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 .
DETAILED ACTION
This Office action is in response to Applicant’s Amendments/Remarks filed 6/8/2026.
Response to Arguments
Claim objections of the most recent Office action have been removed due to Applicant’s amendments.
Applicant’s arguments filed 6/8/2026, pg(s). 11-14, with respect to the prior art rejections to the pending claims have been considered but are moot in view of the newly formulated rejection necessitated by Applicant’s amendments.
The nonstatutory double patenting rejections of the most recent Office action have been removed due to Applicant’s amendments.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim(s) 5-8, 10, 12, 16-17, 19 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim(s) 5, it is unclear whether the “an acceleration/deceleration tendency of the driver” is the “acceleration/deceleration tendency of the driver” of claim 1, or if they’re entirely different components, and thus, the claim is indefinite. For the purposes of examination, the examiner is interpreting them to be the same component.
Regarding claim(s) 10, it is unclear whether the “an acceleration/deceleration tendency of the driver” is the “acceleration/deceleration tendency of the driver” of claim 1, or if they’re entirely different components, and thus, the claim is indefinite. For the purposes of examination, the examiner is interpreting them to be the same component.
Regarding claim(s) 16, it is unclear whether the “an acceleration/deceleration tendency of the driver” is the “acceleration/deceleration tendency of the driver” of claim 13, or if they’re entirely different components, and thus, the claim is indefinite. For the purposes of examination, the examiner is interpreting them to be the same component.
Regarding claim(s) 19, it is unclear whether the “an acceleration/deceleration tendency of the driver” is the “acceleration/deceleration tendency of the driver” of claim 13, or if they’re entirely different components, and thus, the claim is indefinite. For the purposes of examination, the examiner is interpreting them to be the same component.
Dependent claims inherit rejections of the claims they depend upon.
Claim Rejections - 35 USC § 102 / Claim Rejections - 35 USC § 103
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1, 13 is/are rejected under 35 U.S.C. 102(a)(1) as anticipated by Luo et al. (WO2023125849 (A1)) or, in the alternative, under 35 U.S.C. 103 as obvious over of Ito et al. (US 20230234587 A1) in view of Luo et al. (WO2023125849 (A1)).
Regarding claim 1, and similarly claim 13, Luo teaches An autonomous driving control apparatus comprising:
a memory (“memory”, [0135]) configured to store computer-executable instructions (“This application also provides an electronic device, including a memory and a processor. The memory is used to store a program that supports the processor in executing the ACC following distance adjustment display interaction method described in Embodiment 1 above. The processor is configured to execute the program stored in the memory.”, [0135]); and
at least one processor (“processor”, [0135]) configured, by executing the computer-executable instructions by accessing the memory, to
identify at least one of a first driving status of a target vehicle, a second driving status of a forward vehicle driving around the target vehicle, a state of a driver of the target vehicle (“braking distance output by the rule model”, [0016]), energy consumption predicted according to information about a front road, or any combination thereof (“Different drivers set different following distances and cruise speeds based on their driving skills. Different following distances and speeds correspond to different braking distances. At the same time, the driver's ideal braking distance and the expected braking distance of ACC may not be the same. This can lead to some drivers having uncertainty about the status of ACC or the braking distance, and in some cases, they may actively brake to suppress the function of ACC.”, [0079], “Thirdly, embodiments of this application provide a method for calculating braking distance, comprising: acquiring current driving behavior data of a target user in adaptive cruise mode; inputting the current driving behavior data into a pre-trained rule model to obtain a braking distance output by the rule model based on the current driving behavior data; wherein the rule model is trained based on the target user's historical braking behavior data.”, [0016]), and
control the target vehicle in a first control mode, based on at least one of the first driving status, the second driving status, the state of the driver of the target vehicle, the energy consumption, or any combination thereof, wherein in the first control mode, a speed of the target vehicle follows a target speed section including a goal speed (“In one implementation, the target user is the driver, and the current driving behavior data is the driver's behavior data when the ACC function is activated, including: time information, weather information, relative speed and relative distance to target objects (such as vehicles, pedestrians, obstacles, etc.), vehicle deceleration, road curvature, and other information.”, [0083], see also [0079]),
wherein, to identify the state of the driver of the target vehicle, the at least one processor is configured to:
determine an acceleration/deceleration tendency of the driver by applying acceleration/deceleration operations of the driver to a driver acceleration/deceleration decision model (“Step S1201: Obtain the target user's current driving behavior data in adaptive cruise mode.”, [0082], “Step S1202: Input the current driving behavior data into the pre-trained rule model to obtain the braking distance output by the rule model based on the current driving behavior data; wherein, the rule model is trained based on the target user's historical braking behavior data.”, [0084]); and
identify the state of the driver based on the acceleration/deceleration tendency of the driver (“In one implementation, the rule model can be obtained by analyzing historical behavioral data of drivers taking active braking when the ACC function is activated, and training a machine learning model based on the results of the analysis. When ACC cruise control or follow mode is activated, the rule model can output the corresponding braking distance based on different driving behavior data, thereby meeting the driver's ideal braking distance.”, [0085]).
