Prosecution Insights
Last updated: July 17, 2026
Application No. 19/071,852

SYSTEMS AND METHODS FOR NAVIGATING A HOST VEHICLE ON A ROAD SEGMENT WITH OBJECTS ON THE ROAD EDGES

Non-Final OA §102
Filed
Mar 06, 2025
Priority
Mar 06, 2024 — provisional 63/561,961
Examiner
SHAAWAT, MUSSA A
Art Unit
3669
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Mobileye Vision Technologies Ltd.
OA Round
1 (Non-Final)
76%
Grant Probability
Favorable
1-2
OA Rounds
1y 7m
Est. Remaining
82%
With Interview

Examiner Intelligence

Grants 76% — above average
76%
Career Allowance Rate
689 granted / 901 resolved
+24.5% vs TC avg
Moderate +6% lift
Without
With
+5.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 12m
Avg Prosecution
20 currently pending
Career history
913
Total Applications
across all art units

Statute-Specific Performance

§101
8.3%
-31.7% vs TC avg
§103
44.2%
+4.2% vs TC avg
§102
43.2%
+3.2% vs TC avg
§112
1.0%
-39.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 901 resolved cases

Office Action

§102
CTNF 19/071,852 CTNF 80354 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-15-aia AIA Claim(s) 1-45 is/are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by He et al., US Pg. Pub. No. (2021/0365696) referred to hereinafter as He . As per claim 1, He teaches a non-transitory computer-readable medium storing instructions executable by at least one processor to perform a method for navigating a host vehicle relative to a road segment, the method comprising: receiving at least one image captured by at least one camera from an environment of the host vehicle, wherein the at least one image includes representations of at least two objects with offset edges in the environment of the host vehicle (see at least abstract, summary, Para 19, 44-49, 50, fig. 9); analyzing the at least one image to determine a free space boundary relative to the at least two objects, wherein the free space boundary represents an edge of at least one region of free space and follows a path different from a path represented by the offset edges of the at least two objects (see at least abstract, summary, Para 19, 44-49, 50, fig. 9); determining at least one navigational action based on the free space boundary (see at least abstract, summary, Para 50, fig. 9); and causing the host vehicle to implement the at least one navigational action (see at least abstract, summary, Para 19, 44, 50, fig. 9). As per claim 2, He teaches a non-transitory computer-readable medium of claim 1, wherein analyzing the at least one image to determine the free space boundary associated with at least two objects includes identifying a potential area of free space based on at least one map and determining the free space boundary relative to the at least two objects based on the potential area of free space and the at least one image (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 3, He teaches a non-transitory computer-readable medium of claim 1, wherein the at least two objects are parked vehicles (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 4, He teaches a non-transitory computer-readable medium of claim 3, wherein the parked vehicles are positioned parallel to an edge of a road segment (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 5, He teaches a e non-transitory computer-readable medium of claim 1, wherein the at least two objects are spaced apart from one another by a distance (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 6, He teaches a non-transitory computer-readable medium of claim 5, wherein the distance is less than 1 meter (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 7, He teaches a non-transitory computer-readable medium of claim 5, wherein the distance is less than 5 meters (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 8, He teaches a non-transitory computer-readable medium of claim 5, wherein the distance is less than 10 meters (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 9, He teaches a non-transitory computer-readable medium of claim 5, wherein the distance is greater than a threshold distance enabling the host vehicle to either partially or fully enter an area of free space located between the at least two objects (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 10, He teaches a non-transitory computer-readable medium of claim 9, wherein the at least one navigational action includes steering the host vehicle to either partially or fully enter the area of free space located between the at least two objects (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 11, He teaches a non-transitory computer-readable medium of claim 9, wherein the at least one navigational action includes parking the host vehicle within the area of free space located between the at least two objects (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 12, He teaches a non-transitory computer-readable medium of claim 9, wherein the at least one navigational action is determined based on the free space boundary, the distance between the at least two objects, a speed of the host vehicle, a planned angle of entry into the area of free space, or a combination thereof (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 13, He teaches a non-transitory computer-readable medium of claim 5, wherein the distance is greater than a predetermined distance at least a portion of the free space boundary corresponds to a road edge (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 14, He teaches a non-transitory computer-readable medium of claim 1, wherein the free space boundary extends along an edge of the at least two objects (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 15, He teaches a non-transitory computer-readable medium of claim 1, wherein the free space boundary is substantially parallel to an edge of a road or a curb (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 16, He teaches a non-transitory computer-readable medium of claim 1, wherein the at least one navigational action includes steering, braking, or accelerating the host vehicle (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 