Detailed Action
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This FINAL communication is in response to application No. 18/900,984 filed on 27 March 2026. Claims 1, 2, 7, 8 and 15 have been amended. Claims 4-6 and 9-14 have been canceled. Claims 1, 2, 3, 7, 8 and 15 are being presented for examination.
Response to Applicant’s Remarks
Applicant's amendment and/or arguments with respect to the rejection of claims under 35 USC 101 as set forth in the office action of 30 December 2025 have been considered and are NOT PERSUASIVE. The claim does not present actions that are beyond that of a human mind or that a human can calculate with a pencil and a paper. The applicant argues that the collection of obstacle information may be obtained by target sensors such as LIDAR and a stereo camera, and that a warning may be issued. The information gathered by the sensors if a form of insignificant extra solution activity that falls under the category of data gathering. Furthermore, issuing a warning is considered post solution data displaying. Therefore, the claim is still directed to an abstract idea and rejected under 35 USC 101.
Applicant's amendment and/or arguments with respect to the rejection of claims under 35 USC 102/103 as set forth in the office action of 30 December 2025 have been considered and are NOT PERSUASIVE. Applicant points out that the main differences between the subject matter of claim 1 and the prior art is summarizes as (1) only when there is at least one obstacle located in the first preset circle region, the distance between the at least one obstacle and the second origin is calculated to determine whether there is a collision risk and (2) the first preset circle region takes the first origin (the geometric center of the current vehicle) as a center of the circle and the first preset distance as a radius, the first preset distance is a distance between the geometric center of the current vehicle and any corner of the current vehicle.
Furthermore, in paragraph 67, Qin describes three preset circle regions as a safe circle, a warning level, and a dangerous level. Qin only performs a distance when it has surpassed a preset level that has posed a risk to a collision, or the warning preset circle region in order to determine the level of risk the obstacle poses, as described in paragraph 71. Qin also outlines an origin as a center axle of a vehicle, which is the second origin as described in the application.
In paragraph 74, Fichtner outlines a number of heights, comparable to the function of a radius from the center of a vehicle to the edge of a vehicle, in order to determine whether the vehicle is or will be in collision or not.
Applicant’s amendments and/or arguments with respect to the rejection of Claims 1, 2, 3, 7, 8 and 15 under 35 USC 103 as set forth in the office action of 30 December 2025 have been considered but are moot because the new ground(s) of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 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, 7-8 and 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 will serve as a representative claim for the remainder of the 101 rejection.
101 Analysis – Step 1
Claim 1 is directed to a method, is therefore within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
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 follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claims 1 includes limitations that recite an abstract idea (emphasized below):
Claim 1 recites:
A vehicle collision detection method, comprising the following steps:
S 100: acquiring a collection of obstacle information within a preset range of a current vehicle using target sensors, and
dividing the collection of obstacle information into a first obstacle map and a second obstacle map based on a preset obstacle height;
S200: modeling the current vehicle based on the preset obstacle height, and
fusing vehicle models with the corresponding obstacle maps to obtain a first collision detection model and a second collision detection model, respectively; and
S300: obtaining a distance relationship between a preset position of the current vehicle and obstacles corresponding to the collection of obstacle information through the first collision detection model and/or the second collision detection model, and
determining whether the current vehicle is in collision based on the distance relationship;
wherein the step S300 comprises: 5301: acquiring, in the first collision detection model, initial obstacle coordinates of the obstacles under a first rectangular coordinate system: in the first rectangular coordinate system, a geometric center of the current vehicle being a first origin, a width direction of the current vehicle being an x-axis, and a length direction of the vehicle being a y-axis;
S302: calculating a distance between each obstacle and the first origin based on the initial obstacle coordinates and coordinates of the first origin, if the distance between at least one of the obstacles and the first origin is smaller than a first preset distance, performing step S303, otherwise performing step S305;
S303: acquiring transformed obstacle coordinates of obstacles in a first preset circular region under a second rectangular coordinate system, and proceeding to step S304; in the second rectangular coordinate system, a midpoint of a rear axle of the current vehicle being a second origin, the width direction of the vehicle being an X-axis, and the length direction of the vehicle being a Y-axis;
S304: calculating a distance between each obstacle in the first preset circular region and the second origin based on the transformed obstacle coordinates and coordinates of the second origin, if the distance between at least one of the obstacles in the first preset circular region and the second origin is smaller than a second preset distance, determining that the current vehicle is in collision and issue a collision warning message, otherwise performing step S305; and
S305: determining that the current vehicle has no risk of collision; wherein the first preset circle region takes the first origin as a center of the circle and the first preset distance as a radius, and the first preset distance is a distance between the geometric center of the current vehicle and any corner of the current vehicle.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determining...” in the context of this claim encompasses a person looking at data collected and forming a simple judgement. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
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, there are not additional limitations listed. Thus, the additional elements do not integrate the abstract idea into a practical application.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, 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 lack of additional elements remove the possibility of the limitations to be considered significantly more.
