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 . This office action is in response to an amendment filed on 3/19/2026. Claims 1-7 are pending.
Response to Amendment
Amendments filed on 3/19/2026 are under consideration. Claims 1, and 7 are amended. Claim Rejections - 35 USC § 112, are removed upon correction.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/19/2026 has been entered.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: a dangerous zone determination unit configured to determine a dangerous zone within a driving region included in a driving region in claim 1.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. See at least,
[0040] – “The arithmetic operation unit 32 includes one or more processors. The arithmetic operation unit 32 can include a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). The arithmetic operation unit 32 can read the programs and the data stored in the storage unit 30. The arithmetic operation unit 32 includes an information acquisition unit 40, a dangerous zone determination unit 42, and a driving route creation unit 44.”
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
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.
Claims 1 & 7 are rejected under 35 U.S.C. 103 as being unpatentable over Kume (US20240308537A1) and in view of Bogovich (EP3303083A4) .
Regarding Claim 1 Kume teaches An instruction device (Pg. 15 – [0054] – “The automatic driving ECU 10 may appropriately generate this route in the same manner as in a route search of the navigation function” (equates to An instruction device as the ecu is used to instruction the vehicle with updated travel plans. )) configured to instruct an autonomous driving vehicle of a behavior plan including at least a driving route, (Pg. 15 – [0054] – “As the traveling plan, a long/intermediate-term traveling plan and a short-term traveling plan are generated. In the long/intermediate-term traveling plan, a route for directing the host vehicle to a set destination is generated” (equates to configured to instruct an autonomous driving vehicle of a behavior plan including at least a driving route as the quote shows a traveling plan being generated corresponding to a route to be taken by the vehicle)) the instruction device comprising: a dangerous zone determination unit configured to determine a dangerous zone within a driving region, (Pg. 13 – [0035] – “The peripheral monitoring sensor 15 monitors a peripheral environment of the host vehicle. By way of example, the peripheral monitoring sensor 15 detects an obstacle around the host vehicle, such as a moving object such as a pedestrian or another vehicle or a stationary object such as a fallen object on a road.” (equates to the instruction device comprising: a dangerous zone determination unit configured to determine a dangerous zone within a driving region, as the quote shows the obstacle detection being carried out and thus a dangerous zone to avoid via the detection is attained.) ) a driving route creation device configured to create a driving route and a storage unit storing actual driving data, (Pg. 12 – [0032] – “The map DB 13 is a nonvolatile memory storing therein the high-accuracy map data. The high-accuracy map data is map data higher in accuracy than map data used for route guidance provided by a navigation function. In the map DB 13, the map data used for the route guidance may also be stored.” (equates to a driving route creation device configured to create a driving route and a storage unit storing actual driving data, as the quote shows the storage of routes being provided within the map db 13 which can be provided to the user.) ) wherein the dangerous zone determination unit determines a dangerous zone included in a driving region (Pg. 18 – [0083] – “First, in Step Sl, when an obstacle is identified by the obstacle identification unit 111 (YES in Sl), the flow moves to Step S2. Meanwhile, when no obstacle is identified by the obstacle identification unit 111 (NO in Sl), the flow moves to Step S12. In Step S2, the avoidance measure identification unit 131 identifies the avoidance route” (equates to wherein the instruction device determines a dangerous zone included in a driving region as the quote shows the obstacle being identified and leads to a generation of an avoidance route and thus a dangerous zone in the driving region is established based on the obstacle detected. )) based on actual driving data obtained at a time of actual driving, (Pg. 14 – [0045] – “The driving environment recognition unit 101 recognizes a driving environment of the host vehicle from the host vehicle position acquired from the locator 12, the map data acquired from the map DB 13, and the sensing information acquired from the peripheral monitoring sensor 15. The driving environment recognition unit 101 corresponds to a driving environment identification unit. By way of example, the driving environment recognition unit 101 uses these information items to recognize a position, a shape, and a movement state of an object around the host vehicle and generate a virtual space that reproduces a real driving environment.” (equates to based on actual driving data obtained at a time of actual driving, as the quote shows the recognition unit being able to detect what is