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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. CN202110206772.0, which was filed on 02/24/2021.
Response to Amendment
This action is in response to amendments and remarks filed on 04/16/2026. The examiner notes the following adjustments to the claims by the applicant:
Claims 1, 3, 6-7, 9-10 and 16-21 are amended;
Claims 5 and 12-14 are newly cancelled. (Claims 2 and 8 were previously canceled.)
No claims are added.
Therefore, Claims 1, 3-4, 6-7, 9-11 and 15-21 are pending examination, in which Claims 1, 9 and 10 are independent claims.
In light of the instant amendments and arguments:
Regarding the rejection of Claims 1, 3-4, 6-7, 9-11 and 15-21 under 35 U.S.C. §101, the applicant’s arguments have been considered and found persuasive. The rejection is withdrawn.
Claims 10 and 19-21 are objected to for minor informalities.
Further examination resulted in a new rejection of Claims 1, 3-4, 6-7, 9-11 and 15-21 under 35 U.S.C. §103.
THIS ACTION IS MADE FINAL. Necessitated by amendment.
Claim Objections
Claims 10 and 19-21 objected to because of the following informalities:
Each of these claims includes the misspelling of the word sensor (i.e., senor). Appropriate correction is required.
Response to Arguments
Applicant presents the following arguments regarding the previous office action:
To overcome the 35 U.S.C. § 103 rejection, the applicant has amended each independent claim to include the additional underlined limitations (or the equivalent): "A method for starting an unmanned vehicle, applied to the unmanned vehicle, wherein the method is executable by a vehicle-mounted autonomous driving controller of the unmanned vehicle, the vehicle-mounted autonomous driving controller coupled to a sensor and a positioning device of the unmanned vehicle, and the method comprises: in response to completion of a task of the unmanned vehicle at a current node, receiving a signal input by the sensor of the unmanned vehicle containing occupancy state information of a reference start position on a guide line, wherein the guide line is a preset driving route of the unmanned vehicle from the current node to a next node, the reference start position is a position on the guide line reached by the unmanned vehicle from a and the occupancy state information is an occupancy state or a non- occupancy state; in response to a determination that the occupancy state information is the occupancy state, obtaining position data from the positioning device and projecting the current position of the unmanned vehicle to the guide line to determine an initial position of the current position on the guide line; determining the reference start position on the guide line; dynamically generating a target start point sequence on the basis of the reference start position, the initial position, a left road width corresponding to the guide line and a right road width corresponding to the guide line, wherein each target start point in the target start point sequence is a new position point obtained by iteratively calculating based on the reference start position, the initial position, the left road width and the right road width; and selecting, by the vehicle-mounted autonomous driving controller, a target start point from the target start point sequence as a target start position and controlling the unmanned vehicle to start using the target start position, ";
[A.] “When all target positions corresponding to the predefined trajectories are occupied, Derendarz cannot generate new usable trajectories or position points, nor can it solve the autonomous starting problem in scenarios without predefined trajectories. Derendarz does not disclose, teach, or suggest at least the features of "dynamically generating a target start point sequence based on the reference start position, the initial position, the left road width, and the right road width", "iteratively calculating a new position point based on the reference start position, the initial position, the left road width, and the right road width" and "the dynamic generation process including iterative update of the reference start position" as required by amended claim 1.”;
[B.] “Kubota does not involve "detection of occupancy of a reference start position". Obviously, Kubota does not disclose, teach, or suggest at least the features of "dynamically generating a target start point sequence based on the reference start position, the initial position, the left road width, and the right road width", "iteratively calculating a new position point based on the reference start position, the initial position, the left road width, and the right road width" and "the dynamic generation process including iterative update of the reference start position" as required by amended claim 1.”;
[C.] “Boxmeyer does not involve technical means such as route planning, start point selection, guide lines, position mapping, left and right road width collection, or dynamic point generation. Obviously, Boxmeyer does not disclose, teach, or suggest at least the features of "dynamically generating a target start point sequence based on the reference start position, the initial position, the left road width, and the right road width", "iteratively calculating a new position point based on the reference start position, the initial position, the left road width, and the right road width" and "the dynamic generation process including iterative update of the reference start position" as required by amended claim 1.”.
Applicant's arguments A., B. and C. appear to be directed to the instantly amended subject matter. Accordingly, they have been addressed in the rejections below.
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, 3-4, 6-7, 9-11 and 15-21 are rejected under 35 U.S.C. §103 as being unpatentable over the combination of Derendarz et al. (US 10,889,323 B2, henceforth Derendarz) and Duo et al. (CN 111796587 A, henceforth Duo).
