DETAILED ACTION
Response to Amendment
This office action regarding application number 18/564,813, filed November 28, 2023, is in response to the applicants arguments and amendments filed December 9, 2025. Claims 2 and 9 have been cancelled. Claims 1, 3, 8, and 10-13 have been amended. Claims 1, 3-8 and 10-13 are currently pending and are addressed below.
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
The applicants arguments and amendments to the application have overcome some of the objections and rejections previously set forth in the Non-Final action mailed September 17, 2025. Claims 2 and 9 have been cancelled and therefore all associated objections and rejections are withdrawn. Applicants amendments to the specification and abstract have been deemed sufficient to overcome the previous objections, therefore the specification objections are withdrawn. Applicants amendments to the claims have rendered the previous 35 USC 112(f) interpretations moot, therefore the previous interpretations have been withdrawn. Applicants amendments to the claims have been deemed sufficient to overcome the previous 35 USC 112(b) rejections through the removal of “grid-like”, therefore the rejections are withdrawn. Applicants amendments to claims 1 and 12-13 have been deemed sufficient to overcome the previous 35 USC 103 rejections through the inclusion of “the detection information including sensor observation information and probability-of-presence values as stored in a sensor detection information data group” therefore the rejections are withdrawn. However as this changes the scope of the claims, new art rejections have been made based on the changes in scope.
However applicants amendments to the drawings have not overcome all of the previous rejections as discussed below, specifically the drawings still include the following reference characters mentioned in the description: 811, S1007. Applicants amendments to claims 1 and 12-13 have NOT been deemed sufficient to overcome the previous 35 USC 101 rejections for the reasons discussed below, the rejections are maintained with changes to reflect amendments. Additionally the applicants arguments have been fully considered but are not fully persuasive for the reasons seen below.
On page 12 the applicant argues “The objection to the drawings is respectfully traversed. The rejection is premised on Figures 1 and 10 allegedly using both reference characters "14" and "16" to designate "Traveling control mode determination unit." This statement, however, is incorrect. In fact, in Figure 1, reference numeral 14 refers to the "traveling control mode determination unit," while reference numeral 16 refers to the "HMI information generating unit." See Figure 1. Figure 10 does not include any reference to numerals 14 or 16. See Figure 10. Accordingly, withdrawal of the objection is respectfully requested.”, the examiner respectfully disagrees.
Here the examiner would like to clarify the objection, Figure 1 shows items 14 and 16, “Traveling Control Mode Determination Unit” and “HMI Information Generating Unit” respectively. Figure 10 shows at the first section of the flow chart “Traveling Control Mode Determination Unit 16”. Here the objection is based on Figure 1 using item 16 as “HMI Information Generating Unit” and Figure 10 using item 16 as “Traveling Control Mode Determination Unit 16”. Item 16 is being used to designate two different items.
Therefore the objections are maintained and appropriate correction is required. See included image below.
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On pages 17-18 the applicant argues “Regarding Step 2A - Prong 1: The Claim Does NOT Recite a Judicial Exception. The Examiner previously asserted that the limitations: "specifies a correspondence relationship," "determines a relationship," and "determines a detectable area" could be performed mentally. As herein amended, however, this is no longer possible. The amended claim now explicitly recites, using verbatim specification support: a processing unit (CPU, GPU, FPGA, or ASIC) executing operation programs (Spec.[0024]-[0027]); sensor detection information that includes probability-of-presence values and sensor observation values stored in a sensor detection information data group (31) (Spec.[0034]-[0035]); integrated detection information data group (34) derived from sensor fusion computations (Spec. [0065]-[0075]); grid map generation on a polar coordinate system stored in the storage unit as data group (35) (Spec. [0142]-[0147]). These operations cannot be performed "in the mind." They require: 1) Specialized probabilistic sensor data representations, 2) Multisensor fusion computations, 3) Indexing into multi-dimensional grid- map structures, and 4) Updating individual grid cells based on time-series detection changes. All of these features require: matrix-based data, non-human-processable numeric probability values, and specialized memory structures. Accordingly, amended claim 1 does not recite a mental process and does not recite a mathematical concept or a method of organizing human activity. Thus, step 2A, prong 1, is satisfied.”, the examiner respectfully disagrees.
MPEP 2104 discusses requirements under 35 USC 101 and MPEP 2106 discusses Patent subject matter eligibility. MPEP 2106.05(g) provides specific examples of insignificant extra solution activity. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
As is discussed in detail in the rejections below the claims recite the steps of generating integrated detection information, determining a relationship, generating a detectable area, determining a detectable area, determining a detection capability level, and determining a detectable area. The examiner asserts that each of these steps can reasonably be performed in the human mind or with a pen and paper, for example a person of ordinary skill in the art is reasonably able to evaluate sensor data from a plurality of sources to mentally determine an integrated mental representation of an area, a person driving a vehicle performs this function on a daily basis by looking out the windshield while using mirror to mentally keep track of objects. A person can further determine relationships between position and a detection capability of a sensor, this function can also be performed mentally. A person can further mentally or with a pen and paper use a plurality of data sources to determine a detectable area in the form of a map grid. While the steps here are reciting the use of a computer and technological elements the steps themselves can be performed mentally or with a pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with a pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer"). Mental processes recited in claims that require computers are explained further below with respect to point C.
Claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include: a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis."
Therefore the rejections under 35 USC 101 are maintained with changes to reflect amendments.
On page 18 the applicant argues “Regarding Step 2A - Prong 2: The Claim Integrates Any Alleged Abstract Idea into a Practical Application. Even assuming, for the sake of argument, that sensor detection comparison could be considered abstract, amended claim 1 now clearly integrates these operations into a specific practical application, namely: A vehicle-mounted ECU performing real-time sensor-fusion-based determination of sensor detection capabilities using a grid-map structure stored in memory. The amended features expressly include: (1) Specific hardware implementation Processing unit: CPU/GPU/FPGA/ASIC (Spec.[0024]-[0027]), Storage unit storing: sensor detection information data group (31), integrated detection information data group (34), sensor detectable area data group (35), and In-vehicle network interface (Spec.[0023]). This is precisely the sort of machine implementation that the 2019 PEG recognizes as a practical application.”, the examiner respectfully disagrees.
As is discussed in detail in the rejection below the steps here are reciting the use of a computer and technological elements the steps themselves can be performed mentally or with a pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with a pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. The recitation of a processor or ECU amounts to nothing more than instructions apply the exception using a generic computer component and generally link the use of the judicial exception to a technological environment. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept and does not integrate the abstract idea into practical application.
The examiner would like to note that while the arguments recite real-time sensor fusion elements, the claims themselves do not recite this limitation.
Therefore the rejections under 35 USC 101 are maintained with changes to reflect amendments.
On pages 18-19 the applicant argues “Further, as herein amended, the claims are directed to a technical improvement to a technological field (vehicle perception systems). The amended claim now recites: determining detection capability based on detection failures (Spec. [0086]-[0094]);generating a grid-map on a polar coordinate system centered at sensor position (Spec.[0142]-[0147]); updating detection capability levels in each unit area (Spec.[0148]- [0159]). These operations improve: sensor perception robustness, automatic driving reliability, fused environment modeling, and sensor-dependent safety decisions. These are technological improvements recognized as "practical applications" under: Thales Visionix, McRO, CardioNet, Finjan, and SRI International..”, the examiner respectfully disagrees.
MPEP 2106.04(d)(1) is directed towards evaluating improvements in the functioning of a computer or technical field and gives examples of such improvements her “Examples of claims that improve technology and are not directed to a judicial exception include: Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1339, 118 USPQ2d 1684, 1691-92 (Fed. Cir. 2016) (claims to a self-referential table for a computer database were directed to an improvement in computer capabilities and not directed to an abstract idea); McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1315, 120 USPQ2d 1091, 1102-03 (Fed. Cir. 2016) (claims to automatic lip synchronization and facial expression animation were directed to an improvement in computer-related technology and not directed to an abstract idea); Visual Memory LLC v. NVIDIA Corp., 867 F.3d 1253,1259-60, 123 USPQ2d 1712, 1717 (Fed. Cir. 2017) (claims to an enhanced computer memory system were directed to an improvement in computer capabilities and not an abstract idea); Finjan Inc. v. Blue Coat Systems, Inc., 879 F.3d 1299, 125 USPQ2d 1282 (Fed. Cir. 2018) (claims to virus scanning were found to be an improvement in computer technology and not directed to an abstract idea); SRI Int’l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1303 (Fed. Cir. 2019) (claims to detecting suspicious activity by using network monitors and analyzing network packets were found to be an improvement in computer network technology and not directed to an abstract idea). Additional examples are provided in MPEP § 2106.05(a).” Here while the claims are directed towards a computer implemented method, the claims do not improve the functioning of a computer, the claims are simply directed towards method that can reasonably performed within the human mind with the assistance of a pen and paper, that is being performed by a computer. The claims do not improve computer capabilities but simply performing a method using a generic computer system.
Therefore the rejections under 35 USC 101 are maintained with changes to reflect amendments.
On pages 19 the applicant argues “Further, as herein amended, the claims transform data closely tied to physical sensors in the real world. In particular, integrated detection information is derived from: actual physical sensing events, actual detection failures, and real-world detection probability changes across spatial grid cells. This is not abstract manipulation of data. It is processing tied to physical sensor limitations, producing an output used to control vehicle perception and decision-making. Thus, the amended claim integrates any alleged abstract idea into a meaningful practical application, satisfying Step 2A, Prong 2”, the examiner respectfully disagrees.
