Prosecution Insights
Last updated: April 19, 2026
Application No. 18/626,701

SPARSE MAP FOR AUTONOMOUS VEHICLE NAVIGATION

Final Rejection §103
Filed
Apr 04, 2024
Examiner
CHEN, SHELLEY
Art Unit
3665
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Mobileye Vision Technologies Ltd.
OA Round
2 (Final)
66%
Grant Probability
Favorable
3-4
OA Rounds
3y 2m
To Grant
87%
With Interview

Examiner Intelligence

Grants 66% — above average
66%
Career Allow Rate
349 granted / 528 resolved
+14.1% vs TC avg
Strong +21% interview lift
Without
With
+21.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
23 currently pending
Career history
551
Total Applications
across all art units

Statute-Specific Performance

§101
5.2%
-34.8% vs TC avg
§103
64.8%
+24.8% vs TC avg
§102
15.9%
-24.1% vs TC avg
§112
11.8%
-28.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 528 resolved cases

Office Action

§103
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 . Response to Arguments 1. Applicant's arguments filed 16 January 2026 have been fully considered but are not persuasive. The new limitations are disclosed by at least Fairfield as explained in the rejection below. 2. Applicant argues on page 7 that Dorum’s “points where the polynomial functions piece together” do not represent landmarks. This argument is not found persuasive. The “points where the polynomial functions piece together” would be visible from a distance and therefore qualify as landmarks. Alternatively, the third reference Fairfield also discloses landmarks more clearly (col 5: 4-21, etc). 3. Applicant argues on page 7-9 that a POSITA would not be motivated to combine the road map database disclosed in Bolger with the map database disclosed in Dorum, nor would this result in the claimed sparse map, because Bolger's road map database is entirely different from the form of map database disclosed in Dorum. This argument is not found persuasive. Bolger was used only to teach that a sparse map could have a data density of no more than 1 megabyte per kilometer. The map database of Bolger was not bodily incorporated into the invention of Dorum. The test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981). 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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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. 5. Claims 29-45 and 67-68 rejected under 35 U.S.C. 103 as being unpatentable over Dorum et al. (U.S. Patent Application Publication # 2014/244125) in view of Bolger (U.S. Patent Application Publication # US 5,471,393), and further in view of Fairfield et al. (U.S. Patent Application Publication # US 9,476,970). Regarding claims 29 and 45, Dorum discloses a system for navigating a vehicle (P18), the system comprising: a non-transitory computer-readable medium including a sparse map (P4: ADAS features may also use digital map data) for autonomous navigation of the vehicle (P18: The following embodiments incorporate previously recorded probe data into an advanced driver assistance system (ADAS) to create an enhanced model for determining driver behavior from the probe data. The resulting enhanced model may be used for safety applications such as autonomous vehicle control) along a road segment (P20: The probe data may include information describe how people accelerate, decelerate, brake, or perform other actions while navigation a road segment or a particular curve on the road), the sparse map comprising: a polynomial representation of a target trajectory for the autonomous vehicle along the road segment (P39: The database 123 may be a map database or a geographic database configured to store path curves as splines [...] or piecewise polynomials, to represent navigable paths. The preceding examples may be referred to as polycurves. FIG. 2A illustrates an example polycurve 161 modeling road link segments 162); and a plurality of predetermined landmarks associated with the road segment (P42: a spline curve is a composite curve formed with piecewise polynomial functions representing the curve section. The points where the polynomial functions piece together are referred to as knots, and the points on the line segments that define the shape of the spline are control points), wherein the sparse map has a data density of no more than 1 megabyte per kilometer (implicit); and at least one processor configured to execute data included in the sparse map for providing autonomous navigation of the vehicle along the road segment (P18), wherein providing autonomous navigation of the vehicle includes determining at least one position of the vehicle (P36, 69). Dorum does not explicitly disclose that the sparse map has a data density of no more than 1 megabyte per kilometer; or determining the position of the vehicle relative to the target trajectory based on at least one predetermined landmark of the plurality of predetermined landmarks. In the same field of endeavor, Bolger discloses that the sparse map has a data density of no more than 1 megabyte per kilometer (col 4: 34-36: "The preferred embodiment of this invention requires between 8 to 12 kilobytes of storage space per square kilometer of typical city streets"). It would have been obvious before the effective filing date of the claimed invention to modify Dorum to use a data density of no more than 1 megabyte per kilometer, as taught by Bolger, in order to reduce data transmission, storage, and computational load requirements, with predictable results. In the same field of endeavor, Fairfield discloses determining the position of the vehicle relative to the target trajectory based on at least one predetermined landmark of the plurality of predetermined landmarks (col 5: 4-21: “vehicle 101 uses images obtained from the vehicle's camera to determine the vehicle's current position relative to a desired path of travel... Objects may include anything within the vehicle's surroundings, such as buildings, trees, curbs, sidewalks, lane lines, telephone poles, billboards, animals, people, etc.”). It would have been obvious before the effective filing date of the claimed invention to modify Dorum to determine the position of the vehicle relative to the target trajectory based on at least one predetermined landmark, as taught by Fairfield, in order to estimate the position of the vehicle to a greater accuracy and/or reliability than solely using GPS, by enabling position finding based on a camera image as a backup or additional method for position finding, with predictable results. Regarding claim 30-32 and 67-68, Dorum in view of Bolger and Fairfied further discloses that the at least one predetermined landmark includes at least a first predetermined landmark and a second predetermined landmark, and wherein determining the at least one position of the vehicle relative to the target trajectory includes: determining a first position of the vehicle relative to the target trajectory based on first predetermined landmark; and determining a second position of the vehicle relative to the target trajectory based on second predetermined landmark (Fairfield col 5: 4-21). Regarding claim 33, Dorum in view of Bolger further discloses that the plurality of predetermined landmarks are spaced apart by a distance specified such that a distance between the estimated position of the vehicle relative to the target trajectory and an actual position of the vehicle relative to the target trajectory is within a predetermined distance (implicit from P42, Bolger col 4: 16-29, etc; also well known in the art, the Examiner hereby takes Official Notice of this fact). Regarding claim 34, Dorum in view of Bolger further discloses that the plurality of predetermined landmarks include a traffic sign represented in the sparse map by no more than 50 bytes of data (implicit, and well known in the art; the Examiner hereby takes Official Notice of this fact). Regarding claim 35, Dorum in view of Bolger further discloses that the plurality of predetermined landmarks include a directional sign represented in the sparse map by no more than 50 bytes of data (implicit, and well known in the art; the Examiner hereby takes Official Notice of this fact). Regarding claim 36, Dorum in view of Bolger further discloses that the plurality of predetermined landmarks include a general purpose sign represented in the sparse map by no more than 100 bytes of data (implicit, and well known in the art; the Examiner hereby takes Official Notice of this fact). Regarding claim 37, Dorum in view of Bolger further discloses that the plurality of predetermined landmarks include a generally rectangular object represented in the sparse map by no more than 100 bytes of data (implicit, and well known in the art; the Examiner hereby takes Official Notice of this fact). Regarding claim 38, Dorum in view of Bolger further discloses that the representation of the generally rectangular object in the sparse map includes a condensed image signature associated with the generally rectangular object (well known in the art; the Examiner hereby takes Official Notice of this fact). Regarding claim 39, Dorum in view of Bolger further discloses that the plurality of predetermined landmarks are represented in the sparse map by parameters indicative of at least one of a landmark size, a distance to a previous landmark, a landmark type, and a landmark position (P42, etc). Regarding claim 40, Dorum in view of Bolger further discloses that the sparse map has a data density of no more than 100 kilobytes per kilometer (Bolger col 4: 34-36: "The preferred embodiment of this invention requires between 8 to 12 kilobytes of storage space per square kilometer of typical city streets"). Regarding claim 41, Dorum in view of Bolger further discloses that the sparse map has a data density of no more than 10 kilobytes per kilometer (Bolger col 4: 34-36: "The preferred embodiment of this invention requires between 8 to 12 kilobytes of storage space per square kilometer of typical city streets"). Regarding claim 42, Dorum in view of Bolger further discloses that the plurality of predetermined landmarks appear in the sparse map at a rate that is above a rate sufficient to maintain a longitudinal position determination accuracy within 1 meter (implicit from P42, Bolger col 4: 16-29, etc; also well known in the art, the Examiner hereby takes Official Notice of this fact). Regarding claim 43, Dorum in view of Bolger further discloses that the polynomial representation is a three-dimensional polynomial representation (P27: For example, a polycurve describing a 30 path curve (e.g. road center, lane center or average vehicle path per lane) has 3 dimensions (x, y, z). From these dimensions curvature may be computed through taking the derivative (e.g., the first derivative and/or the second derivative) of at least a portion of the polycurve. Equation 1 provides an example curvature (k) calculation using Cartesian coordinates (x, y, z)). Regarding claim 44, Dorum in view of Bolger further discloses that the polynomial representation of the target trajectory is determined based on two or more reconstructed trajectories of prior traversals of vehicles along the road segment (P32-33: the server 125 receives at least one set of probe data from one or more vehicles. The server 125 may record the type of vehicle, the environmental conditions, or other attributes along with the probe data. The probe data may include position only (e.g., generated from a global positioning system (GPS)). Alternatively, the probe data may be more robust and comprise speed data from the speedometer of the vehicle, braking data from the electronic braking system of the vehicle, or any data available from the vehicle monitoring system (e.g., CAN bus or 080). The server 125 is configured to modify a spline curve based on the at least one set of probe data). 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 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 date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHELLEY CHEN whose telephone number is (571)270-1330. The examiner can normally be reached Mondays through Fridays. Examiner interviews are available via telephone. 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 Bishop can be reached at (571) 270-3713. 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. /Shelley Chen/ Patent Examiner Art Unit 3665 February 23, 2026
Read full office action