Regarding Claim 1, Derendarz recites the limitations: a method for starting {starting an unmanned vehicle is interpreted by the examiner as initiating vehicle movement, in some manner, which is reflected in the vehicle trajectories of Fig. 3} an unmanned vehicle {a vehicle with automatic driving capabilities, Abstract}, applied to the unmanned vehicle, wherein the method is executable by a vehicle-mounted autonomous driving controller {control unit 3, transverse control 51 and longitudinal control 52, Fig. 1} of the unmanned vehicle {50, Fig. 2}, the vehicle-mounted autonomous driving controller coupled to a sensor {environmental detection unit, Fig. 2} and a positioning device of the unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}, and the method comprises: in response to completion of a task {arrival of vehicle 50 at property 21, Fig. 3} of the unmanned vehicle at a current node {current position 23, Fig. 3}, receiving a signal input by the sensor of the unmanned vehicle containing occupancy state information {occupancy of a garage bay, Col. 3, Lns. 31-41, determined by environmental detection device ”, Col. 5, Lns. 62-67} of a reference start position {the ends of trajectories 30-33, Fig. 3, represent four different locations for positioning vehicle 50 along a trajectory from its current position 23} on a guide line, wherein the guide line is a preset driving route of the unmanned vehicle {the examiner interprets a guideline as reference element, either marked or unmarked, that facilitates driving within a necessary boundary region (which, for example, is the centerline in a two-way traffic road or the unmarked centerline of a single-lane that driver attempts to follow – corresponding to an inherent guideline); with regard to Fig. 3, a preset driving route/guide element is the unmarked centerline leading from the property entrance through the driveway that passes through decision point 36, and then extends through the center of a garage bay} from the current node {current position 23, Fig. 3} to a next node {target positions 40-43, Fig. 3}, the reference start position is a position on the guide line reached by the unmanned vehicle {target positions 40-43, Fig. 3} from a current position {current location 23, Fig. 3}, and the occupancy state information is an occupancy state or a non-occupancy state {determining garage bay occupancy, Col. 5, Lns. 45-51}; in response to a determination that the occupancy state information is the occupancy state {identification of occupancy status Col. 7, Lns. 5-9}, obtaining position data from the positioning device {the use of radar, ultrasonic sensors and LIDAR (Col. 5, Lns. 62-67) and the wireless connectivity (Col. 8, Lns. 16-17) of control unit 3, Fig. 1, corresponds to vehicle 50, Fig. 3, having continuous location information} and projecting the current position {current location 23, Fig. 3} of the unmanned vehicle to the guide line to determine an initial position of the current position on the guide line {the examiner interprets this as the distance between the current position 23 of vehicle 50 from current position 23 to the centerline of the driveway and property entrance 21, which as mentioned above includes decision point 36, Fig. 3, with the initial position being the location the center of the vehicle passes through the property entrance}; determining the reference start position on the guide line {decision made by control unit 2 on where to park the vehicle, such as target positions 41-42 in the garage, Fig. 3}; dynamically generating a target start point sequence {the examiner interprets this as identifying the location options for placing the vehicle that are unoccupied combined with general path planning; this is accomplished via the multiple sensors of the environmental detection device 2 gathering data on all features in the vicinity of the vehicle and providing the data to control unit 3 for processing and path planning, including continuous monitoring the environment to identify if a target position is occupied or becomes occupied during movement, Col. 5, Ln. 62 – Col. 6, Ln. 3, which includes the control system in Fig. 1 needing to determine the exact route (34, Fig. 3) to take from current position 23 to decision point 36 but needing to first determine the precise location of the “current position”, Col. 7, Lns. 23-26; moreover the dynamic nature, or decision making capabilities of the control system in Fig. 1 includes dealing with obstacles that leads to adjusting the positioning of the vehicle, for example, off the centerline of garage, Col. 3, Ln. 66 – Col. 7, Ln. 14, corresponding to adjusting the target location due to a change in the “width” of the garage space} on the basis of the reference start position {target positions 40-43, Fig. 3}, the initial position {decision point 36, Fig. 3}, a left road width of corresponding to the guide line {left boundary of property entrance 21 and driveway, Fig. 3, relative to unmarked centerline of the driveway} and a right road width corresponding to the guide line {right boundary of property entrance 21 and driveway, Fig. 3, relative to the unmarked centerline of the driveway}, wherein each target start point in the target start point sequence is a new position point obtained by iteratively calculating based on the reference start position, the initial position, the left road width and the right road width {expanding on the above discussion of “dynamically generating a target start point sequence”, the combination of the obstacle detection capabilities of the environmental detection device 2 and the ability of the control unit 3 to factor in “additional information” during path planning and execution (Col. 3, Ln. 62 – Col. 4, Ln. 22) leads to the capability: “The control unit then modifies one of the provided trajectories and then carries out the automated drive.”, Col. 4, Lns. 20-22}; and selecting, by the vehicle-mounted autonomous driving controller {control unit 3 carries-out automated driving of a vehicle 50 (Col. 6, Lns. 14-19), as represented in Fig. 3}, a target start point from the target start point sequence as a target start position {selection of target position when vehicle reaches decision point 36 (Fig. 3),”, Col. 5, Lns. 30-61} and controlling the unmanned vehicle to start using the target start position {parking vehicle in left-hand garage 25, Col. 7, Lns. 47-48}, wherein the dynamically generating the target start point sequence on the basis of the reference start position, the initial position, the left road width and the right road width comprises: iteratively updating the reference start position {the examiner interprets this, as above, as simply a first position (the initial position), a second position (the reference start position or final position) and the boundaries of the region (all of which are basic elements that must always be defined for facilitating autonomous driving, as will be appreciated by one skilled in the art), combined with an external factor that necessitate a location of a new final position, all of which was captured above in describing parking in a garage bay when an obstacle is detected} by the following processing steps: determining whether the difference between the reference start position and the initial position {decision point 36, Fig. 3} meets a preset condition {necessary condition is whether target position 40-43 is unoccupied, which is determined by environmental detection device 2 (Fig. 1) and is constantly evaluated as vehicle moves from current location 23 to decision point 36 towards a target position, Col. 5, Lns. 45-61}; in response to condition meeting, generating an alternative start position on the basis of the reference start position and the initial position {user selection of an alternative starting position (i.e., target positions 40-43, Fig. 3) due to occupancy of first target choice, Col. 3, Lns. 39-41} and determining the alternative start position as the reference start position, and performing the processing steps again {based on occupancy evaluation, a processing step must be repeated to determine which trajectory will be implemented, and thus which of target position 40-43, Fig. 3, will the vehicle 50 drive to, as a result of continuous monitoring of the target position and reevaluation as required, Col. 7, Lns. 1-9}.