Regarding claim 1, and similarly claim 13, Ito teaches An autonomous driving control apparatus comprising:
a memory (see “ROM”, [0054] citation below) configured to store computer-executable instructions; and
at least one processor (“The ECU 90 includes a microcomputer as a main component. The microcomputer includes a CPU, a ROM, a RAM, a non-volatile memory, and an interface. The CPU is configured or programmed to realize various functions by executing instructions, programs, and routines stored in the ROM. In particular, a vehicle driving assistance program of executing a driving assistance control described later in detail as one of automatic driving controls or autonomous driving controls, is stored in the ROM, and the CPU executes the driving assistance control by executing the vehicle driving assistance program.”, [0034]) configured, by executing the computer-executable instructions by accessing the memory, to
identify at least one of a first driving status of a target vehicle, a second driving status of a forward vehicle driving around the target vehicle, a state of a driver of the target vehicle, energy consumption predicted according to information about a front road, or any combination thereof (“When the vehicle moving speed setting switch is operated while the moving assistance control is executed, a signal is sent from the moving assistance operator 51 to the ECU 90. When the ECU 90 receives the signal in question, the ECU 90 sets the current own vehicle moving speed V1 as a set speed Vset which is used by the moving assistance control.”, [0084], see also Figs. 5, 12-14), and
control the target vehicle in a first control mode, based on at least one of the first driving status, the second driving status, the state of the driver of the target vehicle, the energy consumption, or any combination thereof, wherein in the first control mode, a speed of the target vehicle follows a target speed section including a goal speed (“The ordinary constant speed acceleration control is a control to (i) calculate and acquire the driving torque to be output from the driving apparatus 21 so as to maintain the own vehicle moving speed V1 at the set speed Vset.”, [0161], see also Figs. 5, 12-14),
However, Luo teaches
wherein, to identify the state of the driver of the target vehicle, the at least one processor is configured to:
determine an acceleration/deceleration tendency of the driver by applying acceleration/deceleration operations of the driver to a driver acceleration/deceleration decision model (“Step S1201: Obtain the target user's current driving behavior data in adaptive cruise mode.”, [0082], “Step S1202: Input the current driving behavior data into the pre-trained rule model to obtain the braking distance output by the rule model based on the current driving behavior data; wherein, the rule model is trained based on the target user's historical braking behavior data.”, [0084]); and
identify the state of the driver based on the acceleration/deceleration tendency of the driver (“In one implementation, the rule model can be obtained by analyzing historical behavioral data of drivers taking active braking when the ACC function is activated, and training a machine learning model based on the results of the analysis. When ACC cruise control or follow mode is activated, the rule model can output the corresponding braking distance based on different driving behavior data, thereby meeting the driver's ideal braking distance.”, [0085]).
Both Ito and Luo teach controlling a target vehicle in a first control mode where a speed of the target vehicle follows a goal speed. Luo further teaches controlling the target vehicle in the first control mode based on the acceleration/deceleration tendency of a driver. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Ito with the teachings of Luo such that the controlling the target vehicle in the first control mode of Ito is further based on the acceleration/deceleration tendency of the driver, as suggested by Luo, with a reasonable expectation of success. The motivation for doing so would be to “output the corresponding braking distance based on different driving behavior data, thereby meeting the driver's ideal braking distance” [0085], as taught by Luo.
