DETAILED ACTION
This action is in response to the remarks filed on January 26th, 2026. Claims 1-2, 4-5, 8-13, 15-16, and 19-20 are pending and have been examined.
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
Applicant’s arguments with respect to claims 1, 12, and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 1, 12, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Whitehead (US20210129849) in view of Kumano (US20210197828), Halt (US6385533), Zhang (US8194927), Straus (DE102018114808), and Li (“A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios”).
In regards to claim 1, Whitehead teaches a system comprising: a memory configured to store computer-executable instructions; and at least one processor configured to execute the computer-executable instructions (Whitehead Paragraph [0026] “It will be appreciated that the term “controller” as used herein refers to any suitable control device or set of multiple control devices that is/are configured to perform at least a portion of the techniques of the present disclosure. Non-limiting examples include an application-specific integrated circuit (ASIC), one or more processors and a non-transitory memory having instructions stored thereon that, when executed by the one or more processors, cause the controller to perform a set of operations corresponding to at least a portion of the techniques of the present disclosure.”) to: obtain lane marking data using one or more sensors (Whitehead Paragraph [0018] “In one exemplary embodiment, the front-facing camera 124 is an intelligent camera that is configured to detect lane identifiers from captured raw images and output lane identifier information to the controller 116 or the front-facing camera 124 is otherwise integrated as part of the controller 116”); in response to determining that the obtained lane marking data is associated with a particular road type (Whitehead Paragraph [0015] “This conventional feedback-based solution is reactive to the scenario and hence is prone to delays, particularly on roads having a hilly topology, which could be undesirable to a driver of the vehicle.” Examiner note: This excerpt shows that this system would be initiated based on a user being on a certain road type (road with hilly topology)), determine (i) a first lane width dataset based on a first subset of the obtained lane marking data that is associated with one or more widths of a first category, and (ii) a second lane width dataset based on a second subset of the obtained lane marking data that is associated with one or more widths of a second category (Whitehead Figure 4A; Paragraph [0021] “A width extractor 304 extracts lane width information (e.g., for a plurality of different points along the lane) from the lane identifier information, taking into account a relative position of the vehicle 100 with respect to the lane(s) of the road.”; Paragraph [0022] “In this example technique, the width of the lane at different distances and elevations within the image is extracted. This extraction could be limited, for example, to a subset of the image height (V.sub.top-V.sub.bottom) to reduce processing complexity, such as for cases of resolution constraints. As shown, there is a virtual center or dividing lane line (Lc) placed in the immediate center between the outer lane lines. The purpose of this virtual center lane line L.sub.c is to distinguish the difference between the center of the two outer lane lines and the actual path of the vehicle in that lane (P′). …At some vertical level in the image (⊖.sub.v), image pixels are counted horizontally from a horizontal location along P′ (e.g., from a point P), which represents a center of the vehicle with reference to the lane to either of the lane/road marking boundaries or extremes. This is then related to the angular position of the lane marking with reference to the camera (⊖.sub.a, ⊖.sub.b).…These pixel counts or calculations are then repeated for other vertical levels within the vertical range to create sets (⊖.sub.an, ⊖.sub.bn), where n represents the varying vertical levels. These sets are also referred to herein as lane width information.” Examiner note: This excerpt shows determining a first lane width dataset (⊖.sub.an) and a second lane width dataset (⊖.sub.bn) based on the obtained lane identifier information); estimate a probable lane width as a function Whitehead Figure 4B; Paragraph [0023] “For each vertical level n, the angular positions ⊖.sub.a, ⊖.sub.b, first and second width portions (W.sub.1, W.sub.2) of the full width W are as follows: W.sub.1=d*tan(⊖.sub.a) and W.sub.2=d*tan(⊖.sub.b).” Examiner note: This excerpt shows calculating a width W (as seen in figure 4B W = W.sub.1 + W.sub.2) based on the lane width dataset (⊖.sub.a and ⊖.sub.b)).
Whitehead does not teach identifying, based on map data representative of one or more map links or topologies, at least one map link or topology associated with the obtained lane marking data; based on the identified map link or topology, determining that the obtained lane marking data is associated with a particular road type corresponding to a multi-digitized road with a single lane for each direction of travel; performing a location categorization to determine that a location of the obtained marking data exhibits a likelihood of absent or degraded lane markings; in response to determining that the location exhibits the likelihood of absent or degraded lane markings, determining lane widths; and estimating a probable lane width as a function that comprises a weighted median associated with the first lane width dataset and the second lane width dataset, wherein a weight of each of the first lane width dataset and the second lane width dataset is associated with a length of a corresponding lane marking data.