Derendarz does not appear to explicitly recite the limitations: further processing steps: obtaining position information corresponding to the reference start position, wherein the position information comprises the left road width corresponding to the guide line and the right road width corresponding to the guide line; on the basis of the left road width and the reference start position, generating at least one left alternative start point through a preset threshold; on the basis of the right road width and the reference start position, generating at least one right alternative start point through the preset threshold; merging at least one left alternative start point and the at least one right alternative start point to obtain an alternative start point group.
However, Dou explicitly recites limitations: obtaining position information {the examiner interprets this claim language as representing path planning to provide multiple alternative paths (in the case of obstacle avoidance, for example; data is collected by an information collection unit that includes at least one camera, a radar, and a laser rangefinder (Pg. 6, Lns. 15-25) and localization is provided by a “vehicle-mounted satellite navigation device is installed on the vehicle, and the vehicle's position information can be measured” (Pg. 5, Lns. 11-13)} corresponding to the reference start position {path planning (Pg. 6, Lns. 9-16), wherein a future position (emphasis by examiner) corresponds to changing motion to a different lateral position to avoid an obstacle (Pg. 6, Lns. 1-7)}, wherein the position information comprises the left road width corresponding to the guide line and the right road width corresponding to the guide line {the dividing of all road lanes into sub-lanes, described next, takes into account all lane boundaries}; on the basis of the left road width and the reference start position, generating at least one left alternative start point through a preset threshold; on the basis of the right road width and the reference start position, generating at least one right alternative start point through the preset threshold {an automatic driving system, as part of path planning (Pg. 5, Lns. 19-21), divides each lane into a plurality of sub-lanes (S120, Pg. 5, Lns. 19-21, using the criteria: “Divide the road with a road width greater than or equal to twice the width of the sub-lane into a plurality of sub-lanes”), in order to provide alternative paths when an obstacle is identified, wherein this sub-division inherently is based on the left- and right-lane boundaries, as well as the outer boundaries of the road, in the case of road with more than two lanes; the examiner interprets this claim language as representing path planning to provide multiple alternative paths (in the case of obstacle avoidance, for example; data is collected by an information collection unit that includes at least one camera, a radar, and a laser rangefinder, Pg. 6, Lns. 15-25}; merging at least one left alternative start point and the at least one right alternative start point to obtain an alternative start point group {the examiner interprets this as simply combining elements, or, effectively a form of Routine Optimization [MPEP § 2145. 05(II)]}.
Derendarz and Dou are analogous art because they both deal with autonomous vehicle path planning when alternative or changes in a planned trajectory are necessary.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Derendarz and Dou before them, to modify the teachings Derendarz to include the teachings of Dou to provide a granular mechanism for determining an alternative path, with multiple path options, as is necessary when an obstacle is present {Pg. 5, Lns. 19-21 and Pg. 6, Lns. 15-25}.
Regarding Claim 3, the combination of Derendarz and Dou discloses all the limitations of Claim 1, as discussed supra. In addition, Derendarz explicitly recites the limitation: wherein the generating a target start point sequence on the basis of the reference start position, the initial position, the left road width and the right road width further comprises: arranging all alternative start points in the obtained alternative start point group according to a preset arrangement instruction to generate a target start point sequence {ranking of target positions 40-43 described in , Col. 3, Lns. 39-53}.
Regarding Claim 4, the combination of Derendarz and Dou discloses all the limitations of Claim 1, as discussed supra. In addition, Derendarz explicitly recites the limitation: wherein the generating an alternative start position on the basis of the reference start position and the initial position comprises: generating an initial start position on the basis of the reference start position and the initial position {distance between decision point 36, Fig. 3, and a target position 40-43}; and determining the sum of the initial start position and the initial position as an alternative start position {one skilled in the art will appreciate the final position of the vehicle, after starting at current position 23 and passing through decision point 36 and target position 40, can be target position 43, corresponding to a longer trajectory, Fig. 3}.
Regarding Claim 6, the combination of Derendarz and Dou discloses all the limitations of Claim 1, as discussed supra. In addition, Derendarz explicitly recites the limitation: wherein the selecting a target start point from the target start point sequence as the target start position comprises: for each target start point in the target start point sequence, performing the following steps: determining the occupancy state information of the target start point; and in response to a determination that the occupancy state information is a non-occupancy state {occupancy of garage: “depending on a current occupancy status of the target position of a provided trajectory, an alternative target position should be selected”, Col. 3, Lns. 31-41}, determining the target start point as the target start position {with respect to Fig. 3, once garage bay 25 is identified as occupied, trajectory 32 is chosen rather than trajectory 31, thus changing the parking starting point from in front of left-hand garage 25 to right-hand garage26}.