As is discussed in the above responses and in the rejection below, the transformation of data itself is not a practical application, the collection of data via sensors has been determined to be insignificant extra solution activity, See MPEP 2106.05(g), “An example of pre-solution activity is a step of gathering data for use in a claimed process, e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent. An example of post-solution activity is an element that is not integrated into the claim as a whole, e.g., a printer that is used to output a report of fraudulent transactions, which is recited in a claim to a computer programmed to analyze and manipulate information about credit card transactions in order to detect whether the transactions were fraudulent.”. While the data processing can determine a result such as a sensor limitation this can be performed mentally.
The examiner would like to note that while the argument recites producing an output used to control the vehicle, this limitation is not represented in the claims, if a step for controlling the vehicle using the results of the above mental process steps were included in the claims this may be sufficient to overcome the rejections under 35 USC 101, pending examination of the specific amended language.
Therefore the rejections under 35 USC 101 are maintained with changes to reflect amendments.
On pages 19-20 the applicant argues “Regarding Step 2B - The Claim Recites an Inventive Concept. Even assuming an abstract idea remained (it does not), the amended claim now recites significantly more because: (1) The processing unit is not generic; it is expressly disclosed as CPU/GPU/FPGA/ASIC architecture. (Spec.[0024]-[0027]). These are specialized hardware components used for high-speed sensor fusion. (2) The memory structures are not generic; they include specific multi-layered data groups for: sensor detection information (data group 31), integrated detection information (34), and sensor detectable area grid-map (35). These structures are nowhere described as generic or routine. (3) The operations performed are not routine or conventional. The Examiner characterized the original claim as mere "data gathering." That is no longer applicable because the amended claim: generates a polar-coordinate grid map, stores detection capability levels per cell, updates grid cells based on time-series changes in detection success/failure, uses multisensor corroboration from the integrated detection information. No cited art and no routine ECU function performs this transformation. (4) The steps constitute a specific, non-conventional arrangement of components. Under Bascom, even conventional components can form an inventive concept when arranged in a non-conventional manner. Here, the combination of: multisensor fusion, grid-map generation, vehicle ECU execution, polar-coordinate mapping, dynamic capability updating, real-time evaluation is non-conventional and is explicitly tied to the spec. Thus, the amended claim recites significantly more than any alleged abstract idea.”, the examiner respectfully disagrees.
As is discussed in detail in the rejection below the steps here are reciting the use of a computer and technological elements the steps themselves can be performed mentally or with a pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with a pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
The claim only recites the additional elements of a processor and storage, these elements are considered to be generic computer components. The recitation of a processor or ECU amounts to nothing more than instructions apply the exception using a generic computer component and generally link the use of the judicial exception to a technological environment. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept and does not integrate the abstract idea into practical application.
The components themselves are entirely conventional and the limitations of integrating sensor data, generating a polar coordinate map and determining sensor capabilities are considered to be mental process steps. The examiner would like to note that while the arguments recite real-time evaluation and vehicle ECU execution elements, the claims themselves do not recite this limitation.
Therefore the rejections under 35 USC 101 are maintained with changes to reflect amendments.
Applicant’s arguments with respect to claim(s) 1 and 12-13, specifically the “probability-of-presence” limitations, 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.
On pages 21 the applicant argues “Regarding the claimed "integrated detection information ... indicating environmental elements detected by the first external environment sensor and the second external environment sensor and for which the correspondence relationship is specified," Honda integrates on a per-pixel basis (it "assigns to the pixel a second parameter which is the result of integration"), using rules like "the greater of' per-sensor values; it does not build an explicit cross-sensor 'correspondence relationship' between environmental elements(objects) seen by different sensors and store that as an integrated record. The data structure is a pixel map, not an element-to-element correspondence list.”, the examiner respectfully disagrees.
MPEP 2142-2144 discusses the requirements for a case of obviousness using 35 USC 103 and provides examples of such cases. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
As is discussed in the rejection below, the Honda reference is not relied on to teach the limitations of “integrated detection information ... indicating environmental elements detected by the first external environment sensor and the second external environment sensor and for which the correspondence relationship is specified”. Akiyama teaches a sensor detection information integrating unit implemented by the processing unit (See Figures 1 and 2, Figure 1 showing various units such as “Association processing unit” that are implemented by a processor as shown in figure 2); that generates integrated detection information by comparing and integrating the detection information of the first and second external environment sensors to specify a correspondence relationship between environmental elements, the integrated detection information being stored in the storage unit as an integrated detection information data group (Paragraph [0012], “an association processing unit configured to take an association between the first object detection result and the second object detection result in an area excluding the occlusion area determined by the occlusion area detection processing unit “) (Paragraph [0038], "Next, the association between an object detection result of the first object detection unit 1101 for which the occlusion area has been determined as described above, and an object detection result of the second object detection unit 1102, is determined by the association processing unit 1202," here the association processing unit is integrating detection information from the first detection result and the second detection result to determine an association/correspondence relationship between object detections) (See Figures 1 and 2 which shows the functions of the association processing unit implemented by a processor and storage); and indicating environmental elements detected by the first environmental sensor and the second external environment sensor and for which the correspondence relationship is specified (Paragraph [0038], “the association between each object detection result of the first object detection unit 1101 and each object detection result of the second object detection unit 1102 is determined, and the detection results that exhibit a great association are combined,” here the environmental elements/objects that are detected by both sensors are associated/combined).
The Honda reference is relied upon to teach using a plurality of sensor information in order to generate polar coordinate grid maps.
Therefore the combination of Akiyama, Honda, and Xie teaches “integrated detection information ... indicating environmental elements detected by the first external environment sensor and the second external environment sensor and for which the correspondence relationship is specified” and the 35 USC 103 rejections are maintained.
On pages 21-22 the applicant argues “Regarding the claimed "sensor detectable area determining unit ... [that] determines a relationship between a relative position and a detection capability at the first external environment sensor, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information," Honda instead derives per- pixel reliability from sensor-specific position-reliability maps and per-sensor measurements (distance, angle, velocity) and then integrates those reliabilities; it does not determine the first sensor's detection capability based on the first sensor's state of detection of environmental elements that were detected by a second sensor (as reflected in integrated detection information). The capability/reliability is computed from maps and per-sensor inputs, not conditioned on "elements detected by the second sensor."”, the examiner respectfully disagrees.
As is discussed in the rejection below, the Honda reference is not relied on to teach the limitations of "sensor detectable area determining unit ... [that] determines a relationship between a relative position and a detection capability at the first external environment sensor, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information.”. These limitation are taught by the Akiyama reference.
Akiyama teaches a sensor detectable area determining unit implemented by the processing unit that determines a relationship between a relative position and a detection capability at the first external environment sensor (Paragraph [0034], "The number of occlusion areas is one in FIG. 4B, but in the case where there are a plurality of (n) surrounding objects, the above processing is performed for all the object detection results of the first object detection unit 1101, to determine occlusion areas Q1 to Qn for the first object detection unit 1101.") (See Figures 5B-5D); based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor the state of detection being indicated in the integrated detection information (See Figure 3, steps S3-S5, here the figure shows the system determining object detectable area from a first object detection result, and then determine second object detectable area for the second object detection, and then determine an association possible area from the two separate object detection results in which object can be detected by both sensors).
Therefore the combination of Akiyama, Honda, and Xie teaches "sensor detectable area determining unit ... [that] determines a relationship between a relative position and a detection capability at the first external environment sensor, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information.” and the 35 USC 103 rejections are maintained.
On pages 22 the applicant argues “Regarding the claimed "grid map ... created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area," Honda instead divides the detection space into pixels using orthogonal boundary surfaces(rectangular grid). It also mentions a radial/sector alternative whose center is a vehicle reference point (37)-not the installation point of any specific sensor, and certainly not the "first external environment sensor." Thus Honda lacks a polar grid centered at the first sensor's installation point as claimed.”, the examiner respectfully disagrees.
MPEP 2142-2144 discusses the requirements for a case of obviousness using 35 USC 103 and provides examples of such cases. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
As discussed in the rejections below Honda teaches a grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment sensor in each unit area (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map with polar coordinates and the vehicle and sensor at the center of the area, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area) (Column 18, lines 30-35, “The two-dimensional coordinate system may be either a rectangular coordinate system or a polar coordinate system.”) (See Figures 11A and 11B showing two separate polar coordinate systems each having a center at the location of the separate sensors). Here in Honda teaches that a polar or rectangular coordinate system can be used to create a grip map as seen in figures 11A and 11B which further show that the origins of the grid maps are each centered on a sensor/detector.
Therefore the combination of Akiyama, Honda, and Xie teaches "grid map ... created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area," and the 35 USC 103 rejections are maintained.
On pages 22 the applicant argues “Regarding the claimed "determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information," Honda instead assigns/updates reliability levels per pixel from sensor-specific reliability sources and then integrates those values; its per-pixel capability is not computed because the second sensor detected an element and the first sensor's state of detection of that same element changed. The cited integration step applies generic per-sensor reliabilities (including "greater-of' selection), not the cross-sensor conditional update Applicants' claims recite.”, the examiner respectfully disagrees.