Dependent claim(s) 2,3,7,8 do not recite any further limitations that cause the claim(s) to be patent eligible.
Therefore, claim(s) 1,2,3,7,8 and 15 are 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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 7-8, and 15 are rejected under 35 U.S.C 103 as being unpatentable over Fichtner (DE 102020131281 A1) in view of Qin (US 12233856 B2).
Regarding claim 1, Fichtner teaches A vehicle collision detection method, comprising the following steps: S 100: acquiring a collection of obstacle information within a preset range of a current vehicle using target sensors, and (see at least [0063]; The vehicle preferably includes a number of environmental sensors designed to detect the vehicle's surroundings.
Examples of such sensor units in the vehicle include image acquisition devices such as a camera, radar (radio detection and ranging) or lidar (light detection and ranging), ultrasonic sensors, positioning sensors and the like.") Fichtner describes acquiring information regarding the surroundings of a vehicle, including obstacles, using target sensors such as lidar.
dividing the collection of obstacle information into a first obstacle map and a second obstacle map based on a preset obstacle height; S200: (see at least [0059]; "a division of the vehicle into a number of altitude intervals, and for determining a number of interval environment maps based on the determined model and the received three dimensional environment map, wherein for at least one altitude interval of the number of altitude intervals contained in the model an interval environment map assigned to the altitude interval is determined, ") Fichtner describes dividing the collection of obstacle information into one or more obstacle maps, or a first and second obstacle map based on a preset obstacle height
modeling the current vehicle based on the preset obstacle height, and (see at least [0067]; "Figure 2E shows an exemplary division of a vehicle into several height intervals and associated boundary lines;") Fichtner describes modeling the vehicle based on preset height intervals for obstacles.
fusing vehicle models with the corresponding obstacle maps to obtain a first collision detection model and a second collision detection model, respectively; and S300: (see at least [0034-0038]; "The collision is determined, for example, by moving the boundary line according to the trajectory in the interval environment map, which in particular includes a two-dimensional environment map, and by determining an intersection point of the boundary line with an object in the interval environment map.
Determining the collision involves identifying the point of collision on the vehicle.
According to another embodiment of the method, step d) additionally includes determining a collision distance, if a collision has been detected.
The collision distance is measured, in particular, along the predicted trajectory.
According to a further embodiment of the method, the model comprises at least a first height interval corresponding to the wheels, a second height interval corresponding to the underbody, a third height interval corresponding to the body and/or a fourth height interval corresponding to the passenger compartment.") Fichtner describes a multitude of collision models based on the respective heights of the object.
obtaining a distance relationship between a preset position of the current vehicle and obstacles corresponding to the collection of obstacle information through the first collision detection model and/or the second collision detection model, and (see at least [0034]; "The collision is determined, for example, by moving the boundary line according to the trajectory in the interval environment map, which in particular includes a two-dimensional environment map, and by determining an intersection point of the boundary line with an object in the interval environment map.") Fichtner describes the distance relationship between the collision model and the current vehicle position.
determining whether the current vehicle is in collision based on the distance relationship; (see at least [0036]; "According to another embodiment of the method, step d) additionally includes determining a collision distance, if a collision has been detected.") Fichtner describes determining whether the current vehicle is in collision based on the distance.