happening around the host vehicle in real time.)) when creating the driving route, the driving route creation device fixes a driving route in the dangerous zone to an actual driving route created based on the actual driving data, (Pg. 15 – [0054] – “As the traveling plan, a long/intermediate-term traveling plan and a short-term traveling plan are generated. In the long/intermediate-term traveling plan, a route for directing the host vehicle to a set destination is generated. This route is a route including a plurality of links. The automatic driving ECU 10 may appropriately generate this route in the same manner as in a route search of the navigation function” & See Also Pg. 15 – [0059] – “When an obstacle is identified by the obstacle identification unit 111, the avoidance measure identification unit 131 identifies a measure (hereinafter referred to as the avoidance measure) to allow the host vehicle to avoid the obstacle” (equates to when creating the driving route, the instruction device fixes a driving route in the dangerous zone to an actual driving route created based on the actual driving data as the first quote shows the setting of a long term driving plan wherein the vehicle executes based on route search and the second quote shows how while the vehicle is travelling along the path the actual driving data collected may include a detected obstacle and thus a dangerous zone was include in the actual driving route and the dangerous zone was collected based on actual driving data.) ) sets a driving route in a zone other than the dangerous zone as a predetermined driving route, (Pg. 15 – [0059] – “When an obstacle is identified by the obstacle identification unit 111, the avoidance measure identification unit 131 identifies a route (hereinafter referred to as the avoidance route) corresponding to the scheduled traveling path for the host vehicle that allows the obstacle to be avoided as the avoidance measure” & See Also Pg. 18 – [0084] – “In Step S4, the behavior determination unit 103 generates the scheduled traveling path corresponding to the avoidance route identified in S2 as the short-term traveling plan. Subsequently, the control execution unit 104 causes the host vehicle to automatically travel along the scheduled traveling path. In other words, by the driving in a region within the traffic regulations, the obstacle identified in Sl is avoided.” (equates to sets a driving route in a zone other than the dangerous zone as a predetermined driving route as the first quote shows the setting of a driving route that lies outside of the detected obstacle and thus outside of a zone that would cause harm to the host vehicle and the second quote showing that the avoidance route is sent to the vehicle to control the vehicle to travel along it and thus avoid the deemed dangerous zone.) ) and instructs the autonomous driving vehicle to follow a driving route configured by connecting a fixed actual driving route and the predetermined driving route so that they are continuous (Pg. 18 – [0084] – “In Step S4, the behavior determination unit 103 generates the scheduled traveling path corresponding to the avoidance route identified in S2 as the short-term traveling plan. Subsequently, the control execution unit 104 causes the host vehicle to automatically travel along the scheduled traveling path. In other words, by the driving in a region within the traffic regulations, the obstacle identified in Sl is avoided.” & see also Pg. 15 – [0054 & 0055] – “As the traveling plan, a long/intermediate-term traveling plan and a short-term traveling plan are generated. In the long/intermediate-term traveling plan, a route for directing the host vehicle to a set destination is generated. This route is a route including a plurality of links. The automatic driving ECU 10 may appropriately generate this route in the same manner as in a route search of the navigation function. This route search may appropriately be performed on the basis of cost calculation using, e.g., a Dijkstra method. [0055] In the short-term traveling plan, the behavior determination unit 103 uses a generated virtual space around the host vehicle to generate a scheduled traveling path for implementing traveling according to the long/intermediate term traveling plan. Specifically, the behavior determination unit 103 determines execution of steering for a lane change, acceleration/deceleration for speed adjustment, steering for avoiding an obstacle, braking, or the like.” (equates to and instructs the autonomous driving vehicle to follow a driving route configured by connecting the fixed actual driving route and the predetermined driving route so that they are continuous as the first quote shows the short term driving plan being set based on the avoidance route and thus being equivalent to the actual driving route and the second quote showing the short term driving route being one of links of the long term driving plan and thus the long term driving plan is the predetermined path wherein the inclusion of the avoidance route to the short term plan allows for the continuous travelling along the predetermined path and thus still avoids the marked dangerous zone while reaching the desired destination.))
Yet Kume fails to teach in advance of creating the driving route.