Regarding Claim 7, the combination of Derendarz and Dou discloses all the limitations of Claim 1, as discussed supra. In addition, Derendarz explicitly recites the limitation: generating a driving track according to the current position and the target start position {the sum of trajectories 32 and 34, Fig. 3}; controlling the unmanned vehicle to drive according to the driving track {parking vehicle in left-hand garage 25, Col. 7, Lns. 47-48}; and in response to the distance between the unmanned vehicle and the target start position meeting a first target condition {minimum distance to an obstacle, Col. 4, Lns. 2-5} and the driving direction of the unmanned vehicle meeting a second target condition {whether vehicle is to be parked in the forward or reverse direction, Col. 3, Lns. 15-16}, generating the target start point sequence again {the control system in Fig. 1 is constantly monitoring if a target position is occupied or unoccupied (Col. 7, Lns. 1-9), wherein occupation may be an obstacle requiring an adjustment in the final position of the vehicle (Col. 3, Ln. 66 – Col. 7, Ln. 14), corresponding to adjusting the target location due to a change in the effective width of the garage space}.
Regarding Claim 9, Derendarz discloses the limitations: an electronic device {device 1, Col. 6, Lns. 14-19 and Fig. 1}, comprising: at least one vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}; a storage apparatus {memory 4, Fig. 1}, having at least one program stored thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}; and a radar, configured to monitor objects {environmental detection device includes radar, Col. 5, Lns. 65-67}; wherein the vehicle-mounted autonomous driving controller is coupled to the radar {environmental detection device 2 relative to control unit 2 in Fig. 1} and a positioning device of an unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}, and when executed by the at least one vehicle-mounted autonomous driving controller, the at least one program enables the at least one vehicle-mounted autonomous driving controller to implement a method for starting {starting an unmanned vehicle is interpreted by the examiner as initiating vehicle movement, in some manner, which is reflected in the vehicle trajectories of Fig. 3} an unmanned vehicle {a vehicle with automatic driving capabilities, Abstract}, the method comprising: in response to completion of a task {arrival of vehicle 50 at property 21, Fig. 3} of the unmanned vehicle at a current node {current position 23, Fig. 3}, receiving a signal input by the radar of the unmanned vehicle containing occupancy state information {occupancy of a garage bay, Col. 3, Lns. 31-41, determined by environmental detection device ”, Col. 5, Lns. 62-67} of a reference start position {the ends of trajectories 30-33, Fig. 3, represent four different locations for positioning vehicle 50 along a trajectory from its current position 23} on a guide line, wherein the guide line is a preset driving route of the unmanned vehicle {the examiner interprets a guideline as reference element, either marked or unmarked, that facilitates driving within a necessary boundary region (which, for example, is the centerline in a two-way traffic road or the unmarked centerline of a single-lane that driver attempts to follow – corresponding to an inherent guideline); with regard to Fig. 3, a preset driving route/guide element is the unmarked centerline leading from the property entrance through the driveway that passes through decision point 36, and then extends through the center of a garage bay} from the current node {current position 23, Fig. 3} to a next node {target positions 40-43, Fig. 3}, the reference start position is a position on the guide line reached by the unmanned vehicle {target positions 40-43, Fig. 3} from a current position {current location 23, Fig. 3}, and the occupancy state information is an occupancy state or a non-occupancy state {determining garage bay occupancy, Col. 5, Lns. 45-51}; in response to a determination that the occupancy state information is the occupancy state {identification of occupancy status Col. 7, Lns. 5-9}, obtaining position data from the positioning device {the use of radar, ultrasonic sensors and LIDAR (Col. 5, Lns. 62-67) and the wireless connectivity (Col. 8, Lns. 16-17) of control unit 3, Fig. 1, corresponds to vehicle 50, Fig. 3, having continuous location information} and projecting the current position {current location 23, Fig. 3} of the unmanned vehicle to the guide line to determine an initial position of the current position on the guide line {the examiner interprets this as the distance between the current position 23 of vehicle 50 from current position 23 to the centerline of the driveway and property entrance 21, which as mentioned above includes decision point 36, Fig. 3, with the initial position being the location the center of the vehicle passes through the property entrance}; determining the reference start position on the guide line {decision made by control unit 2 on where to park the vehicle, such as target positions 41-42 in the garage, Fig. 3}; dynamically generating a target start point sequence {the examiner interprets this as identifying the location options for placing the vehicle that are unoccupied combined with general path planning; this is accomplished via the multiple sensors of the environmental detection device 2 gathering data on all features in the vicinity of the vehicle and providing the data to control unit 3 for processing and path planning, including continuous monitoring the environment to identify if a target position is occupied or becomes occupied during movement, Col. 5, Ln. 62 – Col. 6, Ln. 3, which includes the control system in Fig. 1 needing to determine the exact route (34, Fig. 3) to take from current position 23 to decision point 36 but needing to first determine the precise location of the “current position”, Col. 7, Lns. 23-26; moreover the dynamic nature, or decision making capabilities of the control system in Fig. 1 includes dealing with obstacles that leads to adjusting the positioning of the vehicle, for example, off the centerline of garage, Col. 3, Ln. 66 – Col. 7, Ln. 14, corresponding to adjusting the target location due to a change in the “width” of the garage space} on the basis of the reference start position {target positions 40-43, Fig. 3}, the initial position {decision point 36, Fig. 3}, a left road width of corresponding to the guide line {left boundary of property entrance 21 and driveway, Fig. 3, relative to unmarked centerline of