MPEP 2142-2144 discusses the requirements for a case of obviousness using 35 USC 103 and provides examples of such cases. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
As discussed in the rejections below Honda teaches a determines a detection capability level in each unit area of the grid map (See figure 4 showing reliability information for the sensor for each unit of the grid like map) (See Figure 11A and 11B showing the state detection for each grid section for a plurality of sensors); based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor (Column 25, lines 25-35, “In the example shown in FIG. 9, the parameter integration section 15 is arranged so as to enable integration of the detection information DS output from the sensor 11A and the detection information DS output from the sensor 11B.” here as can be seen in figure 11B the detection capability level is determined for each unit area of the grid map using the state of detection of a first and second sensor).
Therefore the combination of Akiyama, Honda, and Xie teaches "determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information," and the 35 USC 103 rejections are maintained.
On pages 22-23 the applicant argues “Regarding the claimed "determines a detectable area for the first external environment sensor based on a change in the state of detection indicated by the integrated detection information," Honda may instead update "latest reliability" when a sensor's own detection capability changes and uses second-reliability maps to select allowable control processing, but it does not recalibrate or re-define a first-sensor "detectable area" driven by changes in state-of-detection as indicated by integrated detection information. Its use of second- reliability for control selection (Fig. 14) is not the same as computing/maintaining a sensor- specific detectable-area map based on cross-sensor integrated states.”, the examiner respectfully disagrees.
As is discussed in the rejection below, the Honda reference is not relied on to teach the limitations of "determines a detectable area for the first external environment sensor based on a change in the state of detection indicated by the integrated detection information,". These limitation are taught by the Akiyama reference.
Akiyama teaches determines a detectable area for the first external environment sensor based on change in the state of detection indicated by the integrated detection information (Paragraph [0032], “FIG. 4A shows a detection area P of the first object detection unit 1101 when there is no object around the own vehicle 10. In this case, the first object detection unit 1101 can detect all objects in the detection area P, and no occlusion area occurs. Next, FIG. 4B shows a state in which there is a surrounding object 20 in the detection area P. In this case, the surrounding object 20 becomes an obstacle to cause an area (occlusion area Q1) where the first object detection unit 1101 cannot perform detection,” here the system is determining a detectable area for a first sensor based on a change of state from no object detected to an object being detected which forms an occlusion area) (See also figures 5B-5D) (Paragraph [0035], “In the determination for the occlusion area, margins Mx, My may be set in accordance with object detection error in the X-axis direction or the Y-axis direction in the first object detection unit 1101, whereby the condition A and the condition B may be respectively changed into a condition A′ and a condition B′ as shown below, so as to narrow the occlusion area. It is noted that the margins Mx, My are set as positive values,” here the system is determining the detectable area outside of the occlusion area and is updating that area based on changing states of objects according to the integrated detection results of the first and second object detection units).
Therefore the combination of Akiyama, Honda, and Xie teaches "determines a detectable area for the first external environment sensor based on a change in the state of detection indicated by the integrated detection information," and the 35 USC 103 rejections are maintained.
On pages 23 the applicant argues “Regarding the claimed "acquires, via the in-vehicle network, detection information from a first external environment sensor and ... a second external environment sensor," Honda instead broadly states that sensors "capture detection information" and that the apparatus processes it; it does not require (or even clearly disclose) that acquisition is via an in-vehicle network as part of the invention.”, the examiner respectfully disagrees.
As is discussed in the rejection below, the Honda reference is not relied on to teach the limitations of "acquires, via the in-vehicle network, detection information from a first external environment sensor and ... a second external environment sensor,". These limitation are taught by the Akiyama reference.
Akiyama teaches the use of an in-vehicle network to transfer information (Paragraph [0002], “detection results are transferred as sensor information to a vehicle control device via the in-vehicle network”).
Therefore the combination of Akiyama, Honda, and Xie teaches "acquires, via the in-vehicle network, detection information from a first external environment sensor and ... a second external environment sensor," and the 35 USC 103 rejections are maintained.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: 811, S1007. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference characters "14" and "16" have both been used to designate “Traveling control mode determination unit” in figures 1 and 10. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-8, and 10-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1,
Under Step 1:
Claim 1 is an apparatus claim comprising an electronic control device. (thus the claims are to an apparatus Step 1: yes)
Under Step 2A - Prong 1:
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b)certain methods of organizing human activity, and/or c) mental processes.
Independent Claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
An electronic control device incorporated in a vehicle, the electronic control device comprising:
a processing unit and
a storage unit, the electronic control device being connected to an external environment sensor group via an in-vehicle network, the electronic control device comprising
a sensor detection information acquiring unit implemented by the processing unit that acquires, via the in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the detection information including sensor observation information and probability-of-presence values as stored in a sensor detection information data group in the storage unit, the first and second environment sensors being incorporated in the vehicle
a sensor detection information integrating unit implemented by the processing unit that generates integrated detection information by comparing and integrating the detection information of the first and second external environment sensors to specify a correspondence relationship between environmental elements, the integrated detection information being stored in the storage unit as an integrated detection information data group, and indicating environmental elements detected by the first environmental sensor and the second external environment sensor and for which the correspondence relationship is specified
a sensor detectable area determining unit implemented by the processing unit that
determines a relationship between a relative position and a detection capability at the first external environment sensor, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor the state of detection being indicated in the integrated detection information
generates a detectable area for the first external environment sensor as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment sensor in each unit area
determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information and
determines a detectable area for the first external environment sensor based on change in the state of detection indicated by the integrated detection information.
The examiner submits that the foregoing bolded limitations constitute a “mental process” because as drafted, the limitations are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components (i.e. “electronic control device”). Specifically, but for the “electronic control device” language, “generates integrated detection information by comparing and integrating the detection information … and indicating environmental elements … determines a relationship between a relative position and a detection capability at the first external environment sensor … generates a detectable area for the first external environment sensor … determines a detection capability level in each unit area of the grid map … determines a detectable area for the first external environment sensor ” in the context of this claim encompasses the user mentally specifying relationship between elements detected environmental sensors, and using that specified relationship to determine a detectable area for the first sensor in the form of a grid including a detection capability level. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with a pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Under Step 2A - Prong 2:
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea area as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
An electronic control device incorporated in a vehicle, the electronic control device comprising:
a processing unit and
a storage unit, the electronic control device being connected to an external environment sensor group via an in-vehicle network, the electronic control device comprising
a sensor detection information acquiring unit implemented by the processing unit that acquires, via the in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the detection information including sensor observation information and probability-of-presence values as stored in a sensor detection information data group in the storage unit, the first and second environment sensors being incorporated in the vehicle
a sensor detection information integrating unit implemented by the processing unit that generates integrated detection information by comparing and integrating the detection information of the first and second external environment sensors to specify a correspondence relationship between environmental elements, the integrated detection information being stored in the storage unit as an integrated detection information data group, and indicating environmental elements detected by the first environmental sensor and the second external environment sensor and for which the correspondence relationship is specified
a sensor detectable area determining unit implemented by the processing unit that
determines a relationship between a relative position and a detection capability at the first external environment sensor, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor the state of detection being indicated in the integrated detection information
generates a detectable area for the first external environment sensor as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment sensor in each unit area
determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information and
determines a detectable area for the first external environment sensor based on change in the state of detection indicated by the integrated detection information.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the limitations of “acquires, via the in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the detection information including sensor observation information and probability-of-presence values as stored in a sensor detection information data group in the storage unit, the first and second environment sensors being incorporated in the vehicle” the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (electronic control device) to perform the process. In particular, the acquiring steps from the sensors are recited at a high level of generality (i.e. as a general means of gathering sensor data for use in the determining steps), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Regarding the additional limitations of “An electronic control device incorporated in a vehicle … a processing unit and a storage unit … a sensor detection information acquiring unit … a sensor detection information integrating unit … a sensor detectable area determining unit” the examiner submits that these limitations are an attempt to generally link additional elements to a technological environment. In particular, the electronic control device and plurality of units is recited at a high level of generality and merely automates the determining steps, therefore acting as a generic computer to perform the abstract idea. The electronic control device is claimed generically and is operating in its ordinary capacity and does not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The additional limitation is no more than mere instructions to apply the exception using generic computer components (electronic control device).
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Under Step 2B:
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “An electronic control device incorporated in a vehicle … a processing unit and a storage unit … a sensor detection information acquiring unit … a sensor detection information integrating unit … a sensor detectable area determining unit” amounts to nothing more than mere instructions to apply the exception using a generic computer component and generally link the use of the judicial exception to a technological environment. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “acquires, via the in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the detection information including sensor observation information and probability-of-presence values as stored in a sensor detection information data group in the storage unit, the first and second environment sensors being incorporated in the vehicle” the examiner submits that these limitations are insignificant extra-solution activities. Hence, the claim is not patent eligible.
Therefore claim 1 is ineligible under 35 USC 101.