However, Kumano teaches identifying, based on map data representative of one or more map links or topologies, at least one map link or topology associated with the obtained lane marking data; based on the identified map link or topology, determine that the obtained lane marking data is associated with a particular road type Kumano Paragraph [0027] “The communication terminal 3 communicates with a server that distributes map data via a public communication network, and receives the map data distributed from this server. The map data is link data, node data, or the like. The link data includes various pieces of data such as a link ID identifying a link, a link length indicating a length of the link, a link azimuth, a link travel time, link shape information (hereinafter, link shape), node coordinates (latitude/longitude) of a start point and an end point of the link, and road attributes. … The road attributes include a road name, a road type, a road width, lane number information indicating the number of lanes, a speed regulation value, and the like.” Examiner note: In this excerpt, the map link or topology (map data) is received from the server. And the road type is determined from the road attributes.).
Kumano is considered to be analogous to the claimed invention because they are in the same field of identifying road markings. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead to include the teachings of Kumano, to provide the advantage of allowing the system to estimate road markings, even when they are missing or unrecognizable (Kumano Paragraph [0018] “Accordingly, in the comparative example, when there is no white line or the white line type cannot be recognized, it may be difficult to accurately estimate the traveling lane of the subject vehicle.”).
Furthermore, Halt teaches determining that the obtained lane marking data is associated with a particular road type corresponding to a multi-digitized road with a single lane for each direction of travel (Halt Column 5 Line 63 “The data collection system 225 is a tool that facilitates the collection of information about geographic features, such as roads. In particular, the data collection system 225 facilitates the collection of those kinds of information which are preferably obtained by direct observation by a researcher. The data collection system 225 may be used to obtain the following kinds of information about roads:”; Column 6 Lines 5 and 14 “3. lane category (e.g., number of lanes), or alternatively, exact number of lanes (e.g., 1, 2, 4, etc.),.. 7. whether a road is multi-digitized (i.e., whether the geometry of the lanes in one direction are separately represented from the geometry of the lanes in the other direction),…” Examiner note: This reference teaches that a multi digitized road, with two lanes of travel, could be identified as a road type.).
Halt is considered to be analogous to the claimed invention because they are in the same field of identifying road markings. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano to include the teachings of Halt, to provide the advantage of a system that can identify road markings in an area, and use that data as a starter for the surrounding areas (Halt Column 11 Line 19 “The dynamic profiling feature of the data collection system derives from the recognition that road attributes tend to be location-consistent. When a database researcher is collecting data in a particular administrative area (e.g., municipality, town, city, etc.), it is highly desirable to eliminate repeated entry of the same data elements. Given the "knowledge" gained from the sensors on the car coupled with a dynamic profiling tool, most of this work can be eliminated.”)
Furthermore, Zhang teaches wherein the function comprises a weighted median associated with the first lane width dataset and the second lane width dataset (Column 6 Line 60 “In step 60, a weighting mean of data points of the candidate lane marker region is calculated.” Examiner note: Here, a weighted mean and median are seen as analogous, as both are statistical methods of calculating the middle most data point.).
Zhang is considered to be analogous to the claimed invention because they are in the same field of identifying road lane markings. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano and Halt to include the teaching of a weighted mean of Zhang, to provide the advantage of a system that can detect road markings without the use of a vision based system (Zhang Column 1 Line 8 “Lane marker detection is used either to alert a vehicle driver of the presence of road lane markers in the vehicle driving path, or to provide the feasible driving area constraint for route planning in autonomous driving. The issue is that most systems utilize a vision-based system such as a camera to analyze the captured image. Such vision-based systems are susceptible to incorrectly distinguishing lane markers due to the lighting conditions, shadows from trees and buildings, or poorly painted or warn lane markers.”).
Straus teaches wherein a weight of each of the first lane width dataset and the second lane width dataset is associated with a respective length of a corresponding lane marking represented by the lane marking data. (Straus Page 9, Line 3 “For example, the detectable or detected length of the lane markings can be used to form the second weight.”)