the driveway} and a right road width corresponding to the guide line {right boundary of property entrance 21 and driveway, Fig. 3, relative to the unmarked centerline of the driveway}, wherein each target start point in the target start point sequence is a new position point obtained by iteratively calculating based on the reference start position, the initial position, the left road width and the right road width {expanding on the above discussion of “dynamically generating a target start point sequence”, the combination of the obstacle detection capabilities of the environmental detection device 2 and the ability of the control unit 3 to factor in “additional information” during path planning and execution (Col. 3, Ln. 62 – Col. 4, Ln. 22) leads to the capability: “The control unit then modifies one of the provided trajectories and then carries out the automated drive.”, Col. 4, Lns. 20-22}; and selecting, by the vehicle-mounted autonomous driving controller {control unit 3 carries-out automated driving of a vehicle 50 (Col. 6, Lns. 14-19), as represented in Fig. 3}, a target start point from the target start point sequence as a target start position {selection of target position when vehicle reaches decision point 36 (Fig. 3),”, Col. 5, Lns. 30-61} and controlling the unmanned vehicle to start using the target start position {parking vehicle in left-hand garage 25, Col. 7, Lns. 47-48}, wherein the dynamically generating the target start point sequence on the basis of the reference start position, the initial position, the left road width and the right road width comprises: iteratively updating the reference start position {the examiner interprets this, as above, as simply a first position (the initial position), a second position (the reference start position or final position) and the boundaries of the region (all of which are basic elements that must always be defined for facilitating autonomous driving, as will be appreciated by one skilled in the art), combined with an external factor that necessitate a location of a new final position, all of which was captured above in describing parking in a garage bay when an obstacle is detected} by the following processing steps: determining whether the difference between the reference start position and the initial position {decision point 36, Fig. 3} meets a preset condition {necessary condition is whether target position 40-43 is unoccupied, which is determined by environmental detection device 2 (Fig. 1) and is constantly evaluated as vehicle moves from current location 23 to decision point 36 towards a target position, Col. 5, Lns. 45-61}; in response to condition meeting, generating an alternative start position on the basis of the reference start position and the initial position {user selection of an alternative starting position (i.e., target positions 40-43, Fig. 3) due to occupancy of first target choice, Col. 3, Lns. 39-41} and determining the alternative start position as the reference start position, and performing the processing steps again {based on occupancy evaluation, a processing step must be repeated to determine which trajectory will be implemented, and thus which of target position 40-43, Fig. 3, will the vehicle 50 drive to, as a result of continuous monitoring of the target position and reevaluation as required, Col. 7, Lns. 1-9}.
Derendarz does not appear to explicitly recite the limitations: further processing steps: obtaining position information corresponding to the reference start position, wherein the position information comprises the left road width corresponding to the guide line and the right road width corresponding to the guide line; on the basis of the left road width and the reference start position, generating at least one left alternative start point through a preset threshold; on the basis of the right road width and the reference start position, generating at least one right alternative start point through the preset threshold; merging at least one left alternative start point and the at least one right alternative start point to obtain an alternative start point group.
However, Dou explicitly recites limitations: obtaining position information {the examiner interprets this claim language as representing path planning to provide multiple alternative paths (in the case of obstacle avoidance, for example; data is collected by an information collection unit that includes at least one camera, a radar, and a laser rangefinder (Pg. 6, Lns. 15-25) and localization is provided by a “vehicle-mounted satellite navigation device is installed on the vehicle, and the vehicle's position information can be measured” (Pg. 5, Lns. 11-13)} corresponding to the reference start position {path planning (Pg. 6, Lns. 9-16), wherein a future position (emphasis by examiner) corresponds to changing motion to a different lateral position to avoid an obstacle (Pg. 6, Lns. 1-7)}, wherein the position information comprises the left road width corresponding to the guide line and the right road width corresponding to the guide line {the dividing of all road lanes into sub-lanes, described next, takes into account all lane boundaries}; on the basis of the left road width and the reference start position, generating at least one left alternative start point through a preset threshold; on the basis of the right road width and the reference start position, generating at least one right alternative start point through the preset threshold {an automatic driving system, as part of path planning (Pg. 5, Lns. 19-21), divides each lane into a plurality of sub-lanes (S120, Pg. 5, Lns. 19-21, using the criteria: “Divide the road with a road width greater than or equal to twice the width of the sub-lane into a plurality of sub-lanes”), in order to provide alternative paths when an obstacle is identified, wherein this sub-division inherently is based on the left- and right-lane boundaries, as well as the outer boundaries of the road, in the case of road with more than two lanes; the examiner interprets this claim language as representing path planning to provide multiple alternative paths (in the case of obstacle avoidance, for example; data is collected by an information collection unit that includes at least one camera, a radar, and a laser rangefinder, Pg. 6, Lns. 15-25}; merging at least one left alternative start point and the at least one right alternative start point to obtain an alternative start point group {the examiner interprets this as simply combining elements, or, effectively a form of Routine Optimization [MPEP § 2145. 05(II)]}.