Bogovich teaches in advance of creating the driving route (Pg. 1 – Abstract – “A method is disclosed for analyzing historical accident information to adjust driving actions of an autonomous vehicle over a travel route in order to avoid accidents which have occurred over the travel route. Historical accident information for the travel route can be analyzed to, for example, determine accident types which occurred over the travel route and determine causes and/or probable causes of the accident types. In response to determining accident types and causes / probable causes of the accident types over the travel route, adjustments can be made to the driving actions planned for the autonomous vehicle over the travel route. In addition, in an embodiment, historical accident information can be used to analyze available travel routes and select a route which presents less risk of accident than others” (equates to in advance of creating the driving route as the quote shows the determination of a dangerous area in which the autonomous vehicle would pass through and by a risk score determination have the vehicle avoid the travel route entirely and choose a safer route for the vehicle to go along.)) It would have been an advantageous addition to the system disclosed by Kume to include in advance of creating the driving route as this allows for the vehicle to avoid dangerous zones before ever embarking on the route set out and ensure a safer path of travel is generated based on known information.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include in advance of creating the driving route as this limitation ensures the information of the environment is understood before proceeding along a route allowing for a dangerous zone to be avoided before the vehicle starts its path of travel.
Regarding Claim 7 Kume teaches A method of creating a driving route for an autonomous driving vehicle, (Pg. 10 – [0002] – “The present disclosure relates to a vehicle control device and vehicle control method” & See Also Pg. 15 – [0054] – “route for directing the host vehicle to a set destination is generated” & See Also Pg. 10 – [0004] – “A vehicle control device that performs automatic driving” (equates to A method of creating a driving route for an autonomous driving vehicle, as the first quote shows the art being a method, second showing the route generation capabilities of the art, and third quote showing the vehicle being an autonomous vehicle. )) the method comprising: an actual driving step of causing the autonomous driving vehicle to drive in a driving region and acquiring actual driving data obtained at a time of actual driving; (Pg. 14 – [0048] – “The driving environment recognition unit 101 may also perform determination of an automatic driving area (hereinafter referred to as the AD area) of the traveling region of the host vehicle” & See Also Pg. 15 – [0054] – “determines a traveling plan for traveling the host vehicle on the basis of a result of recognition of a driving environment by the driving environment recognition unit 101.” (equates to an actual driving step of causing the autonomous driving vehicle to drive in a driving region and acquiring actual driving data obtained at a time of actual driving; as the environmental recognition unit of this art can determine an autonomous driving region where the vehicle can travel autonomously and then a route can be generated for the vehicle to travel based on the environmental recognition unit’s determination. And t specifically the last quote shows the driving environment being recognize or sensed and thus the driving region can be detected at the time of driving. )) a dangerous zone determining step of determining, a dangerous zone included in the driving region; by collating the actual driving data with a threshold(Pg. 15 – [0059] – “he avoidance measure identification unit 131 identifies a measure (hereinafter referred to as the avoidance measure) to allow the host vehicle to avoid the obstacle. When an obstacle is identified by the obstacle identification unit 111, the avoidance measure identification unit 131 identifies a route (hereinafter referred to as the avoidance route) corresponding to the scheduled traveling path for the host vehicle that allows the obstacle to be avoided as the avoidance measure.” & See Also Pg. 15 – [0054] – “determines a traveling plan for traveling the host vehicle on the basis of a result of recognition of a driving environment by the driving environment recognition unit 101.” & See Also Pg. 14 – [0045] – “The driving environment recognition unit 101 recognizes a driving environment of the host vehicle from the host vehicle position acquired from the locator 12” & See Also Pg. 19 – [0098] – “identifies whether or not an obstacle is present within a predetermined range from a stop line… The predetermined range may optionally be settable. The predetermined range may appropriately be a range in which the obstacle described above presumably has a low possibility of preventing the host vehicle from passing…” (equates to a dangerous zone determining step of determining, a dangerous zone included in the driving region; by collating the actual driving data with a threshold as the first quote shows an avoidance measure identification unit that can identify obstacle or dangerous areas for the vehicle to travel within. It can perform this avoidance measure by way of the traveling path which is generated based on the real time information gathered from the environmental recognition unit of the second and third quotes where the environmental recognition unit can get real time driving data as seen from the last quote. The last quote specifically showing the obstacle detection and thus a dangerous zone