Straus is considered to be analogous to the claimed invention because it is in the same field of digitally identifying roads. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, and Zhang to include the teaching of Straus to weight road markings that are longer (and therefore clearer), providing the advantage of having more accurate data being weighted higher (Straus “In this way, particularly reliable and / or precise track data can be assigned a higher weight than other track data.”)
Lastly, Li teaches performing a location categorization to determine that a location of the obtained marking data exhibits a likelihood of absent or degraded lane markings (Li Section IV “Our system uses a simple classification method based on the detected optimal drivable lines. Based on the minimum width of the optimal drivable region, we classify the current road into two types (A and B in Fig. 6). If min(width1, width2, width3) > widthth, we detect lanes in the region [see Fig. 6(b)–(d)]; otherwise, we assume that there are no lane markings on the road [see Fig. 6(a)].” Examiner note: This section shows that when certain conditions are not met, it is assumed that lane markings are not present (or absent).); and in response to determining that the location exhibits the likelihood of absent or degraded lane markings, determining lane widths (Li Figure 6(a) Examiner note: Figure 6a corresponds to the scenario when it is assumed there are no lane markings on the road).
Li is considered to be analogous to the claimed invention because it is in the same field of lane detection. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, Zhang, and Straus to include the teachings of Li to determine when road markings are available, providing the advantage of a system that works on roads with clear lane markings (structured roads) and roads without (unstructured roads). (Li Section IV “Using this optimal drivable region, we ensure safe driving of the autonomous vehicle on either structured or unstructured roads. To follow lanes on structured roads, our vehicle first determines whether lane detection is necessary in the current road scenario.”)
In regards to claim 12, Whitehead in view of Kumano, Halt, Zhang, Straus, and Li renders obvious the claim limitations as in the consideration of claim 1.
In regards to claim 20, Whitehead in view of Kumano, Halt, Zhang, Straus, and Li teaches a computer program product comprising a non-transitory computer-readable medium having stored thereon computer-executable instructions which when executed by at least one processor, cause the at least one processor to carry out operations for determining lane width data of claim 1 (Kumano Paragraph [0034] “The automatic driving ECU 2 is mainly configured by a processor, a volatile memory, a non-transitory tangible storage medium such as a nonvolatile memory, an I/O, and a microcomputer including buses for connecting those components, and executes various processes related to the automatic driving by executing control programs stored in the non-volatile memory. The various processes related to the automatic driving include a process (hereinafter, traveling lane estimation process) of estimating the traveling lane of the subject vehicle. The memory mentioned in the above is a non-transitory tangible storage medium that non-temporarily stores computer-readable program and data.”) and renders obvious the remaining claim limitations as in the consideration of claims 1 and 12.
Claims 2 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Whitehead in view of Kumano, Halt, Zhang, Straus, and Li, and further in view of Franke (Lane Recognition on Country Roads).
In regards to claim 2, Whitehead in view of Kumano, Halt, Zhang, Straus, and Li teaches the system of claim 1, but fails to teach wherein the particular road type corresponds to a local road.
However, Franke teaches wherein the particular road type corresponds to a local road (Franke Figures 9 and 10; Page 5, Column 1, Sections A,B,C; Examiner note: Country roads are analogous to local roads as they are both examples of two lane roads with one lane in each direction. Country roads are also known to be badly marked or unmarked (Franke Page 1, Column 1 “unmarked or badly marked country roads”) similar to the local roads of the present disclosure.)
Franke is considered to be analogous to the claimed invention because they are in the same field of identifying road markings. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, Zhang, Straus, and Li to include the teachings of Franke, to provide the advantage of having a system that works not only on “well marked highways and secondary roads”, but on “unmarked or badly marked country roads” (Franke, Figures 9 and 10; Page 1 Column 1). This also allows the system to exploit any and all available markings.
In regards to claim 13, Whitehead in view of Kumano, Halt, Zhang, Straus, Li, and Franke renders obvious the claim limitations as in the consideration of claims 2 and 12 above.
Claims 4 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Whitehead in view of Kumano, Halt, Zhang, Straus, and Li, and further in view of Oishi (US20200312126).
In regards to claim 4, Whitehead in view of Kumano, Halt, Zhang, Straus, and Li teaches the system of claim 1, but fails to teach wherein the first category corresponds to widths that are greater than a threshold width, and wherein the second category corresponds to widths that are at or lower than the threshold width.