Regarding Claim 10, Derendarz discloses a non-volatile computer-readable medium, storing a computer program thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}, wherein a method for starting {starting an unmanned vehicle is interpreted by the examiner as initiating vehicle movement, in some manner, which is reflected in the vehicle trajectories of Fig. 3} an unmanned vehicle {a vehicle with automatic driving capabilities, Abstract} is implemented when the program is executed by a vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}, the vehicle-mounted autonomous driving controller {control unit 3, Fig. 1} coupled to a senor {environmental detection unit 2 , Fig. 2} and a positioning device of the unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}, and the method for starting the unmanned vehicle comprising: in response to completion of a task {arrival of vehicle 50 at property 21, Fig. 3} of the unmanned vehicle at a current node {current position 23, Fig. 3}, receiving a signal input by the sensor of the unmanned vehicle containing occupancy state information {occupancy of a garage bay, Col. 3, Lns. 31-41, determined by environmental detection device ”, Col. 5, Lns. 62-67} of a reference start position {the ends of trajectories 30-33, Fig. 3, represent four different locations for positioning vehicle 50 along a trajectory from its current position 23} on a guide line, wherein the guide line is a preset driving route of the unmanned vehicle {the examiner interprets a guideline as reference element, either marked or unmarked, that facilitates driving within a necessary boundary region (which, for example, is the centerline in a two-way traffic road or the unmarked centerline of a single-lane that driver attempts to follow – corresponding to an inherent guideline); with regard to Fig. 3, a preset driving route/guide element is the unmarked centerline leading from the property entrance through the driveway that passes through decision point 36, and then extends through the center of a garage bay} from the current node {current position 23, Fig. 3} to a next node {target positions 40-43, Fig. 3}, the reference start position is a position on the guide line reached by the unmanned vehicle {target positions 40-43, Fig. 3} from a current position {current location 23, Fig. 3}, and the occupancy state information is an occupancy state or a non-occupancy state {determining garage bay occupancy, Col. 5, Lns. 45-51}; in response to a determination that the occupancy state information is the occupancy state {identification of occupancy status Col. 7, Lns. 5-9}, obtaining position data from the positioning device {the use of radar, ultrasonic sensors and LIDAR (Col. 5, Lns. 62-67) and the wireless connectivity (Col. 8, Lns. 16-17) of control unit 3, Fig. 1, corresponds to vehicle 50, Fig. 3, having continuous location information} and projecting the current position {current location 23, Fig. 3} of the unmanned vehicle to the guide line to determine an initial position of the current position on the guide line {the examiner interprets this as the distance between the current position 23 of vehicle 50 from current position 23 to the centerline of the driveway and property entrance 21, which as mentioned above includes decision point 36, Fig. 3, with the initial position being the location the center of the vehicle passes through the property entrance}; determining the reference start position on the guide line {decision made by control unit 2 on where to park the vehicle, such as target positions 41-42 in the garage, Fig. 3}; dynamically generating a target start point sequence {the examiner interprets this as identifying the location options for placing the vehicle that are unoccupied combined with general path planning; this is accomplished via the multiple sensors of the environmental detection device 2 gathering data on all features in the vicinity of the vehicle and providing the data to control unit 3 for processing and path planning, including continuous monitoring the environment to identify if a target position is occupied or becomes occupied during movement, Col. 5, Ln. 62 – Col. 6, Ln. 3, which includes the control system in Fig. 1 needing to determine the exact route (34, Fig. 3) to take from current position 23 to decision point 36 but needing to first determine the precise location of the “current position”, Col. 7, Lns. 23-26; moreover the dynamic nature, or decision making capabilities of the control system in Fig. 1 includes dealing with obstacles that leads to adjusting the positioning of the vehicle, for example, off the centerline of garage, Col. 3, Ln. 66 – Col. 7, Ln. 14, corresponding to adjusting the target location due to a change in the “width” of the garage space} on the basis of the reference start position {target positions 40-43, Fig. 3}, the initial position {decision point 36, Fig. 3}, a left road width of corresponding to the guide line {left boundary of property entrance 21 and driveway, Fig. 3, relative to unmarked centerline of the driveway} and a right road width corresponding to the guide line {right boundary of property entrance 21 and driveway, Fig. 3, relative to the unmarked centerline of the driveway}, wherein each target start point in the target start point sequence is a new position point obtained by iteratively calculating based on the reference start position, the initial position, the left road width and the right road width {expanding on the above discussion of “dynamically generating a target start point sequence”, the combination of the obstacle detection capabilities of the environmental detection device 2 and the ability of the control unit 3 to factor in “additional information” during path planning and execution (Col. 3, Ln. 62 – Col. 4, Ln. 22) leads to the capability: “The control unit then modifies one of the provided trajectories and then carries out the automated drive.”, Col. 4, Lns. 20-22}; and selecting, by the vehicle-mounted autonomous driving controller {control unit 3 carries-out automated driving of a vehicle 50 (Col. 6, Lns. 14-19), as represented in Fig. 3}, a target start point from the target start point sequence as a target start position {selection of target position when vehicle reaches decision point 36 (Fig. 3),”, Col. 5, Lns. 30-61} and controlling the unmanned vehicle to start using the target start position {parking vehicle in left-hand garage 25, Col. 7, Lns. 47-48}, wherein the dynamically generating the target start point sequence on the basis of the reference start position, the initial position, the left road width and the right road width comprises: iteratively updating the reference start position {the examiner interprets this, as above, as simply a first position (the initial position), a second position (the reference start position or final position) and the boundaries of the region (all of which are basic elements that must always be defined for facilitating autonomous driving, as will be appreciated by one skilled in the art), combined with an external factor that necessitate a location of a new final position, all of which was captured above in describing parking in a garage bay when an obstacle is detected} by the following processing steps: determining whether the difference between the reference start position and the initial position {decision point 36, Fig. 3} meets a preset condition {necessary condition is whether target position 40-43 is unoccupied, which is determined by environmental detection device 2 (Fig. 1) and is constantly evaluated as vehicle moves from current location 23 to decision point 36 towards a target position, Col. 5, Lns. 45-61}; in response to condition meeting, generating an alternative start position on the basis of the reference start position and the initial position {user selection of an alternative starting position (i.e., target positions 40-43, Fig. 3) due to occupancy of first target choice, Col. 3, Lns. 39-41} and determining the alternative start position as the reference start position, and performing the processing steps again {based on occupancy evaluation, a processing step must be repeated to determine which trajectory will be implemented, and thus which of target position 40-43, Fig. 3, will the vehicle 50 drive to, as a result of continuous monitoring of the target position and reevaluation as required, Col. 7, Lns. 1-9}.