wherein the step S300 comprises: 5301: acquiring, in the first collision detection model, initial obstacle coordinates of the obstacles under a first rectangular coordinate system: in the first rectangular coordinate system, a geometric center of the current vehicle being a first origin, a width direction of the current vehicle being an x-axis, and a length direction of the vehicle being a y-axis; (see at least [0008] ;"Each measuring point refers in particular to an object located in the surrounding area. The reference coordinate system refers in particular to a reference point of the vehicle, such as the center point of a rear axle. The reference coordinate system is preferably a Cartesian coordinate system, wherein, for example, an x-axis points along the longitudinal direction of the vehicle, a y-axis points along the transverse direction of the vehicle, and a z-axis points perpendicular to the longitudinal and transverse directions. Alternatively, the three dimensional environment map can include a geometric representation for each object in the environment. For example, an object can be represented as a surface in space or as a voluminous object in space.") Fichtner describes coordinates that include obstacles, as well as a rectangular coordinate system with the capacity for the geometric center of the vehicle being the first original, and the x-axis being the width and length direction being the y-axis.
S304: calculating a distance between each obstacle in the first preset circular region and the second origin based on the transformed obstacle coordinates and coordinates of the second origin, if the distance between at least one of the obstacles in the first preset circular region and the second origin is smaller than a second preset distance, determining that the current vehicle is in collision and issue a collision warning message, otherwise performing step S305; and (see at least [27, 28, 003]; "Thus, the respective boundary line corresponds to the interval environment map assigned to the altitude interval. Since the boundary line has a specific position in the vehicle's reference coordinate system, it can be represented in the interval environment map, with positions and distances to other objects in the interval environment map being particularly true to scale.
Each boundary line serves in particular the purpose of representing, in the form of an outline, areas of the vehicle that lie within the assigned height interval and that may
therefore collide with an object located within that height interval…Therefore, preferably a three-dimensional model of the vehicle and a three-dimensional
model of the obstacle are used to obtain the most accurate collision warning possible") Fichtner describes determining whether the distance between object and vehicle is smaller than a preset distance to determine whether the vehicle is in collision and a system for a waning message.
wherein the first preset circle region takes the first origin as a center of the circle and the first preset distance as a radius, and the first preset distance is a distance between the geometric center of the current vehicle and any corner of the current vehicle. (see at least [0028]; "Each boundary line serves in particular the purpose of representing, in the form of an outline, areas of the vehicle that lie within the assigned height interval and that maytherefore collide with an object located within that height interval.") Fichtner describes preset distances that represent the distances of the dimensions of the vehicle, representative of the distance from the center of the vehicle to the corners.
Fichtner does not explicitly disclose S302: calculating a distance between each obstacle and the first origin based on the initial obstacle coordinates and coordinates of the first origin, if the distance between at least one of the obstacles and the first origin is smaller than a first preset distance, performing step S303, otherwise performing step S305; S303: acquiring transformed obstacle coordinates of obstacles in a first preset circular region under a second rectangular coordinate system, and proceeding to step S304; in the second rectangular coordinate system, a midpoint of a rear axle of the current vehicle being a second origin, the width direction of the vehicle being an X-axis, and the length direction of the vehicle being a Y-axis; S305: determining that the current vehicle has no risk of collision.
However, Qin teaches S302: calculating a distance between each obstacle and the first origin based on the initial obstacle coordinates and coordinates of the first origin, if the distance between at least one of the obstacles and the first origin is smaller than a first preset distance, performing step S303, otherwise performing step S305; (see at least [Fig. 7, 71]; " Optionally, the decision and anti-collision module may determine a risk of a collision between a surrounding vehicle only at the warning and/or dangerous level and the ego-vehicle based on a collision potential energy of the surrounding vehicle. ") Qin teaches calculating a distance between each obstacle and the origin, the vehicle, if smaller than a first preset distance, moving to another step.
S303: acquiring transformed obstacle coordinates of obstacles in a first preset circular region under a second rectangular coordinate system, and proceeding to step S304; in the second rectangular coordinate system, a midpoint of a rear axle of the current vehicle being a second origin, the width direction of the vehicle being an X-axis, and the length direction of the vehicle being a Y-axis; (see at least [19, 20]; "
calculating a location of the surrounding obstacle in the coordinate system based on the first sensing data, where the location is used to indicate coordinates and a quadrant of the obstacle in the coordinate system.