17, He teaches a non-transitory computer-readable medium of claim 1, wherein analyzing the at least one image to determine the free space boundary relative to the at least two objects further comprises receiving an output provided by a trained system, wherein the output includes a height estimate for a plurality of pixels in the at least one image associated with one of the at least two objects (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 18, He teaches a non-transitory computer-readable medium of claim 17, wherein analyzing the at least one image to determine the free space boundary relative to the at least two objects further comprises using the height estimate to determine the free space boundary (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 19, He teaches a non-transitory computer-readable medium of claim 17, wherein determining the at least one navigational action is further based on the height estimate (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 20, He teaches a non-transitory computer-readable medium of claim 17, wherein at least one of the at least two objects is an object overhanging a road surface of the road and the height estimate is relative to at least a portion of the object overhanging the road surface (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 21, He teaches a non-transitory computer-readable medium of claim 20, wherein the object overhanging the road surface includes at least one of a lamppost, gates, barriers, tree branches, or a traffic sign (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 22, He teaches a non-transitory computer-readable medium of claim 1, wherein the method further comprises detecting the at least two objects by: analyzing the at least one image, using an output of RADAR system, using an output of a LIDAR system, using an output of a trained system, or a combination thereof (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 23, He teaches a non-transitory computer-readable medium of claim 1, wherein the method further comprises determining whether at least one moving object is crossing the free space boundary (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 24, He teaches a non-transitory computer-readable medium of claim 23, wherein the at least one moving object is a pedestrian or a vehicle (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 25, He teaches a non-transitory computer-readable medium of claim 23, wherein determining the at least one navigational action is further based on whether the at least one moving object is crossing the free space boundary (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 26, He teaches a non-transitory computer-readable medium of claim 1, wherein the method further comprises refining the free space boundary based on a driving policy associated with the host vehicle (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 27, He teaches a non-transitory computer-readable medium of claim 1, wherein the method further comprises determining whether one or more of the at least two objects are moving (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 28, He teaches a non-transitory computer-readable medium of claim 1, wherein the at least one navigational action includes altering a planned trajectory of the host vehicle based on the free space boundary (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 29, He teaches a non-transitory computer-readable medium of claim 1, wherein the at least two objects are located on one side of the road segment (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 30, He teaches a non-transitory computer-readable medium of claim 29, wherein the at least one image further includes representations of at least two additional objects with offset edges in the environment of the host vehicle and located on another side of the road segment (see at least abstract, summary, Para 19, 44-49, 50, fig. 9), and wherein the method further comprises: analyzing the at least one image to determine an additional free space boundary relative to the at least two additional objects, wherein the additional free space boundary represents an additional edge of the at least one region of free space and follows a path different from a path represented by the offset edges of the at least two additional objects (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claim 31, He teaches a non-transitory computer-readable medium of claim 30, wherein determining the at least one navigational action is further based on the additional free space boundary (see at least abstract, summary, Para 19, 44-49, 50, fig. 9). As per claims 32-45, the limitations of claims 32-45 are similar to the limitations of claims 1-31, therefore they are rejected based on the same rationale. Conclusion Please refer to from 892 for cited references. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUSSA A SHAAWAT whose telephone number is (313)446-6592. The examiner can normally be reached Monday-Friday 9am-5pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin Piateski can be reached at 571-270-7429. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MUSSA A SHAAWAT/Primary Examiner, Art Unit 3669 Application/Control Number: 19/071,852 Page 2 Art Unit: 3669 Application/Control Number: 19/071,852 Page 3 Art Unit: 3669 Application/Control Number: 19/071,852 Page 4 Art Unit: 3669 Application/Control Number: 19/071,852 Page 5 Art Unit: 3669 Application/Control Number: 19/071,852 Page 6 Art Unit: 3669 Application/Control Number: 19/071,852 Page 7 Art Unit: 3669 Application/Control Number: 19/071,852 Page 8 Art Unit: 3669
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Prosecution Timeline

Mar 06, 2025
Application Filed
Apr 15, 2026
Non-Final Rejection mailed — §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
76%
Grant Probability
82%
With Interview (+5.7%)
2y 12m (~1y 7m remaining)
Median Time to Grant
Low
PTA Risk
Based on 901 resolved cases by this examiner. Grant probability derived from career allowance rate.

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