Regarding dependent claims 3-8 and 10-11
Under Step 1:
Claims 3-8 and 10-11 are to a method comprising the steps of “an environmental element detected by the second external environment sensor has changed, the detection position being indicated in time series data of the integrated detection information” (Claim 3), “estimates a cause by which a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor has changed” (Claim 4), “expressed as a combination of a detectable distance and a detectable angle range, and the sensor detectable area determining unit estimates whether a cause of change in the state of detection is a cause related to a detection distance or a cause related to a detection angle, determines a detectable distance for the first external environment sensor, based on the estimated cause related to the detection distance, and determines a detectable angle range for the first external environment sensor” (Claim 5), “determining unit estimates whether a cause of change in the state of detection is occlusion by a different obstacle, and does not use information indicating the estimated cause being occlusion by the different obstacle” (Claim 6), “determines detection reliability of the first external environment sensor” (Claim 7), “a vehicle control information generating unit that generates control information on the vehicle” (Claim 8), “the sensor detectable area determining unit reduces a detection capability level in a unit area corresponding to a position in a detectable area for the first external environment sensor” (Claim 10), and “wherein the grid-like map is created by dividing an area into grid-like patterns on a polar coordinate system” (Claim 11) (thus the claims are to an method, Step 1: yes).
Under Step 2A – Prong 1:
Claims 3-8 and 10-11 depend on claim 1 and recite the limitations of “an environmental element detected by the second external environment sensor has changed, the detection position being indicated in time series data of the integrated detection information” (Claim 3), “estimates a cause by which a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor has changed” (Claim 4), “expressed as a combination of a detectable distance and a detectable angle range, and the sensor detectable area determining unit estimates whether a cause of change in the state of detection is a cause related to a detection distance or a cause related to a detection angle, determines a detectable distance for the first external environment sensor, based on the estimated cause related to the detection distance, and determines a detectable angle range for the first external environment sensor” (Claim 5), “determining unit estimates whether a cause of change in the state of detection is occlusion by a different obstacle, and does not use information indicating the estimated cause being occlusion by the different obstacle” (Claim 6), “determines detection reliability of the first external environment sensor” (Claim 7), “a vehicle control information generating unit that generates control information on the vehicle” (Claim 8), “the sensor detectable area determining unit reduces a detection capability level in a unit area corresponding to a position in a detectable area for the first external environment sensor” (Claim 10), and “wherein the grid-like map is created by dividing an area into grid-like patterns on a polar coordinate system” (Claim 11), These claims recite an abstract idea which is directed to mental process.
Under Step 2A – Prong 2:
This judicial exception is not integrated into a practical application, the claims do not includes any additional elements that integrate the abstract idea into a practical application. In particular the claims here only further recite additional mental process limitations or further define the mental process limitations. For example claims 3-8 and 10-11, recite the additional mental process limitations of “determines a relationship between a relative position and a detection capability”, “estimates a cause”, and “generates control information” which are all considered to be mental process steps able to be performed in the human mind or with a pen and paper.
Under Step 2B:
Step 2B, the claims 3-8 and 10-11 do not include any additional elements that are sufficient to amount to significantly more than the judicial exception for similar reasons as that discussed in Step 2A Prong Two.
The additional limitations recited in the dependent claims 3-8 and 10-11 fail to establish that the dependent claims are not directed to an abstract idea. The additional limitations of the dependent claims, when considered individually and in combination, do not amount to significantly more than the abstract idea. Accordingly, claims 3-8 and 10-11 are not patent eligible.
Regarding claim 12,
Under Step 1:
Claim 12 is an apparatus claim comprising an electronic control device. (thus the claims are to an apparatus Step 1: yes)
Under Step 2A - Prong 1:
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b)certain methods of organizing human activity, and/or c) mental processes.
Independent Claim 12 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 12 recites:
An electronic control device incorporated in a vehicle, comprising:
a processing unit and
a storage unit, the electronic control device being connected to an external environment sensor group via an in-vehicle network, the electronic control device comprising
a sensor detection information acquiring unit implemented by the processing unit that acquires, via the in-vehicle network, detection information from each of a plurality of external environment sensors with different detection ranges, the detection information including sensor observation information and probability-of-presence values and being stored in the storage unit as a sensor detection information data group, the external environment sensors being incorporated in the vehicle,
a sensor detection information integrating unit implemented by the processing unit that generates integrated detection information by comparing and integrating the detection information of the plurality of external environment sensors to specify correspondence relationships between environmental elements detected by the plurality of external environment sensors, the integrated detection information being stored in the storage unit as an integrated detection information data group and
a sensor detectable area determining unit implemented by the processing unit that compares detection results in an overlapping area of detection ranges of the plurality of external environment sensors indicated by the integrated detection information and determines an effective detection range for at least one of the external environment sensors as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the at least one external environment sensor at a center of the area to express a detection capability level of the at least one external environment sensor in each unit area, and that determines a detection capability level in each unit area of the grid map, based on a state of detection by the at least one external environment sensor of an environmental element detected by another one of the plurality of external environment sensors, the state of detection being indicated in the integrated detection information
The examiner submits that the foregoing bolded limitations constitute a “mental process” because as drafted, the limitations are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components (i.e. “electronic control device”). Specifically, but for the “electronic control device” language, “generates integrated detection information by comparing and integrating the detection information of the plurality of external environment sensors to specify correspondence relationships between environmental elements detected by the plurality of external environment sensors, the integrated detection information being stored in the storage unit as an integrated detection information data group … compares detection results in an overlapping area of detection ranges of the plurality of external environment sensors indicated by the integrated detection information and determines an effective detection range for at least one of the external environment sensors as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the at least one external environment sensor at a center of the area to express a detection capability level of the at least one external environment sensor in each unit area, and that determines a detection capability level in each unit area of the grid map, based on a state of detection by the at least one external environment sensor of an environmental element detected by another one of the plurality of external environment sensors, the state of detection being indicated in the integrated detection information” in the context of this claim encompasses the user mentally or with a pen and paper using detection information from a plurality of sensors to determine a range of one of the sensors by mentally comparing detection results in an overlapping area and mapping the results to grid. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Under Step 2A - Prong 2:
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea area as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
An electronic control device incorporated in a vehicle, comprising:
a processing unit and
a storage unit, the electronic control device being connected to an external environment sensor group via an in-vehicle network, the electronic control device comprising
a sensor detection information acquiring unit implemented by the processing unit that acquires, via the in-vehicle network, detection information from each of a plurality of external environment sensors with different detection ranges, the detection information including sensor observation information and probability-of-presence values and being stored in the storage unit as a sensor detection information data group, the external environment sensors being incorporated in the vehicle,
a sensor detection information integrating unit implemented by the processing unit that generates integrated detection information by comparing and integrating the detection information of the plurality of external environment sensors to specify correspondence relationships between environmental elements detected by the plurality of external environment sensors, the integrated detection information being stored in the storage unit as an integrated detection information data group and
a sensor detectable area determining unit implemented by the processing unit that compares detection results in an overlapping area of detection ranges of the plurality of external environment sensors indicated by the integrated detection information and determines an effective detection range for at least one of the external environment sensors as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the at least one external environment sensor at a center of the area to express a detection capability level of the at least one external environment sensor in each unit area, and that determines a detection capability level in each unit area of the grid map, based on a state of detection by the at least one external environment sensor of an environmental element detected by another one of the plurality of external environment sensors, the state of detection being indicated in the integrated detection information.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the limitations of “acquires, via the in-vehicle network, detection information from each of a plurality of external environment sensors with different detection ranges, the detection information including sensor observation information and probability-of-presence values and being stored in the storage unit as a sensor detection information data group, the external environment sensors being incorporated in the vehicle” the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (electronic control device) to perform the process. In particular, the acquiring detection information from sensors are recited at a high level of generality (i.e. as a general means of gathering sensor data for use in the mental process step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Regarding the additional limitations of “An electronic control device incorporated in a vehicle, comprising: a processing unit and a storage unit … a sensor detection information acquiring unit … a sensor detection information integrating unit … a sensor detectable area determining unit” the examiner submits that these limitations are an attempt to generally link additional elements to a technological environment. In particular, the electronic control device and units are recited at a high level of generality and merely automates the determining steps, therefore acting as a generic computer to perform the abstract idea. The electronic control device is claimed generically and is operating in its ordinary capacity and does not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The additional limitation is no more than mere instructions to apply the exception using generic computer components (the electronic control device).
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Under Step 2B:
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “An electronic control device incorporated in a vehicle, comprising: a processing unit and a storage unit … a sensor detection information acquiring unit … a sensor detection information integrating unit … a sensor detectable area determining unit” amounts to nothing more than mere instructions to apply the exception using a generic computer component and generally link the judicial exception to a technological environment. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “acquires, via the in-vehicle network, detection information from each of a plurality of external environment sensors with different detection ranges, the detection information including sensor observation information and probability-of-presence values and being stored in the storage unit as a sensor detection information data group, the external environment sensors being incorporated in the vehicle” the examiner submits that these limitations are insignificant extra-solution activities. Hence, the claim is not patent eligible.
Therefore claim 12 is ineligible under 35 USC 101.
Regarding claim 13,
Under Step 1:
Claim 13 is an method claim comprising an electronic control device performing the steps of acquiring, integrating, and determining. (thus the claims are to an method Step 1: yes)
Under Step 2A - Prong 1:
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b)certain methods of organizing human activity, and/or c) mental processes.
