set as the assist road segment, judge whether to set the intersecting road segment as a quasi assist road segment based on a visibility of the intersecting road segment from the assist road segment and the vehicles are configured to perform the driver assist when running in the quasi assist road segment.
However, Kobashi, in a similar field of endeavor, teaches a method for collision avoidance using visibility grids at an intersection, where the intersection operational environment monitor may correlate, associate, or otherwise process the operation environment information to identify, track, or predict actions or one or more vehicles at an intersection, based on visibility factors and near-miss data on the road segment; and the vehicle may determine a first (host vehicle) is approaching the intersection via a first road, and that a second vehicle is approaching the intersection by traversing a second road, to determine a probability of an accident between the two vehicles at the intersection, and the host vehicle can reason about what the sensors of the vehicle itself cannot see to prevent getting in an accident, and an alert may be provided to each vehicle or pedestrians associated with the intersection (i.e., an assist road segment for the host vehicle, and a quasi-assist segment including providing alerts for each vehicle or pedestrian’s path intersecting the host vehicle) (e.g. Paragraphs [0034], [0102], [0127], [0135], [0190], [0215]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the Applicant’s invention, with a reasonable expectation for success, to modify the intersection risk indicator determination system of Baig, with the feature of determining other vehicles or objects approaching the same intersection and providing assistance in the system of Kobashi, in order to avoid an accident from happening when visibility is restricted for at least one agent approaching the intersection (see at least Paragraph [0215[ of Kobashi).
As per Claim 3, Baig discloses every feature of Claim 1, but Baig fails to disclose every feature of wherein the server is configured to: set as an assist road segment candidate a road segment with a high frequency of occurrence of at least one of accidents and near misses from among the road segments of intersections in a region not set in the assist region and adjoining the assist region: and
send information relating to a specific intersection candidate having that assist road segment candidate to the vehicles, and the vehicles are configured to: receive information relating to that specific intersection candidate from the server; and perform driver assist in accordance with an amount of traffic in the surroundings of the specific intersection candidate when running on the assist road segment candidate.
However, Kobashi, in a similar field of endeavor, teaches a method for collision avoidance using visibility grids at an intersection, where the intersection operational environment monitor may correlate, associate, or otherwise process the operation environment information to identify, track, or predict actions or one or more vehicles at an intersection, based on visibility factors and near-miss data on the road segment; and the vehicle may determine a first (host vehicle) is approaching the intersection via a first road, and that a second vehicle is approaching the intersection by traversing a second road, to determine a probability of an accident between the two vehicles at the intersection, and the host vehicle can reason about what the sensors of the vehicle itself cannot see to prevent getting in an accident, and an alert may be provided to each vehicle or pedestrians associated with the intersection (e.g. Paragraphs [0034], [0102], [0127], [0135], [0190], [0215]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the Applicant’s invention, with a reasonable expectation for success, to modify the intersection risk indicator determination system of Baig, with the feature of determining other vehicles or objects approaching the same intersection and providing assistance in the system of Kobashi, in order to avoid an accident from happening when visibility is restricted for at least one agent approaching the intersection (see at least Paragraph [0215] of Kobashi).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection 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 nonprovisional extension fee (37 CFR 1.17(a)) 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MERRITT LEVY whose telephone number is (571)270-5595. The examiner can normally be reached Mon-Fri 0630-1600.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abby Flynn can be reached at (571) 272-9855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MERRITT LEVY/Examiner, Art Unit 3663
/ABBY J FLYNN/Supervisory Patent Examiner, Art Unit 3663
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