(20) In another possible implementation, an ego-vehicle coordinate system of the intelligent vehicle may be a coordinate system that uses a center of mass of the ego-vehicle as an origin and uses a traveling direction as a positive direction of an X-axis. Optionally, the coordinate system may alternatively use a middle point of the head of the ego-vehicle or a middle point of the tail of the ego-vehicle as an origin.") Qin teaches acquiring transformed obstacle coordinates in a second coordinate system, with an origin of the coordinate system being the middle point of the tail of the vehicle.
S305: determining that the current vehicle has no risk of collision; (see at least [67]; ". When an obstacle is at the safe level, there is no possibility of a collision with the vehicle.") Qin teaches determining there is no risk of collision.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Fichtner to incorporate the teachings of Qin which teaches the coordinates of obstacles within a preset distance and the distance correlating with the size of the vehicle, as well as determine when the vehicle has no risk of collision in order to determine where the obstacles are in relation to the vehicle to be able to proceed with safety.
Regarding claim 2, Fichtner teaches The vehicle collision detection method according to claim 1, wherein the dividing the collection of obstacle information into a first obstacle map and a second obstacle map based on a preset obstacle height in step S100 comprises:
calibrating a maximum size of front wheels and rear wheels of the current vehicle, respectively, and (see at least [0038]; "According to a further embodiment of the method, the model comprises at least a first height interval corresponding to the wheels,")
setting the preset obstacle height according to the maximum size; and (see at least [0039]; "Depending on the height intervals, the model can include a wheel boundary line")
determining whether heights of the obstacles corresponding to the collection of obstacle information are greater than the preset obstacle height, if yes, classifying the obstacles into the first obstacle map, otherwise classifying the obstacles into the second obstacle map. (see at least [0027] "Preferably, for each height interval of the number, a corresponding boundary line is determined and assigned to the height interval. Thus, the respective boundary line corresponds to the interval environment map assigned to the altitude interval. Since the boundary line has a specific position in the vehicle's reference coordinate system, it can be represented in the interval environment map, with positions and distances to other objects in the interval environment map being particularly true to scale.")
Regarding claim 3, Fichtner teaches The vehicle collision detection method according to claim 2, wherein step S200 comprises: modeling the current vehicle to obtain a first vehicle model comprising a front overhang and a rear overhang of the vehicle, and a second vehicle model with the front overhang and the rear overhang of the vehicle removed; and (see at least [0038]; "a second height interval corresponding to the underbody, a third height interval corresponding to the body")
fusing the first vehicle model and the second vehicle model with the first obstacle map and the second obstacle map, respectively, to obtain the first collision detection model and the second collision detection model. (see at least [034]; "The collision is determined, for example, by moving the boundary line according to the trajectory in the interval environment map, which in particular includes a two-dimensional environment map, and by determining an intersection point of the boundary line with an object in the interval environment map.")
Regarding claim 7, Fichtner teaches The vehicle collision detection method according to claim 3, wherein step S300 further comprises: S311: acquiring, in the second collision detection model, initial obstacle coordinates of the obstacles under the first rectangular coordinate system; (see at least [0008, 0059]; "The reference coordinate system is preferably a Cartesian coordinate system, wherein, for example, an x-axis points along the longitudinal direction of the vehicle, a y-axis points along the transverse direction of the vehicle, and a z-axis points perpendicular to the longitudinal and transverse directions. Alternatively, the three dimensional environment map can include a geometric representation for each object in the environment.…a division of the vehicle into a number of altitude intervals, and for determining a number of interval environment maps based on the determined model and the received three dimensional environment map, wherein for at least one altitude interval of the number of altitude intervals contained in the model an interval environment map assigned to the altitude interval is determined, ")
S312: calculating a distance between each obstacle and the first origin based on the initial obstacle coordinates and coordinates of the first origin, if the distance between at least one of the obstacles and the first origin is smaller than a third preset distance, performing step S313, otherwise performing step S315; (see at least [0030]; "step d) includes determining a distance of the vehicle to an object in the environment depending on at least one of the determined interval environment maps,")
S313: acquiring transformed obstacle coordinates of obstacles in a second preset circular region under the second rectangular coordinate system, and proceeding to step S314; (see at least [0008]; "Each measuring point refers in particular to an object located in the surrounding area. The reference coordinate system refers in particular to a reference point of the vehicle, such as the center point of a rear axle. The reference coordinate system is preferably a Cartesian coordinate system, wherein, for example, an x-axis points along the longitudinal direction of the vehicle, a y-axis points along the transverse direction of the vehicle, and a z-axis points perpendicular to the longitudinal and transverse directions. Alternatively, the three dimensional environment map can include a geometric representation for each object in the environment. For example, an object can be represented as a surface in space or as a voluminous object in space.")