being identified based on a threshold or a predetermined range of obstacle detection as set out of the environmental recognition unit of the host vehicle. )) and the driving route creating step of creating the driving route when the autonomous driving vehicle drives in the driving region (Pg. 15 – [0054] – “As the traveling plan, a long/intermediate-term traveling plan and a short-term traveling plan are generated. In the long/intermediate-term traveling plan, a route for directing the host vehicle to a set destination is generated… The automatic driving ECU 10 may appropriately generate this route in the same manner as in a route search of the navigation function” ) the driving route creating step including fixing a driving route in the dangerous zone to an actual driving route created based on the actual driving data, (Pg. 15 – [0054] – “As the traveling plan, a long/intermediate-term traveling plan and a short-term traveling plan are generated. In the long/intermediate-term traveling plan, a route for directing the host vehicle to a set destination is generated. This route is a route including a plurality of links. The automatic driving ECU 10 may appropriately generate this route in the same manner as in a route search of the navigation function” & See Also Pg. 15 – [0059] – “When an obstacle is identified by the obstacle identification unit 111, the avoidance measure identification unit 131 identifies a measure (hereinafter referred to as the avoidance measure) to allow the host vehicle to avoid the obstacle” (equates to when creating the driving route, the instruction device fixes a driving route in the dangerous zone to an actual driving route created based on the actual driving data as the first quote shows the setting of a long term driving plan wherein the vehicle executes based on route search and the second quote shows how while the vehicle is travelling along the path the actual driving data collected may include a detected obstacle and thus a dangerous zone was include in the actual driving route and the dangerous zone was collected based on actual driving data.) ) setting a driving route in a zone other than the dangerous zone as a predetermined driving route, Pg. 15 – [0059] – “When an obstacle is identified by the obstacle identification unit 111, the avoidance measure identification unit 131 identifies a route (hereinafter referred to as the avoidance route) corresponding to the scheduled traveling path for the host vehicle that allows the obstacle to be avoided as the avoidance measure” & See Also Pg. 18 – [0084] – “In Step S4, the behavior determination unit 103 generates the scheduled traveling path corresponding to the avoidance route identified in S2 as the short-term traveling plan. Subsequently, the control execution unit 104 causes the host vehicle to automatically travel along the scheduled traveling path. In other words, by the driving in a region within the traffic regulations, the obstacle identified in Sl is avoided.” (equates to sets a driving route in a zone other than the dangerous zone as a predetermined driving route as the first quote shows the setting of a driving route that lies outside of the detected obstacle and thus outside of a zone that would cause harm to the host vehicle and the second quote showing that the avoidance route is sent to the vehicle to control the vehicle to travel along it and thus avoid the deemed dangerous zone.) ) and connecting a fixed actual driving route and the predetermined driving route so that they are continuous(Pg. 18 – [0084] – “In Step S4, the behavior determination unit 103 generates the scheduled traveling path corresponding to the avoidance route identified in S2 as the short-term traveling plan. Subsequently, the control execution unit 104 causes the host vehicle to automatically travel along the scheduled traveling path. In other words, by the driving in a region within the traffic regulations, the obstacle identified in Sl is avoided.” & see also Pg. 15 – [0054 & 0055] – “As the traveling plan, a long/intermediate-term traveling plan and a short-term traveling plan are generated. In the long/intermediate-term traveling plan, a route for directing the host vehicle to a set destination is generated. This route is a route including a plurality of links. The automatic driving ECU 10 may appropriately generate this route in the same manner as in a route search of the navigation function. This route search may appropriately be performed on the basis of cost calculation using, e.g., a Dijkstra method. [0055] In the short-term traveling plan, the behavior determination unit 103 uses a generated virtual space around the host vehicle to generate a scheduled traveling path for implementing traveling according to the long/intermediate term traveling plan. Specifically, the behavior determination unit 103 determines execution of steering for a lane change, acceleration/deceleration for speed adjustment, steering for avoiding an obstacle, braking, or the like.” (equates to and instructs the autonomous driving vehicle to follow a driving route configured by connecting the fixed actual driving route and the predetermined driving route so that they are continuous as the first quote shows the short term driving plan being set based on the avoidance route and thus being equivalent to the actual driving route and the second quote showing the short term driving route being one of links of the long term driving plan and thus the long term driving plan is the predetermined path wherein the inclusion of the avoidance route to the short term plan allows for the continuous travelling along the predetermined path and thus still avoids the marked dangerous zone while reaching the desired destination.))