Derendarz does not appear to explicitly recite the limitations: further processing steps: obtaining position information corresponding to the reference start position, wherein the position information comprises the left road width corresponding to the guide line and the right road width corresponding to the guide line; on the basis of the left road width and the reference start position, generating at least one left alternative start point through a preset threshold; on the basis of the right road width and the reference start position, generating at least one right alternative start point through the preset threshold; merging at least one left alternative start point and the at least one right alternative start point to obtain an alternative start point group.
However, Dou explicitly recites limitations: obtaining position information {the examiner interprets this claim language as representing path planning to provide multiple alternative paths (in the case of obstacle avoidance, for example; data is collected by an information collection unit that includes at least one camera, a radar, and a laser rangefinder (Pg. 6, Lns. 15-25) and localization is provided by a “vehicle-mounted satellite navigation device is installed on the vehicle, and the vehicle's position information can be measured” (Pg. 5, Lns. 11-13)} corresponding to the reference start position {path planning (Pg. 6, Lns. 9-16), wherein a future position (emphasis by examiner) corresponds to changing motion to a different lateral position to avoid an obstacle (Pg. 6, Lns. 1-7)}, wherein the position information comprises the left road width corresponding to the guide line and the right road width corresponding to the guide line {the dividing of all road lanes into sub-lanes, described next, takes into account all lane boundaries}; on the basis of the left road width and the reference start position, generating at least one left alternative start point through a preset threshold; on the basis of the right road width and the reference start position, generating at least one right alternative start point through the preset threshold {an automatic driving system, as part of path planning (Pg. 5, Lns. 19-21), divides each lane into a plurality of sub-lanes (S120, Pg. 5, Lns. 19-21, using the criteria: “Divide the road with a road width greater than or equal to twice the width of the sub-lane into a plurality of sub-lanes”), in order to provide alternative paths when an obstacle is identified, wherein this sub-division inherently is based on the left- and right-lane boundaries, as well as the outer boundaries of the road, in the case of road with more than two lanes; the examiner interprets this claim language as representing path planning to provide multiple alternative paths (in the case of obstacle avoidance, for example; data is collected by an information collection unit that includes at least one camera, a radar, and a laser rangefinder, Pg. 6, Lns. 15-25}; merging at least one left alternative start point and the at least one right alternative start point to obtain an alternative start point group {the examiner interprets this as simply combining elements, or, effectively a form of Routine Optimization [MPEP § 2145. 05(II)]}.
Regarding Claim 11, the combination of Derendarz and Dou discloses all the limitations of Claim 3, as discussed supra. In addition, Derendarz explicitly recites the limitations: wherein the generating an alternative start position on the basis of the reference start position and the initial position comprises: generating an initial start position on the basis of the reference start position and the initial position {distance between decision point 36, Fig. 3, and a target position 40-43}; and determining the sum of the initial start position and the initial position as an alternative start position {one skilled in the art will appreciate the final position of the vehicle, after starting at current position 23 and passing through decision point 36 and target position 40, can be target position 43, corresponding to a longer trajectory, Fig. 3}.
Regarding Claim 15, the combination of Derendarz and Dou discloses all the limitations of Claim 6, as discussed supra. In addition, Derendarz explicitly recites the limitations: the method further comprises: generating a driving track according to the current position and the target start position {the sum of trajectories 32 and 34, Fig. 3}; controlling the unmanned vehicle to drive according to the driving track {parking vehicle in left-hand garage 25, Col. 7, Lns. 47-48}; and in response to the distance between the unmanned vehicle and the target start position meeting a first target condition {minimum distance to an obstacle, Col. 4, Lns. 2-5} and the driving direction of the unmanned vehicle meeting a second target condition {whether vehicle is to be parked in the forward or reverse direction, Col. 3, Lns. 15-16}, generating the target start point sequence again {the control system in Fig. 1 is constantly monitoring if a target position is occupied or unoccupied (Col. 7, Lns. 1-9), wherein occupation may be an obstacle requiring an adjustment in the final position of the vehicle (Col. 3, Ln. 66 – Col. 7, Ln. 14), corresponding to adjusting the target location due to a change in the effective width of the garage space}.