S314: calculating a distance between each obstacle in the second preset circular region and the second origin based on the transformed obstacle coordinates and coordinates of the second origin, (see at least [27, 28]; "Thus, the respective boundary line corresponds to the interval environment map assigned to the altitude interval. Since the boundary line has a specific position in the vehicle's reference coordinate system, it can be represented in the interval environment map, with positions and distances to other objects in the interval environment map being particularly true to scale. [0028] Each boundary line serves in particular the purpose of representing, in the form of an outline, areas of the vehicle that lie within the assigned height interval and that may therefore collide with an object located within that height interval.")
if the distance between at least one of the obstacles in the second preset circular region and the second origin is smaller than the second preset distance, determining that the current vehicle is in collision, otherwise performing step S315; and (see at least [36]; "According to another embodiment of the method, step d) additionally includes determining a collision distance, if a collision has been detected. The collision distance is measured, in particular, along the predicted trajectory.")
S315: determining that the current vehicle has no risk of collision, wherein the second preset circle region takes the first origin as a center of the circle and the third preset distance as a radius. (see at least [0033]; "The predicted trajectory includes, for example, an extrapolation of the vehicle's path based on the current driving state, in particular a current steering angle and/or wheel angle. The predicted trajectory can also include already planned maneuvers, such as steering the vehicle. In this way, it is possible, for example, to check whether a trajectory planned in")
Regarding claim 8, Fichtner teaches The vehicle collision detection method according to claim 3, wherein step S303 or step S313 specifically comprises: acquiring a vehicle heading angle, (see at least [0033]; "The predicted trajectory includes, for example, an extrapolation of the vehicle's path based on the current driving state, in particular a current steering angle and/or wheel angle.")
corresponding initial obstacle coordinates of the obstacles in the first preset circular region or the second preset circular region under the first rectangular coordinate system, (see at least [0008]; "The three-dimensional environment map, for example, comprises a point cloud with a set of individual measurement points, where each measurement point is assigned a threedimensional position comprising an altitude value, a latitude value and a longitude value in a reference coordinate system.")
and coordinates of the midpoint of the rear axle of the vehicle under the first rectangular coordinate system; (see at least [0008]; "Each measuring point refers in particular to an object located in the surrounding area.The reference coordinate system refers in particular to a reference point of the vehicle, such as the center point of a rear axle. The reference coordinate system is preferably a Cartesian coordinate system, wherein, for example, an x-axis points along the longitudinal direction of the vehicle, a y-axis points along the transverse direction of the vehicle, and a z-axis points perpendicular to the longitudinal and transverse directions. Alternatively, the threedimensional environment map can include a geometric representation for each object in the environment. For example, an object can be represented as a surface in space or as avoluminous object in space.")