However, Oishi teaches wherein the first category corresponds to widths that are greater than a threshold width (Oishi Paragraph [0029] “the road 100 whose width is the certain threshold or more is assumed to be the second road.”), and wherein the second category corresponds to widths that are at or lower than the threshold width. (Oishi Paragraph [0029] “the road 100 whose width is less than a certain threshold is assumed to be the first road”)
Oishi is considered to be analogous to the claimed invention because they are in the same field of using image processing techniques to identifying roads. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, Zhang, Straus, and Li to include the teaching of sorting roads into categories of Oishi, to provide the advantage of using the correct data and equations when dealing with any road type (Oishi Paragraph [006] “The present invention was made considering such a problem, and has an object of providing a road management device that can appropriately select information to be used when performing analysis of a road based on information acquired by a camera or a sensor installed in a vehicle.)
In regards to claim 15, Whitehead in view of Kumano, Halt, Zhang, Straus, Li, and Oishi renders obvious the claim limitations as in the consideration of claims 4 and 12 above.
Claims 5 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Whitehead in view of Kumano, Halt, Zhang, Straus, and Li, and further in view of Horinaga (US20210117698).
In regards to claim 5, Whitehead in view of Kumano, Halt, Zhang, Straus, and Li teaches the system of claim 1, but fails to teach wherein the first category corresponds to lane markings that respectively define distances between road edges and wherein the second category corresponds to lane markings that respectively define distances between a road edge and a road centerline.
However, Horinaga teaches wherein the first category corresponds to lane markings that respectively define distances between road edges (Horinaga Figure 3, P5 and P7) and wherein the second category corresponds to lane markings that respectively define distances between a road edge and a road centerline (Horinaga Figure 9, P15 and P17).
Horinaga is considered to be analogous to the claimed invention because they are in the same field of identifying widths of roads. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, Zhang, Straus, and Li to include the teachings of Horinaga. This would provide the advantage of being able to determine the width of the traveling lane without the use of adjacent lanes (Horinaga Paragraph [0090] “That is, it is possible to detect the change in lane width for the own vehicle without using the information on the adjacent lane according to the present embodiment.”).
In regards to claim 16, Whitehead in view of Kumano, Halt, Zhang, Straus, Li, and Horinaga renders obvious the claim limitations as in the consideration of claims 5 and 12 above.
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Whitehead in view of Kumano, Halt, Zhang, Straus, and Li, and further in view of Shirai (US20020044080).
In regards to claim 8, Whitehead in view of Kumano, Halt, Zhang, Straus, and Li teaches the system of claim 1, but fails to teach extracting a key lane marking from the lane marking data based on a width of the key lane marking, such that the width of key lane marking is closest to the estimated probable lane width among all lane markings in the lane marking data.
However, Shirai teaches extracting a key lane marking from the lane marking data based on a width of the key lane marking, such that the width of key lane marking is closest to the estimated probable lane width among all lane markings in the lane marking data. (Figure 10 Steps 423-425; Paragraph [0107] “The step S423 calculates the lane width from the interval between neighboring ones of the typical predicted transverse positions”; Paragraph [0108] “] The step S424 converts the coordinates (X.sub.0, Z.sub.0) of the central position of each probable delineator into the coordinates (X.sub.1, Z.sub.1) thereof which occur on the assumption that the present vehicle is traveling along a straight road. The conversion of the coordinates is similar to that implemented by the block S412 in FIG. 6. The step S424 calculates a lane-width corresponding value on the basis of the lane width given by the step S423. The step S424 searches the probable delineators for one or ones each having a coordinate value X.sub.1 greater than the lane-width corresponding value. The step S424 excludes such a probable delineator or delineators from consideration concerning road-shape recognition. In other words, the step S424 selects only probable delineators each having a coordinate value X.sub.1 equal to or less than the lane-width corresponding value”)
Shirai is considered to be analogous to the claimed invention because they are in the same field of using image processing techniques to identify roads. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, Zhang, Straus, and Li to include the teaching of Shirai to only include the most accurate data and accommodate roads of many types (Shirai “The reference region for the determination as to whether or not probable delineators should be excluded is set depending on the calculated lane width (see the step S424 in FIG. 10). Accordingly, even in the case where the present vehicle is traveling along a lane having a variable width, the lane shape (the road shape) can be accurately recognized.”)