Independent Claim 13 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 13 recites:
A control method by an electronic control device incorporated in a vehicle the method being implemented by a processing unit executing instructions stored in a storage unit of the electronic control device the method comprising:
acquiring, via an in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the first external environment sensor and second external environment sensor being incorporated in the vehicle, the detection information including sensor observation information and probability of presence values, and storing the detection information in the storage unit as a sensor detection information data group
generating, by comparing and integrating the detection information of the first and second external environment sensors, integrated detection information that specifies a correspondence relationship between environmental elements detected by the first external environment sensor and the second external environment sensor, and storing the integrated detection information in the storage unit as an integrated detection information data group
determining, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor as indicated in the integrated detection information, a relationship between a relative position and a detection capability at the first external environment sensor
generating a detectable area for the first external environment sensor as a grid map created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment in each unit area,
determining a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information and
determining a detectable area for the first external environment sensor based on a change in the state of detection indicated by the integrated detection information.
The examiner submits that the foregoing bolded limitations constitute a “mental process” because as drafted, the limitations are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components (i.e. “electronic control device ”). Specifically, but for the “electronic control device ” language, “generating, by comparing and integrating the detection information of the first and second external environment sensors, integrated detection information … determining … a relationship between a relative position and a detection capability at the first external environment sensor … generating a detectable area for the first external environment sensor as a grid map … determining a detection capability level in each unit area of the grid map … determining a detectable area for the first external environment sensor” in the context of this claim encompasses the user mentally or with a pen and paper generating integrated detection information using a plurality of sources, determining a relationship between the position and detection capability of a first source, determining a detectable area as a grid with associated detection capability and finally determining a detectable area. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with a pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Under Step 2A - Prong 2:
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea area as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A control method by an electronic control device incorporated in a vehicle the method being implemented by a processing unit executing instructions stored in a storage unit of the electronic control device the method comprising:
acquiring, via an in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the first external environment sensor and second external environment sensor being incorporated in the vehicle, the detection information including sensor observation information and probability of presence values, and storing the detection information in the storage unit as a sensor detection information data group
generating, by comparing and integrating the detection information of the first and second external environment sensors, integrated detection information that specifies a correspondence relationship between environmental elements detected by the first external environment sensor and the second external environment sensor, and storing the integrated detection information in the storage unit as an integrated detection information data group
determining, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor as indicated in the integrated detection information, a relationship between a relative position and a detection capability at the first external environment sensor
generating a detectable area for the first external environment sensor as a grid map created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment in each unit area,
determining a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor, the state of detection being indicated in the integrated detection information and
determining a detectable area for the first external environment sensor based on a change in the state of detection indicated by the integrated detection information.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the limitations of “acquiring, via an in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the first external environment sensor and second external environment sensor being incorporated in the vehicle, the detection information including sensor observation information and probability of presence values, and storing the detection information in the storage unit as a sensor detection information data group” the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (electronic control device) to perform the process. In particular, the acquiring steps from the sensors are recited at a high level of generality (i.e. as a general means of gathering sensor data for use in the determining steps), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Regarding the additional limitations of “an electronic control device incorporated in a vehicle the method being implemented by a processing unit executing instructions stored in a storage unit of the electronic control device the method comprising” the examiner submits that these limitations are an attempt to generally link additional elements to a technological environment. In particular, the electronic control device is recited at a high level of generality and merely automates the determining steps, therefore acting as a generic computer to perform the abstract idea. The electronic control device is claimed generically and is operating in its ordinary capacity and does not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The additional limitation is no more than mere instructions to apply the exception using generic computer components (electronic control device).
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Under Step 2B:
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “an electronic control device incorporated in a vehicle the method being implemented by a processing unit executing instructions stored in a storage unit of the electronic control device the method comprising” amounts to nothing more than mere instructions to apply the exception using a generic computer component and generally link the use of the judicial exception to a technological environment. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “acquiring, via an in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor, the first external environment sensor and second external environment sensor being incorporated in the vehicle, the detection information including sensor observation information and probability of presence values, and storing the detection information in the storage unit as a sensor detection information data group” the examiner submits that these limitations are insignificant extra-solution activities. Hence, the claim is not patent eligible.
Therefore claim 13 is ineligible under 35 USC 101.
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 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.
Claim 1, 3-8, and 10-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Akiyama (US-20200225342) in view of Honda (US-7054467) and further in view of Xia (US-20230072637).
Regarding claim 1, Akiyama teaches an electronic control device incorporated in a vehicle, the electronic control device comprising (Paragraph [0012], "An object recognition device according to the present invention includes: first object detection means mounted on a vehicle and configured to detect a surrounding object around the vehicle")
a processing unit and a storage unit, the electronic control device being connected to an external environment sensor group via an in-vehicle network, the electronic control device comprising (Paragraph [0029], “The object recognition processing unit 1200 is composed of a processor 100 and a storage device 101, as shown in FIG. 2 which shows an example of hardware thereof.”) (Paragraph [0002], “detection results are transferred as sensor information to a vehicle control device via the in-vehicle network”)
a sensor detection information acquiring unit implemented by the processing unit that acquires, via the in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor (Paragraph [0027], "The object recognition device includes a first object detection unit 1101, a second object detection unit 1102, and an object recognition processing unit 1200")
the detection information including sensor observation information (Paragraph [0028], “The first object detection unit 1101 is composed of a device such as a camera or a light detection and ranging (lidar) device, which is capable of acquiring an object detection position and in addition, object width information.”)
the first and second environment sensors being incorporated in the vehicle (Abstract, “object recognition device of a vehicle”) (See Figures 4A-5D)
a sensor detection information integrating unit implemented by the processing unit (See Figures 1 and 2, Figure 1 showing various units such as “Association processing unit” that are implemented by a processor as shown in figure 2)
that generates integrated detection information by comparing and integrating the detection information of the first and second external environment sensors to specify a correspondence relationship between environmental elements, the integrated detection information being stored in the storage unit as an integrated detection information data group (Paragraph [0012], “an association processing unit configured to take an association between the first object detection result and the second object detection result in an area excluding the occlusion area determined by the occlusion area detection processing unit “) (Paragraph [0038], "Next, the association between an object detection result of the first object detection unit 1101 for which the occlusion area has been determined as described above, and an object detection result of the second object detection unit 1102, is determined by the association processing unit 1202," here the association processing unit is integrating detection information from the first detection result and the second detection result to determine an association/correspondence relationship between object detections) (See Figures 1 and 2 which shows the functions of the association processing unit implemented by a processor and storage)
and indicating environmental elements detected by the first environmental sensor and the second external environment sensor and for which the correspondence relationship is specified (Paragraph [0038], “the association between each object detection result of the first object detection unit 1101 and each object detection result of the second object detection unit 1102 is determined, and the detection results that exhibit a great association are combined,” here the environmental elements/objects that are detected by both sensors are associated/combined)
a sensor detectable area determining unit implemented by the processing unit that determines a relationship between a relative position and a detection capability at the first external environment sensor (Paragraph [0034], "The number of occlusion areas is one in FIG. 4B, but in the case where there are a plurality of (n) surrounding objects, the above processing is performed for all the object detection results of the first object detection unit 1101, to determine occlusion areas Q1 to Qn for the first object detection unit 1101.") (See Figures 5B-5D)
based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor the state of detection being indicated in the integrated detection information (See Figure 3, steps S3-S5, here the figure shows the system determining object detectable area from a first object detection result, and then determine second object detectable area for the second object detection, and then determine an association possible area from the two separate object detection results in which object can be detected by both sensors)
generates a detectable area for the first external environment sensor (See Figure 5C and 5D showing the system determining detectable areas and occlusion areas for the sensors)
the state of detection being indicated in the integrated detection information (Paragraph [0041], “The update processing unit 1203 determines that the object detection result of the first object detection unit 1101 and the object detection result of the second object detection unit 1102 that are combined with each other in the association processing by the association processing unit 1202 correspond to an identical object, and integrates the detection information therebetween, thereby specifying (recognizing) the position of each of the surrounding objects 20a, 20b, 20c and updating the recognition result for the specified object (step S7),” here the system is updating the recognition result/state of detection in the integrated detection information)
and determines a detectable area for the first external environment sensor based on change in the state of detection indicated by the integrated detection information (Paragraph [0032], “FIG. 4A shows a detection area P of the first object detection unit 1101 when there is no object around the own vehicle 10. In this case, the first object detection unit 1101 can detect all objects in the detection area P, and no occlusion area occurs. Next, FIG. 4B shows a state in which there is a surrounding object 20 in the detection area P. In this case, the surrounding object 20 becomes an obstacle to cause an area (occlusion area Q1) where the first object detection unit 1101 cannot perform detection,” here the system is determining a detectable area for a first sensor based on a change of state from no object detected to an object being detected which forms an occlusion area) (See also figures 5B-5D) (Paragraph [0035], “In the determination for the occlusion area, margins Mx, My may be set in accordance with object detection error in the X-axis direction or the Y-axis direction in the first object detection unit 1101, whereby the condition A and the condition B may be respectively changed into a condition A′ and a condition B′ as shown below, so as to narrow the occlusion area. It is noted that the margins Mx, My are set as positive values,” here the system is determining the detectable area outside of the occlusion area and is updating that area based on changing states of objects according to the integrated detection results of the first and second object detection units).
However Akiyama does not explicitly teach generates a detectable area for the first external environment sensor as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment sensor in each unit area, determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor.