Yet Kume fails to teach in advance of a driving route creating step.
Bogvich teaches in advance of a driving route creating step. (Pg. 1 – Abstract – “A method is disclosed for analyzing historical accident information to adjust driving actions of an autonomous vehicle over a travel route in order to avoid accidents which have occurred over the travel route. Historical accident information for the travel route can be analyzed to, for example, determine accident types which occurred over the travel route and determine causes and/or probable causes of the accident types. In response to determining accident types and causes / probable causes of the accident types over the travel route, adjustments can be made to the driving actions planned for the autonomous vehicle over the travel route. In addition, in an embodiment, historical accident information can be used to analyze available travel routes and select a route which presents less risk of accident than others” (equates to in advance of creating the driving route as the quote shows the determination of a dangerous area in which the autonomous vehicle would pass through and by a risk score determination have the vehicle avoid the travel route entirely and choose a safer route for the vehicle to go along.)) It would have been an advantageous addition to the system disclosed by Kume to include in advance of creating the driving route as this allows for the vehicle to avoid dangerous zones before ever embarking on the route set out and ensure a safer path of travel is generated based on known information.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include in advance of creating the driving route as this limitation ensures the information of the environment is understood before proceeding along a route allowing for a dangerous zone to be avoided before the vehicle starts its path of travel.
Claim Rejections - 35 USC § 103
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.
Claims 2, 4, and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Kume-Bogovich in view of Zhixin (CN113928340A) .
Regarding Claim 2 Kume-Bogovich teaches (Kume Discloses the following limitations:) The instruction device according to claim 1, wherein the actual driving route is set at a position, (Pg. 15- [0054] – “determines a traveling plan for traveling the host vehicle on the basis of a result of recognition of a driving environment by the driving environment recognition unit 101.” & See Also Pg. 14 – [0045] – “The driving environment recognition unit 101 recognizes a driving environment of the host vehicle from the host vehicle position acquired from the locator 12” & See Also Pg. 12 – [0031] – “The locator 12 includes a GNSS (Global Navigation Satellite System) receiver and an inertial sensor. The GNSS receiver receives positioning signals from a plurality of positioning satellites” (equates to wherein the actual driving route is set at a position as the quotes show a traveling plan based on an environment recognition unit that utilizes positioning from the locator to give an actual position for the formulation of the driving route.))
Yet Kume fails to teach where the actual driving data exceeds a threshold, on the driving route.
Zhixin teaches where the actual driving data exceeds a threshold, on the driving route. (Pg. 1 – [11 , 12, 13] – “Determine the target expansion detection frame corresponding to each target obstacle information; According to each target expansion detection frame, the current position information of the target vehicle, and the lane boundary line information of the road to which the target vehicle belongs, determine at least one obstacle-avoiding driving path to be used corresponding to the target vehicle; The target obstacle avoidance travel path is determined according to the relative position information between each discrete point in each obstacle avoidance travel route to be used and each target expansion detection frame.” & See Also Pg. 10 – [62] – “Exemplarily, in practical applications, by judging whether the distance between each discrete point in the obstacle avoidance driving route to be used and each vertex of each target expansion detection frame is greater than a certain preset threshold, in order to enable the target vehicle to avoid the obstacle safely. The width of the target vehicle itself can be set as the threshold value, and the distance between each discrete point in the obstacle avoidance driving route to be used and each vertex of each target expansion detection frame can be set to be larger than the target vehicle's own width condition. As the target obstacle avoidance driving path” (equates to where the actual driving data exceeds a threshold, on the driving route as the first quote shows the detection of the obstacle in the path to be discretized into “target expansion detection frames” wherein the second quote shows the vehicle width being used as a threshold when exceeding it can the vehicle drive safely past the detected obstacle.) ). It would have been an advantageous addition to the device disclosed by Kume to include where the actual driving data exceeds a threshold, on the driving route as this limitation allows for a threshold distance around an obstacle to be provided and allows for a safe passage an easy route generation to be made based on a threshold distance away from a detected dangerous zone.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include where the actual driving data exceeds a threshold, on the driving route as having a threshold distance away from an obstacle allows for easy path generation to take place while always avoiding an obstacle based on the threshold utilized.