calculating a first included angle based on the initial obstacle coordinates and the coordinates of the midpoint of the rear axle of the vehicle, and (see at least [0093]; "The predicted trajectory TR is, for example, predicted based on current driving condition data in the form of an extrapolation. This means that the trajectory TR represents the further movement of vehicle 100 with a constant steering angle. In this example, the predicted trajectory TR refers to a center point on the rear axle of vehicle 100….Two objects, O1 and O2, are located in the vicinity of 200.It should be noted that the objects O1, O2 of Fig. 5 have a different height than the objects 01, O2 shown in Fig. 3. For example, object 01 has a height that falls into a lowest height interval HI1 (see Fig. 2A ) (wheel height interval) protrudes into it. For example, object O2 has a height that falls within a height interval HI3 (see Fig. 2A ) (body height interval) protrudes into it. ")
calculating a distance between each obstacle and the midpoint of the rear axle of the vehicle, wherein the first included angle is an included angle between a connecting line of each obstacle and the midpoint of the rear axle of the vehicle and a perpendicular line segment from the obstacle to the X-axis of the second rectangular coordinate system; (see at least [105]; "The origin O of the reference coordinate system REF is, for example, at a specific point on vehicle 100 (see Fig.1 , Fig. 2 or Fig. 5 ), in particular a center point of the rear axle, anchored. As an example, a single measuring point P is shown, whose coordinates are (L, B, H). A three-dimensional environment map 3DD (see Fig. 3 or Fig. 6) comprises, for example, a large number, in particular several hundred, several thousand or even several tens of thousands of measurement points P, each of which corresponds, for example, to a point on the surface of an object O1 - O4 (see Fig. 1 - Fig. 5 ) correspond.")
calculating a second included angle based on the first included angle and the vehicle heading angle; and (see at least [0093]; "The predicted trajectory TR is, for example, predicted based on current driving condition data in the form of an extrapolation. This means that the trajectory TR represents the further movement of vehicle 100 with a constant steering angle. In this example, the predicted trajectory TR refers to a center point on the rear axle of vehicle 100….Two objects, O1 and O2, are located in the vicinity of 200.It should be noted that the objects O1, O2 of Fig. 5 have a different height than the objects 01, O2 shown in Fig. 3. For example, object 01 has a height that falls into a lowest height interval HI1 (see Fig. 2A ) (wheel height interval) protrudes into it. For example, object O2 has a height that falls within a height interval HI3 (see Fig. 2A ) (body height interval) protrudes into it. ")
calculating the transformed obstacle coordinates of each obstacle based on the distance between the obstacle and the midpoint of the rear axle of the vehicle and the second included angle. (see at least [105]; "The origin O of the reference coordinate system REF is, for example, at a specific point on vehicle 100 (see Fig.1 , Fig. 2 or Fig. 5 ), in particular a center point of the rear axle, anchored. As an example, a single measuring point P is shown, whose coordinates are (L, B, H). A three-dimensional environment map 3DD (see Fig. 3 or Fig. 6) comprises, for example, a large number, in particular several hundred, several thousand or even several tens of thousands of measurement points P, each of which corresponds, for example, to a point on the surface of an object O1 - O4 (see Fig. 1 - Fig. 5 ) correspond.")
Regarding claim 15, Qin teaches A vehicle, comprising target sensors, a processor, a computer-readable device storing a program, and a warning module, wherein the target sensors are configured for acquiring obstacle information, the processor is configured for executing the program to implement the vehicle collision detection method according to claim 1, and the warning module is configured for issuing the collision warning message.(see at least [23, 31, 34, 35, 11]; " The sensing device 102 includes one or more of sensors that have a capability of detecting and identifying a surrounding object, such as an image collection device 1021, a laser radar 1022, and a millimeter wave radar 1023. .. The controller includes a processor, a memory, a communication interface, and a bus….According to an eighth aspect, this application provides a computer-readable storage medium. The computer-readable storage medium stores instructions. When the instructions are run on a computer, the computer is enabled to perform the method or function according to the foregoing aspects. (35) According to a ninth aspect, this application provides a computer program product including instructions. When the computer program product runs on a computer, the computer is enabled to perform the method or function according to the foregoing aspects….the intelligent vehicle prompts a risk of a collision between the intelligent vehicle and the surrounding obstacle through seat vibration; or the intelligent vehicle prompts is a risk of a collision between the intelligent vehicle and the surrounding obstacle through in-vehicle lamp flashing. By using the foregoing method, message interaction between the intelligent vehicle and the driver can be implemented.")
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Fichtner to incorporate the teachings of Qin which teaches sensors, processors, a program, and a warning module in order to be able to perform and execute the desired functions of avoiding a collision as well as determining when the vehicle is in collision.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HANA VICTORIA HALL whose telephone number is (571)272-5289. The examiner can normally be reached M-F 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rachid Bendidi can be reached at 5712724896. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HANA VICTORIA HALL/Examiner, Art Unit 3664
/RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664
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