Honda teaches an information processing apparatus and method which readily enable integration of information pieces output from sensors including
generates a detectable area for the first external environment sensor as a grid map stored in the storage unit as a sensor detectable area data group (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area)
the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment sensor in each unit area (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map with polar coordinates and the vehicle and sensor at the center of the area, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area) (Column 18, lines 30-35, “The two-dimensional coordinate system may be either a rectangular coordinate system or a polar coordinate system.”) (See Figures 11A and 11B showing two separate polar coordinate systems each having a center at the location of the separate sensors)
determines a detection capability level in each unit area of the grid map (See figure 4 showing reliability information for the sensor for each unit of the grid like map) (See Figure 11A and 11B showing the state detection for each grid section for a plurality of sensors)
based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor (Column 25, lines 25-35, “In the example shown in FIG. 9, the parameter integration section 15 is arranged so as to enable integration of the detection information DS output from the sensor 11A and the detection information DS output from the sensor 11B.” here as can be seen in figure 11B the detection capability level is determined for each unit area of the grid map using the state of detection of a first and second sensor).
Akiyama and Honda are analogous art as they are both generally related to systems for processing sensor information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include generates a detectable area for the first external environment sensor as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment sensor in each unit area, determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor of Honda in the system for determining a detectable area of Akiyama with a reasonable expectation of success in order to convert the various sensor parameters to a single format in order to make the information interchangeable and therefore ease integration and reducing manufacturing costs (Column 3, lines 15-25 “The information processing apparatus includes the parameter conversion means. Hence, the format of the information given to the parameter integration means is made interchangeable, without regard to the format of information output from the sensor means. As a result, detection information can be integrated through use of parameter integration means of single construction, without regard to the combination of sensor means. Hence, the versatility of the parameter integration means is improved, thereby curtailing costs for manufacturing the information processing apparatus.”).
However the combination does not explicitly teach probability-of-presence values as stored in a sensor detection information data group in the storage unit.
Xia teaches a vehicle drivable area detection method, an autonomous driving assistance system, and an autonomous driving vehicle including
probability-of-presence values as stored in a sensor detection information data group in the storage unit (Paragraph [0005], “image data obtained by a camera apparatus, to obtain a first probability distribution of an obstacle; obtaining a second probability distribution of the obstacle based on a time of flight and an echo width of a radar echo signal; and obtaining, based on the first probability distribution of the obstacle and the second probability distribution of the obstacle, a drivable area of a vehicle represented by a probability, where the probability indicates a probability that the vehicle cannot drive through the area,” here the system is determining a probability of presence for an obstacle using each of a plurality of sensors).
Akiyama, Honda, and Xia are analogous art as they are both generally related to systems for processing sensor information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include probability-of-presence values as stored in a sensor detection information data group in the storage unit of Xia in the system for determining a detectable area of Akiyama and Honda with a reasonable expectation of success in order to improve the autonomous driving reliability by accurately determining the probability of obstacles and the associated driving range around a vehicle (Paragraph [0033], “so that a drivable range around the vehicle can be accurately recognized, a new solution is provided for the vehicle drivable area detection method, and support is provided for improving autonomous driving reliability and optimizing driving experience of a user”).
Regarding claim 3, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claim 1, Akiyama further teaches wherein the sensor detectable area determining unit determines a relationship between a relative position and a detection capability at the first external environment sensor (Paragraph [0032], “FIG. 4A shows a detection area P of the first object detection unit 1101 when there is no object around the own vehicle 10. In this case, the first object detection unit 1101 can detect all objects in the detection area P, and no occlusion area occurs. Next, FIG. 4B shows a state in which there is a surrounding object 20 in the detection area P. In this case, the surrounding object 20 becomes an obstacle to cause an area (occlusion area Q1) where the first object detection unit 1101 cannot perform detection,” here the system is determining a relationship between the position of the sensor and detection capability which forms occlusion zones for the first sensor)
based on a detection position at which a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor has changed (Paragraph [0050], “When the first object detection unit 1101 detects an object at time t1+Δt, the prediction processing unit 2204 reads the object recognition result for time t1 recorded in the prediction processing unit 2204, and calculates an object prediction result obtained by shifting the read object recognition result to time t1+Δt at which the first object detection unit 1101 detects the object.”) (Paragraph [0051], “As shown in FIG. 8, the second association processing unit 2202 determines, as an association possible area TA, a range in which the object prediction result of the prediction processing unit 2204 described above and the detectable area PA of the first object detection unit 1101 overlap each other (step S9),” here when the system detects an environmental element that has changed position/state at a future time the system can determine that the object has moved by predicting the future state of the object and adjusting the detectable area based on the movement)
the detection position being indicated in time series data of the integrated detection information (Paragraph [0050], “When the first object detection unit 1101 detects an object at time t1+Δt,” here the object detections are recorded as time based data t1 and t1+Δt).
Regarding claim 4, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claim 1, Akiyama further teaches wherein the sensor detectable area determining unit also estimates a cause by which a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor has changed and based on the estimated cause, determines a relationship between a relative position and a detection capability at the first external environment sensor (Paragraph [0040], “On the other hand, as shown in FIG. 5C, in the case where the first object detection unit 1101 detects the surrounding objects 20a, 20b, 20c in front of the own vehicle 10, as described in FIG. 4B, the surrounding objects 20a, 20b, 20c become obstacles and thus occlusion areas Q2, Q3 for which the first object detection unit 1101 cannot perform detection, occur.”) (See Figures 5B - 5D, figure 5B shows all of the objects detected by the second sensor, Figure 5C shows some objects detected by the first sensor and object that are causing occlusion areas inhibiting detection of some objects).
Regarding claim 5, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claim 1, Akiyama further teaches wherein a relationship between the relative position and the detection capability is expressed as a combination of a detectable distance and a detectable angle range (See Figures 5B-5D showing a distance and angle range for each sensor)
and the sensor detectable area determining unit estimates whether a cause of change in the state of detection is a cause related to a detection distance or a cause related to a detection angle (Paragraph [0040], “As shown in FIG. 5D, the association processing unit 1202 determines, as an association possible area SA, a range in which the detectable area PA of the first object detection unit 1101 and the detectable area RA of the second object detection unit 1102 overlap each other (step S5). Then, for the surrounding objects 20a, 20b, 20c detected in the association possible area SA, the association processing unit 1202 compares object detection results of the first object detection unit 1101 and object detection results of the second object detection unit 1102, and as described above, combines the object detection results between which the difference in the distances to the respective detected objects is the smallest (step S6),” the system determines and area which comprises a range and angle and determines an overlap area between the two sensor angles and ranges determines if objects are detectable)
determines a detectable distance for the first external environment sensor, based on the estimated cause related to the detection distance (See Figures 5B-5D showing a distance and angle range for each sensor)
and determines a detectable angle range for the first external environment sensor, based on the estimated cause related to the detection angle (See Figures 5B-5D showing a distance and angle range for each sensor).
Regarding claim 6, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claim 1, Akiyama further teaches wherein the sensor detectable area determining unit estimates whether a cause of change in the state of detection is occlusion by a different obstacle and does not use information indicating the estimated cause being occlusion by the different obstacle, as information for determining a relationship between a relative position and a detection capability at the first external environment sensor (Paragraph [0043], “in embodiment 1 according to the present invention, associations are taken for only the association possible area excluding the occlusion area, whereby association is suppressed, and further, a different object present in the occlusion area is prevented from being determined to be an identical object. Thus, the possibility of occurrence of an object recognition result based on an erroneous combination (erroneous association) can be decreased,” here the system can determine whether an associated object is within an occlusion area and suppresses association of a different occluded object from being associated with the original object).
Regarding claim 7, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claim 1, Akiyama further teaches wherein the sensor detectable area determining unit determines detection reliability of the first external environment sensor (Paragraph [0031], “An object detection position measured by the first object detection unit 1101 and object detection position accuracy information thereof are outputted as an object detection position signal and an object detection position accuracy signal,” here the system can determine a detection reliability/accuracy of the first sensor)
by comparing detection position information from the first external environment sensor about detection of the environmental element with detection position information from the second external environment sensor about detection of the environmental element, and determines a state of detection by the first external environment sensor, based on the detection reliability (Paragraph [0041], “combines the object detection results between which the difference in the distances to the respective detected objects is the smallest. The update processing unit 1203 determines that the object detection result of the first object detection unit 1101 and the object detection result of the second object detection unit 1102 that are combined with each other in the association processing by the association processing unit 1202 correspond to an identical object, and integrates the detection information therebetween, thereby specifying (recognizing) the position of each of the surrounding objects 20a, 20b, 20c and updating the recognition result for the specified object (step S7)” here the system can merge the object detection results from the first and second environment sensors to determine if the same objects are being detected and determines the updated recognition for the objects and increasing the reliability/accuracy).
Regarding claim 8, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claim 1, Akiyama further teaches a vehicle control information generating unit that generates control information on the vehicle based on a detectable area for the first external environment sensor, the detectable area being determined by the sensor detectable area determining unit, and on the integrated detection information (Paragraph [0042], “Using information about the recognized relative positions between the own vehicle 10 and the surrounding objects 20a, 20b, 20c around the own vehicle obtained from the object recognition processing unit 1200 as described above, the vehicle control unit 1300 performs control for a collision damage mitigation brake system for mitigating a damage when the own vehicle 10 collides with a frontward object, an adaptive cruise control system for following a frontward vehicle, and the like. That is, it is possible to perform autonomous driving of the own vehicle on the basis of an object recognition result from the object recognition processing unit 1200.”).