Regarding Claim 4 Kume-Zhixin teaches (Kume discloses the following limitations:) The instruction device according to claim 2, wherein the actual driving data is at least data of a yaw angular velocity or an acceleration in an up-down direction of the autonomous driving vehicle. (Pg. 12 – [0031] – “The locator 12 includes a GNSS (Global Navigation Satellite System) receiver and an inertial sensor. The GNSS receiver receives positioning signals from a plurality of positioning satellites. The inertial sensor includes, e.g., a gyro sensor and an acceleration sensor.” & See Also Pg. 14 – [0045] – “The driving environment recognition unit 101 recognizes a driving environment of the host vehicle from the host vehicle position acquired from the locator 12, the map data acquired from the map DB 13, and the sensing information acquired from the peripheral monitoring sensor 15. The driving environment recognition unit 101 corresponds to a driving environment identification unit. By way of example, the driving environment recognition unit 101 uses these information items to recognize a position, a shape, and a movement state of an object around the host vehicle and generate a virtual space that reproduces a real driving environment.” (equates to wherein the actual driving data is at least data of a yaw angular velocity or an acceleration in an up-down direction of the autonomous driving vehicle as the environmental recognition unit of this art is able to acquire real time data of the vehicle’s surroundings and the recognition unit includes an inertial sensor with both acceleration sensors and gyroscopes where the gyroscope can acquire the yaw angular velocity and the acceleration sensors can get the up and down acceleration of the vehicle. ))
Regarding Claim 5 Kume-Bogovich-Zhixin teaches (Kume discloses the following limitations:) The instruction device according to claim 2, wherein the behavior plan includes a driving condition for the autonomous driving vehicle, (Pg. 13 – [0036] – “The vehicle control ECU 16 is an electronic control device that controls driving of the host vehicle. As the driving control, acceleration/deceleration control” (equates to wherein the behavior plan includes a driving condition for the autonomous driving vehicle as the quote shows the driving being control and thus a behavior plan is formed wherein the acceleration is controlled within the driving operation which is equivalent a driving condition.)) and
Yet Kume fails to teach sets a driving condition based on the actual driving data at the position where the actual driving data exceeds the threshold.
Zhixin teaches sets a driving condition based on the actual driving data at the position where the actual driving data exceeds the threshold. (Pg. 14 – [79] – “Further, according to conditions such as the obstacle speed being less than a certain set threshold, the obstacle position is in front of the target vehicle, or the obstacle is within the preset area associated with the target vehicle, etc., the stationary obstacles around the driving path of the target vehicle are screened… set the maximum speed limit of the target vehicle when avoiding obstacles. Generally, in It can be set to 10m/s in urban road driving” & See Also Pg. 10 – [62] – “The width of the target vehicle itself can be set as the threshold value, and the distance between each discrete point in the obstacle avoidance driving route to be used and each vertex of each target expansion detection frame can be set to be larger than the target vehicle's own width condition. As the target obstacle avoidance driving path” (equates to sets a driving condition based on the actual driving data at the position where the actual driving data exceeds the threshold as the first quote shows the vehicle encounter with the obstacle within a given area being linked to setting a speed of the vehicle for the travel path and thus a driving condition is based on actual driving data, wherein the second quote shows the travel path being based on the threshold distance between the vehicle and obstacle wherein the distance exceeds the threshold and travel path is given accordingly. )) It would have been an advantageous addition to the system disclosed by Kume to include sets a driving condition based on the actual driving data at the position where the actual driving data exceeds the threshold as this limitation allows for setting a vehicle parameter when it is detected that a vehicle is outside the threshold range of colliding with an obstacle.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include sets a driving condition based on the actual driving data at the position where the actual driving data exceeds the threshold as this limitations allows for more control of setting a vehicle parameter while still avoiding detected obstacles.