Prosecution Timeline

Apr 04, 2024
Application Filed
Oct 17, 2025
Non-Final Rejection — §103
Jan 16, 2026
Response Filed
Feb 23, 2026
Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12576862
SYSTEM FOR DETECTING A FAULTY ECU ON A VEHICLE NETWORK AND A METHOD THEREOF
2y 5m to grant Granted Mar 17, 2026
Patent 12568872
SYSTEMS AND METHODS FOR EQUIPMENT CONTROL USING LARGE LANGUAGE MODEL-BASED ARTIFICIAL INTELLIGENCE
2y 5m to grant Granted Mar 10, 2026
Patent 12570274
INFRASTRUCTURE-BASED COLLABORATIVE AUTOMATED PARKING AND LOCATION MANAGEMENT
2y 5m to grant Granted Mar 10, 2026
Patent 12570272
METHOD FOR CONTROLLING AT LEAST ONE DEVICE OF A MOTOR VEHICLE, AND ASSOCIATED MOTOR VEHICLE
2y 5m to grant Granted Mar 10, 2026
Patent 12557722
Agricultural Lane Following
2y 5m to grant Granted Feb 24, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
66%
Grant Probability
87%
With Interview (+21.0%)
3y 2m
Median Time to Grant
Moderate
PTA Risk
Based on 528 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month