Regarding claim 10, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claims 1, Akiyama further teaches wherein when a state of detection by the first external environment sensor is detection failure, the sensor detectable area determining unit reduces a detection capability level in a unit area corresponding to a position in a detectable area for the first external environment sensor, the position being indicated in the integrated detection information (See Figures 4B-5D showing occlusion areas in which a detection state for a first sensor in unavailable/failed, these areas are shown as occlusion areas and reduced detection areas).
Regarding claim 11, the combination of Akiyama, Honda, and Xia teaches the system as discussed above in claims 1 and 9, Akiyama does not explicitly teach wherein the grid map is created by dividing an area into grid patterns on a polar coordinate system, the area having an installation point of the first external environment sensor at a center of the area.
However Honda teaches wherein the grid-like map is created by dividing an area into grid-like patterns on a polar coordinate system, the area having an installation point of the first external environment sensor at a center of the area (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map with polar coordinates and the vehicle and sensor at the center of the area, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area) (Column 18, lines 30-35, “The two-dimensional coordinate system may be either a rectangular coordinate system or a polar coordinate system.”).
Akiyama and Honda are analogous art as they are both generally related to systems for processing sensor information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein the grid-like map is created by dividing an area into grid-like patterns on a polar coordinate system, the area having an installation point of the first external environment sensor at a center of the area of Honda in the system for determining a detectable area of Akiyama with a reasonable expectation of success in order to convert the various sensor parameters to a single format in order to make the information interchangeable and therefore ease integration and reducing manufacturing costs (Column 3, lines 15-25 “The information processing apparatus includes the parameter conversion means. Hence, the format of the information given to the parameter integration means is made interchangeable, without regard to the format of information output from the sensor means. As a result, detection information can be integrated through use of parameter integration means of single construction, without regard to the combination of sensor means. Hence, the versatility of the parameter integration means is improved, thereby curtailing costs for manufacturing the information processing apparatus.”).
Regarding claim 12, Akiyama teaches an electronic control device incorporated in a vehicle, comprising: (Paragraph [0012], "An object recognition device according to the present invention includes: first object detection means mounted on a vehicle and configured to detect a surrounding object around the vehicle")
a processing unit and a storage unit, the electronic control device being connected to an external environment sensor group via an in-vehicle network, the electronic control device comprising (Paragraph [0029], “The object recognition processing unit 1200 is composed of a processor 100 and a storage device 101, as shown in FIG. 2 which shows an example of hardware thereof.”) (Paragraph [0002], “detection results are transferred as sensor information to a vehicle control device via the in-vehicle network”)
a sensor detection information acquiring unit implemented by the processing unit that acquires, via the in-vehicle network, detection information from each of a plurality of external environment sensors with different detection ranges (Paragraph [0027], "The object recognition device includes a first object detection unit 1101, a second object detection unit 1102, and an object recognition processing unit 1200") (See figures 5B-5D showing different detection ranges) (Paragraph [0002], “detection results are transferred as sensor information to a vehicle control device via the in-vehicle network”)
the detection information including sensor observation information (Paragraph [0028], “The first object detection unit 1101 is composed of a device such as a camera or a light detection and ranging (lidar) device, which is capable of acquiring an object detection position and in addition, object width information.”)
the external environment sensors being incorporated in the vehicle (Abstract, “object recognition device of a vehicle”) (See Figures 4A-5D)
a sensor detection information integrating unit implemented by the processing unit that (See Figures 1 and 2, Figure 1 showing various units such as “Association processing unit” that are implemented by a processor as shown in figure 2)
generates integrated detection information by comparing and integrating the detection information of the plurality of external environment sensors to specify correspondence relationships between environmental elements detected by the plurality of external environment sensors, the integrated detection information being stored in the storage unit as an integrated detection information data group (Paragraph [0012], “an association processing unit configured to take an association between the first object detection result and the second object detection result in an area excluding the occlusion area determined by the occlusion area detection processing unit “) (Paragraph [0038], "Next, the association between an object detection result of the first object detection unit 1101 for which the occlusion area has been determined as described above, and an object detection result of the second object detection unit 1102, is determined by the association processing unit 1202," here the association processing unit is integrating detection information from the first detection result and the second detection result to determine an association/correspondence relationship between object detections) (See Figures 1 and 2 which shows the functions of the association processing unit implemented by a processor and storage)
and a sensor detectable area determining unit implemented by the processing unit that compares detection results in an overlapping area of detection ranges of the plurality of external environment sensors indicated by the integrated detection information (Paragraph [0034], "The number of occlusion areas is one in FIG. 4B, but in the case where there are a plurality of (n) surrounding objects, the above processing is performed for all the object detection results of the first object detection unit 1101, to determine occlusion areas Q1 to Qn for the first object detection unit 1101.") (See Figure 5C and 5D showing the system determining detectable areas and occlusion areas for the sensors) (See Figure 3, steps S3-S5, here the figure shows the system determining object detectable area from a first object detection result, and then determine second object detectable area for the second object detection, and then determine an association possible area from the two separate object detection results in which object can be detected by both sensors) (See Figure 3, steps S3-S5, here the figure shows the system determining object detectable area from a first object detection result, and then determine second object detectable area for the second object detection, and then determine an association possible area from the two separate object detection results in which object can be detected by both sensors)
and determines an effective detection range for at least one of the external environment sensors (See Figure 5C and 5D showing the system determining detectable areas and occlusion areas for the sensors)
the state of detection being indicated in the integrated detection information (Paragraph [0041], “The update processing unit 1203 determines that the object detection result of the first object detection unit 1101 and the object detection result of the second object detection unit 1102 that are combined with each other in the association processing by the association processing unit 1202 correspond to an identical object, and integrates the detection information therebetween, thereby specifying (recognizing) the position of each of the surrounding objects 20a, 20b, 20c and updating the recognition result for the specified object (step S7),” here the system is updating the recognition result/state of detection in the integrated detection information).
However Akiyama does not explicitly teach determines an effective detection range for at least one of the external environment sensors as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the at least one external environment sensor at a center of the area to express a detection capability level of the at least one external environment sensor in each unit area, and that determines a detection capability level in each unit area of the grid map, based on a state of detection by the at least one external environment sensor of an environmental element detected by another one of the plurality of external environment sensors.
Honda teaches an information processing apparatus and method which readily enable integration of information pieces output from sensors including
determines an effective detection range for at least one of the external environment sensors as a grid map stored in the storage unit as a sensor detectable area data group (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area)
the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the at least one external environment sensor at a center of the area to express a detection capability level of the at least one external environment sensor in each unit area (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map with polar coordinates and the vehicle and sensor at the center of the area, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area) (Column 18, lines 30-35, “The two-dimensional coordinate system may be either a rectangular coordinate system or a polar coordinate system.”) (See Figures 11A and 11B showing two separate polar coordinate systems each having a center at the location of the separate sensors)
and that determines a detection capability level in each unit area of the grid map (See figure 4 showing reliability information for the sensor for each unit of the grid like map) (See Figure 11A and 11B showing the state detection for each grid section for a plurality of sensors)
based on a state of detection by the at least one external environment sensor of an environmental element detected by another one of the plurality of external environment sensors (Column 25, lines 25-35, “In the example shown in FIG. 9, the parameter integration section 15 is arranged so as to enable integration of the detection information DS output from the sensor 11A and the detection information DS output from the sensor 11B.” here as can be seen in figure 11B the detection capability level is determined for each unit area of the grid map using the state of detection of a first and second sensor).
Akiyama and Honda are analogous art as they are both generally related to systems for processing sensor information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include determines an effective detection range for at least one of the external environment sensors as a grid map stored in the storage unit as a sensor detectable area data group, the grid map being created by dividing an area into grid patterns on a polar coordinate system having an installation point of the at least one external environment sensor at a center of the area to express a detection capability level of the at least one external environment sensor in each unit area, and that determines a detection capability level in each unit area of the grid map, based on a state of detection by the at least one external environment sensor of an environmental element detected by another one of the plurality of external environment sensors of Honda in the system for determining a detectable area of Akiyama with a reasonable expectation of success in order to convert the various sensor parameters to a single format in order to make the information interchangeable and therefore ease integration and reducing manufacturing costs (Column 3, lines 15-25 “The information processing apparatus includes the parameter conversion means. Hence, the format of the information given to the parameter integration means is made interchangeable, without regard to the format of information output from the sensor means. As a result, detection information can be integrated through use of parameter integration means of single construction, without regard to the combination of sensor means. Hence, the versatility of the parameter integration means is improved, thereby curtailing costs for manufacturing the information processing apparatus.”).
However the combination does not explicitly teach probability-of-presence values and being stored in the storage unit as a sensor detection information data group.
Xia teaches a vehicle drivable area detection method, an autonomous driving assistance system, and an autonomous driving vehicle including
probability-of-presence values and being stored in the storage unit as a sensor detection information data group (Paragraph [0005], “image data obtained by a camera apparatus, to obtain a first probability distribution of an obstacle; obtaining a second probability distribution of the obstacle based on a time of flight and an echo width of a radar echo signal; and obtaining, based on the first probability distribution of the obstacle and the second probability distribution of the obstacle, a drivable area of a vehicle represented by a probability, where the probability indicates a probability that the vehicle cannot drive through the area,” here the system is determining a probability of presence for an obstacle using each of a plurality of sensors).