Claims 3 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Kume-Bogovich-Zhixin and in further view of Taveria (US 10,717,435 B2).
Regarding Claim 3 Kume-Zhixin- Bogovich teaches The instruction device according to claim 2, as previously mapped above.
Yet Kume-Zhixin fails to disclose wherein a position where the actual driving data is equal to or less than the threshold is provided such that the actual driving route is changeable.
Taveira discloses wherein a position where the actual driving data is equal to or less than the threshold is provided such that the actual driving route is changeable. (Pg. 11 – Col. 4 – lines 27-31 – “…"proximity threshold" is used herein to refer to a minimum distance between an object and a robotic vehicle that a collision avoidance system will permit before controlling the robotic vehicle to stop or change a direction of travel away from the object.” (equates to wherein a position where the actual driving data is equal to or less than the threshold is provided such that the actual driving route is changeable as the art disclosed a proximity threshold distance in which the vehicle can go up until the path is then changed. Therefor if the vehicle is equal to or less than the threshold the path of the vehicle be changed to avoid collision.)) It would have been an advantageous addition to the system disclosed by Kume-Zhixin to include wherein a position where the actual driving data is equal to or less than the threshold is provided such that the actual driving route is changeable as this limitation gives the way for the vehicle to automatically change paths or have a new path generated based on being too close to an obstacle.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein a position where the actual driving data is equal to or less than the threshold is provided such that the actual driving route is changeable as this limitation allows for a simple way to avoid obstacles while being within a threshold distance rather than only excluding the vehicle from entering if they were to breach a threshold distance from an obstacle.
Regarding Claim 6 Kume-Bogovich-Zhixin teaches A behavior plan instruction system comprising the instruction device (Pg. 13 – [0044] – “Subsequently, using FIG. 2, a description will be given of a schematic configuration of the automatic driving ECU 10. As illustrated in FIG. 2, the automatic driving ECU 10 includes a driving environment recognition unit 101, a HCU communication unit 102, a behavior determination unit 103, a control execution unit 104, and a vehicle exterior-notification instruction unit 105”) according to claim 1 and the autonomous driving vehicle, (Pg. 10 – [0004] – “A vehicle control device that performs automatic driving”)
Yet Kume-Bogovich fails to teach wherein the instruction device is provided in a server, the autonomous driving vehicle transmits the actual driving data to the server, and the autonomous driving vehicle receives the behavior plan from the server.
Zhixin teaches wherein the instruction device is provided in a server (Pg. 19 – [121] – “Computer program code for carrying out the operations of embodiments of the present invention may be written in one or more programming languages…The program code may execute entirely on the…remote computer or server ” & See Also Pg. 2 – [18] – “The target obstacle avoidance travel path determination module is used for determining the target obstacle avoidance travel path according to the relative position information between each discrete point in each obstacle avoidance travel route to be used” (equates to wherein the instruction device is provided in a server as the second quote shows an obstacle avoidance route generation system thus equivalent to the instruction device. Wherein the first quote shows any embodiment of the art can be ran on a remote server. ))
Yet all fails to teach the autonomous driving vehicle transmits the actual driving data to the server and the autonomous driving vehicle receives the behavior plan from the server
Taveria teaches the autonomous driving vehicle transmits the actual driving data to the server, (Pg. 13 – Col.8 – lines 30-34 – “Thus, the aerial robotic vehicle 200 may navigate using a combination of navigation techniques, including dead-reckoning, camera-based recognition of the land features below and around the aerial robotic vehicle 200 (e.g., recognizing a road, landmarks, highway signage, etc.),” & See Also Pg. 13 – Col. 7 – lines 46 – 53 –“ using the processor 220, the one or more communication components 232, and an antenna may be configured to conduct wireless communications with a variety of remote computing devices, examples of which include the base station or cell tower 50 (e.g., base station 20), a beacon, server, a smartphone, a tablet, or another computing device with which the aerial robotic vehicle 200 may communicate.” & See Also Fig. 2 – Pg. 5 (equates to the autonomous driving vehicle transmits the actual driving data to the server as the first quote shows the robot ability to acquire driving data include position of the vehicle and the second quote shows the communication link between the server and the robot wherein the robot can update the position or driving