In regards to claim 19, Whitehead in view of Kumano, Halt, Zhang, Straus, Li, and Shirai renders obvious the claim limitations as in the consideration of claims 8 and 12 above.
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Whitehead in view of Kumano, Halt, Zhang, Straus, Li, and Shirai, and further in view of Wang (US20140278055).
In regards to claim 9, Whitehead in view of Kumano, Halt, Zhang, Straus, Li, and Shirai teaches the system of claim 8, but fails to teach wherein the at least one processor is further configured to extract one or more nearby lane markings in vicinity of the key lane marking.
However, Wang teaches wherein the at least one processor is further configured to extract one or more nearby lane markings in vicinity of the key lane marking (Paragraph [0051] “In some examples, once a road is updated in the digital map, the nearby GPS traces (135) can be re-processed through the map matching module (105) described above in connection with FIGS. 1-3.”).
Wang is considered to be analogous to the claimed invention because they are in the same field of using map data to identify roads. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, Zhang, Straus, Li, and Shirai to include the teaching of Wang to make a more complete map database with all the nearby lane markers (Wang Paragraph [0051] “By running the method described above in connection with FIG. 4 iteratively, the system (100) of mobile module (200) can acquire additional roads while existing roads may be leveraged to help split up the GPS traces (135) into clusters of GPS traces (135)”)
In regards to claim 10, Whitehead in view of Kumano, Halt, Zhang, Straus, Li, Shirai, and Wang teaches the system of claim 9, and teaches wherein the at least one processor is further configured to update a map database based on the key lane marking and the one or more nearby lane markings, such that the update comprises complementing missing lane boundary data of the obtained lane marking data. (Wang Figure 3; Wang Paragraph [0034] “A proposed change to the digital map may then be received (320) at the map updating module (120). The processor (130) may then cause a number of roads in the map database (125) to be updated (325) based on the proposed changes.”)
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Whitehead in view of Kumano, Halt, Zhang, Straus, and Li, and further in view of Thang (“The Anomaly Detection by Using DBSCAN Clustering with Multiple Parameters”).
In regards to claim 11, Whitehead in view of Kumano, Halt, Zhang, Straus, and Li teaches the system of claim 1, but fails to teach wherein the at least one processor is further configured to: remove outlier data from the lane marking data based on a distance associated with the lane marking data and the corresponding identified map link or topology.
However Thang teaches wherein the at least one processor is further configured to: remove outlier data from the lane marking data based on a distance associated with the lane marking data and the corresponding identified map link or topology.(Section III, Paragraph 1 “In detection phase, we assign new points to clusters and make alerts if points are assigned to anomaly clusters.” Section III, Sub-section B, Step 5 “For each new point, find the closest cluster’s mean points and then try assigning it to the cluster. If the point fall inside cluster (dp-m <= Cz) or the point fall outside cluster (dpm >= Cz) but distance from it to the cluster is smaller than cluster’s epsilon, assign the point to the cluster. Otherwise mark the point as unsure points.” Examiner note: Here, anomaly clusters and unsure points are analogous to outliers.)
Thang is considered to be analogous to the claimed invention because they are in the same field of identifying lane markings. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Whitehead in view of Kumano, Halt, Zhang, Straus, and Li to include the teachings of Thang, providing the advantage of not needing to train a network to detect outliers, and instead are able to use real world data, and identify the outliers in said data (Thang “In statistical detection and machine learning techniques, supervised anomaly detection algorithms are often used with the combination of labeled data or attack-free data in training phase to model normal behavior. The performances of these algorithms highly depend on attack-free training data. However, it is difficult to obtain such training data in real world network environment. Data mining techniques such as clustering and outlier detection are unsupervised anomaly detection algorithms. They attempt to detect anomalous behavior without using any knowledge about the training 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 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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
“Visual Detection and Tracking of Poorly Structured Dirt Roads” teaches a method of detecting road boundaries when there are no clear markings, for example on a dirt road.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CALEB LOGAN ESQUINO whose telephone number is (703)756-1462. The examiner can normally be reached M-Fr 8:00AM-4:00PM EST.
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/CALEB L ESQUINO/Examiner, Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677