Akiyama, Honda, and Xia are analogous art as they are both generally related to systems for processing sensor information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include probability-of-presence values and being stored in the storage unit as a sensor detection information data group of Xia in the system for determining a detectable area of Akiyama and Honda with a reasonable expectation of success in order to improve the autonomous driving reliability by accurately determining the probability of obstacles and the associated driving range around a vehicle (Paragraph [0033], “so that a drivable range around the vehicle can be accurately recognized, a new solution is provided for the vehicle drivable area detection method, and support is provided for improving autonomous driving reliability and optimizing driving experience of a user”).
Regarding claim 13, Akiyama teaches a control method by an electronic control device incorporated in a vehicle (Paragraph [0012], "An object recognition device according to the present invention includes: first object detection means mounted on a vehicle and configured to detect a surrounding object around the vehicle")
the method being implemented by a processing unit executing instructions stored in a storage unit of the electronic control device the method comprising (Paragraph [0029], “The object recognition processing unit 1200 is composed of a processor 100 and a storage device 101, as shown in FIG. 2 which shows an example of hardware thereof.”)
acquiring, via an in-vehicle network, detection information from a first external environment sensor and detection information from a second external environment sensor (Paragraph [0027], "The object recognition device includes a first object detection unit 1101, a second object detection unit 1102, and an object recognition processing unit 1200") (Paragraph [0002], “detection results are transferred as sensor information to a vehicle control device via the in-vehicle network”)
the first external environment sensor and second external environment sensor being incorporated in the vehicle (Abstract, “object recognition device of a vehicle”) (See Figures 4A-5D)
the detection information including sensor observation information (Paragraph [0028], “The first object detection unit 1101 is composed of a device such as a camera or a light detection and ranging (lidar) device, which is capable of acquiring an object detection position and in addition, object width information.”)
generating, by comparing and integrating the detection information of the first and second external environment sensors, integrated detection information that specifies a correspondence relationship between environmental elements detected by the first external environment sensor and the second external environment sensor, and storing the integrated detection information in the storage unit as an integrated detection information data group (Paragraph [0012], “an association processing unit configured to take an association between the first object detection result and the second object detection result in an area excluding the occlusion area determined by the occlusion area detection processing unit “) (Paragraph [0038], "Next, the association between an object detection result of the first object detection unit 1101 for which the occlusion area has been determined as described above, and an object detection result of the second object detection unit 1102, is determined by the association processing unit 1202," here the association processing unit is integrating detection information from the first detection result and the second detection result to determine an association/correspondence relationship between object detections) (See Figures 1 and 2 which shows the functions of the association processing unit implemented by a processor and storage)
determining, based on a state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor as indicated in the integrated detection information, a relationship between a relative position and a detection capability at the first external environment sensor (Paragraph [0034], "The number of occlusion areas is one in FIG. 4B, but in the case where there are a plurality of (n) surrounding objects, the above processing is performed for all the object detection results of the first object detection unit 1101, to determine occlusion areas Q1 to Qn for the first object detection unit 1101.") (See Figures 5B-5D) (See Figure 3, steps S3-S5, here the figure shows the system determining object detectable area from a first object detection result, and then determine second object detectable area for the second object detection, and then determine an association possible area from the two separate object detection results in which object can be detected by both sensors)
generating a detectable area for the first external environment sensor (See Figure 5C and 5D showing the system determining detectable areas and occlusion areas for the sensors)
the state of detection being indicated in the integrated detection information (Paragraph [0041], “The update processing unit 1203 determines that the object detection result of the first object detection unit 1101 and the object detection result of the second object detection unit 1102 that are combined with each other in the association processing by the association processing unit 1202 correspond to an identical object, and integrates the detection information therebetween, thereby specifying (recognizing) the position of each of the surrounding objects 20a, 20b, 20c and updating the recognition result for the specified object (step S7),” here the system is updating the recognition result/state of detection in the integrated detection information)
and determining a detectable area for the first external environment sensor based on a change in the state of detection indicated by the integrated detection information (Paragraph [0032], “FIG. 4A shows a detection area P of the first object detection unit 1101 when there is no object around the own vehicle 10. In this case, the first object detection unit 1101 can detect all objects in the detection area P, and no occlusion area occurs. Next, FIG. 4B shows a state in which there is a surrounding object 20 in the detection area P. In this case, the surrounding object 20 becomes an obstacle to cause an area (occlusion area Q1) where the first object detection unit 1101 cannot perform detection,” here the system is determining a detectable area for a first sensor based on a change of state from no object detected to an object being detected which forms an occlusion area) (See also figures 5B-5D) (Paragraph [0035], “In the determination for the occlusion area, margins Mx, My may be set in accordance with object detection error in the X-axis direction or the Y-axis direction in the first object detection unit 1101, whereby the condition A and the condition B may be respectively changed into a condition A′ and a condition B′ as shown below, so as to narrow the occlusion area. It is noted that the margins Mx, My are set as positive values,” here the system is determining the detectable area outside of the occlusion area and is updating that area based on changing states of objects according to the integrated detection results of the first and second object detection units).
However Akiyama does not explicitly teach generating a detectable area for the first external environment sensor as a grid map created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment in each unit area, determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor.
Honda teaches an information processing apparatus and method which readily enable integration of information pieces output from sensors including
generating a detectable area for the first external environment sensor as a grid map (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area)
created by dividing an area into grid patterns on a polar coordinate system having an installation point of the at least one external environment sensor at a center of the area to express a detection capability level of the at least one external environment sensor in each unit area and storing the grid map in the storage unit as a sensor detectable area data group (See Figures 3-4, figure 3 showing the area around the vehicle divided into a grid like map with polar coordinates and the vehicle and sensor at the center of the area, and figure 4 expressing a detection capability for the area in front of the vehicle for each unit area) (Column 18, lines 30-35, “The two-dimensional coordinate system may be either a rectangular coordinate system or a polar coordinate system.”) (See Figures 11A and 11B showing two separate polar coordinate systems each having a center at the location of the separate sensors)
determining a detection capability level in each unit area of the grid map (See figure 4 showing reliability information for the sensor for each unit of the grid like map) (See Figure 11A and 11B showing the state detection for each grid section for a plurality of sensors)
based on a state of detection by the first external environment sensor of the environmental element detected by the second external environment sensor (Column 25, lines 25-35, “In the example shown in FIG. 9, the parameter integration section 15 is arranged so as to enable integration of the detection information DS output from the sensor 11A and the detection information DS output from the sensor 11B.” here as can be seen in figure 11B the detection capability level is determined for each unit area of the grid map using the state of detection of a first and second sensor).
Akiyama and Honda are analogous art as they are both generally related to systems for processing sensor information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include generating a detectable area for the first external environment sensor as a grid map created by dividing an area into grid patterns on a polar coordinate system having an installation point of the first external environment sensor at a center of the area to express a detection capability level of the first external environment in each unit area, determines a detection capability level in each unit area of the grid map, based on the state of detection by the first external environment sensor of an environmental element detected by the second external environment sensor of Honda in the system for determining a detectable area of Akiyama with a reasonable expectation of success in order to convert the various sensor parameters to a single format in order to make the information interchangeable and therefore ease integration and reducing manufacturing costs (Column 3, lines 15-25 “The information processing apparatus includes the parameter conversion means. Hence, the format of the information given to the parameter integration means is made interchangeable, without regard to the format of information output from the sensor means. As a result, detection information can be integrated through use of parameter integration means of single construction, without regard to the combination of sensor means. Hence, the versatility of the parameter integration means is improved, thereby curtailing costs for manufacturing the information processing apparatus.”).
However the combination does not explicitly teach probability of presence values, and storing the detection information in the storage unit as a sensor detection information data group.
Xia teaches a vehicle drivable area detection method, an autonomous driving assistance system, and an autonomous driving vehicle including
probability of presence values, and storing the detection information in the storage unit as a sensor detection information data group (Paragraph [0005], “image data obtained by a camera apparatus, to obtain a first probability distribution of an obstacle; obtaining a second probability distribution of the obstacle based on a time of flight and an echo width of a radar echo signal; and obtaining, based on the first probability distribution of the obstacle and the second probability distribution of the obstacle, a drivable area of a vehicle represented by a probability, where the probability indicates a probability that the vehicle cannot drive through the area,” here the system is determining a probability of presence for an obstacle using each of a plurality of sensors).
Akiyama, Honda, and Xia are analogous art as they are both generally related to systems for processing sensor information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include probability of presence values, and storing the detection information in the storage unit as a sensor detection information data group of Xia in the system for determining a detectable area of Akiyama and Honda with a reasonable expectation of success in order to improve the autonomous driving reliability by accurately determining the probability of obstacles and the associated driving range around a vehicle (Paragraph [0033], “so that a drivable range around the vehicle can be accurately recognized, a new solution is provided for the vehicle drivable area detection method, and support is provided for improving autonomous driving reliability and optimizing driving experience of a user”).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Grauer (US-20160350601) teaches a processing unit enhances the captured images with stored imaging data according to a correspondence of metadata with vehicle situations, for example, according to a relation between capturing parameters of different sensing units. Mori (US-20230011475) teaches an object recognition device comprising a plurality of sensors and determines an association between a detected object with secondary position data. Steyer (US-20210394761) teaches detecting an object with camera data and sensor data and determining a degree of overlap between the camera data and sensor data for a plurality of distances.
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.
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/CHRISTOPHER GEORGE FEES/Examiner, Art Unit 3662
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