data of itself by way of communication with the server.)) and the autonomous driving vehicle receives the behavior plan from the server. (Pg. 13 – Col. 7 – lines 46 – 53 –“ using the processor 220, the one or more communication components 232, and an antenna may be configured to conduct wireless communications with a variety of remote computing devices, examples of which include the base station or cell tower 50 (e.g., base station 20), a beacon, server, a smartphone, a tablet, or another computing device with which the aerial robotic vehicle 200 may communicate.” & See Also Fig. 2 – Pg. 5 & See Also Pg. 12 – Col. 6 – lines 50-54 – “The processor 220 and memory 222 may be configured as or be included within a system-on-chip (SoC) 215 along with additional elements such as (but not limited to) a communication interface 224, one or more input units 226,” & See Also Pg. 13 – Col. 8 – lines 40-48 – “input units 226 for receiving control instructions, data from human operators or automated/pre-programmed controls, and/or for collecting data indicating various conditions relevant to the aerial robotic vehicle 200. For example, the input units 226 may receive input from one or more of etc. 45 various components, such as camera(s) or other imaging sensors, detection and ranging sensors (e.g., radar, sonar, lidar, etc.), microphone(s), position information functionalities (e.g., a global positioning system (GPS” (equates to the autonomous driving vehicle receives the behavior plan from the server.as the vehicle is seen to be in contact with the remote server and can communicate with the server by taking in input commands such as a behavior plan that would include control instruction as seen from the last quote. )) It would have been an advantageous addition to the system disclosed by Kume-Bogovich-Zhixin to include the autonomous driving vehicle transmits the actual driving data to the server and the autonomous driving vehicle receives the behavior plan from the server as these limitations allow for easy communication between the vehicle and a remote server ensuring this device can have a configuration that includes off board equipment and allows for more computing power at an offsite location.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include the autonomous driving vehicle transmits the actual driving data to the server and the autonomous driving vehicle receives the behavior plan from the server as the inclusion of these limitations allows for offsite processing to be done and allows for a smaller device structure to be utilized onboard the vehicle.
Response to Arguments
Response to 35 U.S.C. § 102 rejection of claims 1 and 7 applicant’s amendments to the claim changes the scope. Applicant’s arguments have been considered but are not persuasive.
Applicant argues on page 2, “Claims 1 and 7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kume et al. (US 20240308537 A1). Applicant amends claims 1 and 7 to clarify the feature of fixing a route based on actual driving data obtained in advance in the present application. In contrast, Kume discloses a technology relating to obstacle avoidance when it becomes necessary during automatic driving. Kume does not disclose "obtaining actual driving data in advance" and "fixing a route based on the actual driving data obtained in advance", Accordingly, the withdrawal of the claim rejection under § 102 is respectfully requested.” –Applicant’s arguments with respect to claim(s) 1 & 7 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.
Response to 35 U.S.C. § 103 rejection of claims 2-6 applicant’s amendments to the claim changes the scope. Applicant’s arguments have been considered but are not persuasive.
b. Applicant argues on page 3, “Claims 2, 4 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Kume in view of Zhixin (CN 113928340 A).
Claims 3 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Kume-Zhixin and in view of Taveria (US 10,717,435 B2). Neither Zhixin nor Taveria discloses the feature of fixing a route based on actual driving data obtained in advance. Therefore, Zhixin and Taveria cannot cure the deficiencies of Kume. Accordingly, the withdrawal of the claim rejection under § 103 is respectfully requested.”– As to point B see point A
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. GB2585114A. - A system for determining a risk of an accident on a driving route (FS) comprises a memory device for storing route risk parameters of the driving route (FS) and a computer device for determining a respective risk factor for each of the route risk parameters (11). The respective risk factor indicates a measure of a risk of an accident on a respective route section (A1, A2, A3, …, An) of the driving route (FS). The computer device is designed to determine a total risk index of the driving route (FS) depending on the respective risk factor of the respective at least one route risk parameter, wherein the total risk index indicates a measure of a risk of an accident on the driving route (FS).
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/R.A.W./Examiner, Art Unit 3667
/Hitesh Patel/Supervisory Patent Examiner, Art Unit 3667
7/15/26
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