Regarding Claim 16, the combination of Derendarz and Dou discloses all the limitations of Claim 6, as discussed supra. In addition, Derendarz explicitly recites the limitations: an electronic device {device 1, Col. 6, Lns. 14-19 and Fig. 1}, comprising: at least one vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}; a storage apparatus {memory 4, Fig. 1}, having at least one program stored thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}; and a radar, configured to monitor objects {environmental detection device includes radar, Col. 5, Lns. 65-67}; wherein the vehicle-mounted autonomous driving controller is coupled to the radar {environmental detection device 2 relative to control unit 2 in Fig. 1} and a positioning device of an unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}, and when executed by the at least one vehicle-mounted autonomous driving controller, the at least one program enables the at least one vehicle-mounted autonomous driving controller to implement a method for starting {starting an unmanned vehicle is interpreted by the examiner as initiating vehicle movement, in some manner, which is reflected in the vehicle trajectories of Fig. 3} an unmanned vehicle {a vehicle with automatic driving capabilities, Abstract} according to Claim 6 {see Claim 6 above}.
Regarding Claim 17, the combination of Derendarz and Dou discloses all the limitations of Claim 3, as discussed supra. In addition, Derendarz explicitly recites the limitations: an electronic device {device 1, Col. 6, Lns. 14-19 and Fig. 1}, comprising: at least one vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}; a storage apparatus {memory 4, Fig. 1}, having at least one program stored thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}; and a radar, configured to monitor objects {environmental detection device includes radar, Col. 5, Lns. 65-67}; wherein the vehicle-mounted autonomous driving controller is coupled to the radar {environmental detection device 2 relative to control unit 2 in Fig. 1} and a positioning device of an unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}, and when executed by the at least one vehicle-mounted autonomous driving controller, the at least one program enables the at least one vehicle-mounted autonomous driving controller to implement a method for starting {starting an unmanned vehicle is interpreted by the examiner as initiating vehicle movement, in some manner, which is reflected in the vehicle trajectories of Fig. 3} an unmanned vehicle {a vehicle with automatic driving capabilities, Abstract} according to Claim 3 {see Claim 3 above}.
Regarding Claim 18, the combination of Derendarz and Dou discloses all the limitations of Claim 4, as discussed supra. In addition, Derendarz explicitly recites the limitations: an electronic device {device 1, Col. 6, Lns. 14-19 and Fig. 1}, comprising: at least one vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}; a storage apparatus {memory 4, Fig. 1}, having at least one program stored thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}; and a radar, configured to monitor objects {environmental detection device includes radar, Col. 5, Lns. 65-67}; wherein the vehicle-mounted autonomous driving controller is coupled to the radar {environmental detection device 2 relative to control unit 2 in Fig. 1} and a positioning device of an unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}, and when executed by the at least one vehicle-mounted autonomous driving controller, the at least one program enables the at least one vehicle-mounted autonomous driving controller to implement a method for starting {starting an unmanned vehicle is interpreted by the examiner as initiating vehicle movement, in some manner, which is reflected in the vehicle trajectories of Fig. 3} an unmanned vehicle {a vehicle with automatic driving capabilities, Abstract} according to Claim 4 {see Claim 4 above}.
Regarding Claim 19, the combination of Derendarz and Dou discloses all the limitations of Claim 6, as discussed supra. In addition, Derendarz explicitly recites the limitations: a non-volatile computer-readable medium, storing a computer program thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}, wherein the method according to claim 6 {see Claim 6 above} is implemented when the program is executed by a vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}, the vehicle-mounted autonomous driving controller {control unit 3, Fig. 1} coupled to a senor {environmental detection unit 2 , Fig. 2} and a positioning device of the unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}.
Regarding Claim 20, the combination of Derendarz and Dou discloses all the limitations of Claim 3, as discussed supra. In addition, Derendarz explicitly recites the limitations: a non-volatile computer-readable medium, storing a computer program thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}, wherein the method according to claim 3 {see Claim 3 above} is implemented when the program is executed by a vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}, the vehicle-mounted autonomous driving controller {control unit 3, Fig. 1} coupled to a senor {environmental detection unit 2 , Fig. 2} and a positioning device of the unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}.
Regarding Claim 21, the combination of Derendarz and Dou discloses all the limitations of Claim 4, as discussed supra. In addition, Derendarz explicitly recites the limitations: a non-volatile computer-readable medium, storing a computer program thereon {control unit 3 and memory 4, Fig. 1, are part of a computerized system which inherently includes code and programming}, wherein the method according to claim 4 {see Claim 4 above} is implemented when the program is executed by a vehicle-mounted autonomous driving controller {control unit 3, Fig. 1}, the vehicle-mounted autonomous driving controller {control unit 3, Fig. 1} coupled to a senor {environmental detection unit 2 , Fig. 2} and a positioning device of the unmanned vehicle {various sensors, including Lidar, with the capability of locating the position of the vehicle are described in Col. 5, Lns. 62-67}.
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 RICHARD EDWIN GEIST whose telephone number is (703)756-5854. The examiner can normally be reached Monday-Friday, 9am-6pm.
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/R.E.G./Examiner, Art Unit 3665
/CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665
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