Claim(s) 2-4, 9-10, 14-15, 18-19 is/are rejected under 35 U.S.C. 103 as obvious over of Ito et al. (US 0230234587 A1) in view of Luo et al. (WO2023125849 (A1)).
Regarding claim 2, and similarly claim 14, Ito in view of Luo teaches The autonomous driving control apparatus of claim 1, and Ito further teaches wherein the at least one processor is configured to:
identify the first driving status based on at least one of the goal speed received from the driver, a goal distance, the speed of target vehicle, map information of the front road obtained from a navigation of the target vehicle, information of a brake pedal sensor (BPS) of the target vehicle, or any combination thereof, wherein the goal distance is received together with the goal speed and is a keeping distance between the forward vehicle and the target vehicle (“When the vehicle moving speed setting switch is operated while the moving assistance control is executed, a signal is sent from the moving assistance operator 51 to the ECU 90. When the ECU 90 receives the signal in question, the ECU 90 sets the current own vehicle moving speed V1 as a set speed Vset which is used by the moving assistance control.”, [0084]);
identify the second driving status including a distance between the target vehicle and the forward vehicle based on at least one of a RADAR sensor, a LiDAR sensor, or any combination thereof, wherein the RADAR sensor, the LiDAR sensor, or any combination thereof is included in the target vehicle (“proceeds with the process to a step 530 to determine whether there is the preceding vehicle 200F”, [0189], “The ECU 90 acquires the inter-vehicle distance D between the preceding vehicle 200F and the own vehicle 100 and a preceding vehicle moving speed V2, i.e., a moving speed of the preceding vehicle 200F, based on the surrounding detection information IS”, [0101], “The radio wave sensor 61 is a sensor which detects information on objects around the own vehicle 100 by using radio waves. The radio wave sensor 61 may include a radar sensor such as a millimeter wave radar, or a sonic sensor such as an ultrasonic sensor such as a clearance sonar, or an optical sensor such as a laser radar such as a LiDAR.”, [0098], see also Fig. 12 and [0100]);
determine second control torque of a second control mode, based on at least one of the first driving status, the second driving status, or any combination thereof, wherein in the second control mode, the speed of the target vehicle follows the goal speed (“The ordinary following acceleration control is a control to (i) calculate and acquire the driving torque to be output from the driving apparatus 21 so as to maintain the predicted reaching time TTC at the predetermined predicted reaching time TTCref, (ii) set the acquired driving torque as the system requested driving torque TQ1sys_req, and (iii) cause the driving apparatus 21 to output the driving torque corresponding to the set system request driving torque TQ1sys_req.”, [0149], see also Fig. 13).; and
control the target vehicle such that the speed of the target vehicle follows the goal speed, by applying the second control torque to the target vehicle (see [0149] citation above and Fig. 13).
Regarding claim 9, and similarly claim 18, Ito in view of Luo teaches The autonomous driving control apparatus of claim 2, and Ito further teaches wherein the at least one processor is configured to:
release the first control mode applied to the target vehicle (see “execute an ordinary following acceleration control”, [0148] citation below); and
control the target vehicle in the second control mode based on the target vehicle (“when the vehicle driving assistance apparatus 10 proceeds with the process to the step 1305, the vehicle driving assistance apparatus 10 determines whether the ordinary following acceleration condition C3 is satisfied. When the ordinary following acceleration condition C3 is satisfied, the vehicle driving assistance apparatus 10 determines “Yes” at the step 1305 and proceeds with the process to a step 1310 to execute an ordinary following acceleration control.”, [0148]),
wherein the first control mode is applied to the target vehicle, satisfying an inverse conversion condition that a control mode of the target vehicle is capable of being converted from the first control mode to the second control mode (“When there is the preceding vehicle 200F, the vehicle driving assistance apparatus 10 determines “Yes” at the step 1205 and proceeds with the process to a step 1210 to execute the ordinary following control by executing the routine shown in FIG. 13. Thus, when the vehicle driving assistance apparatus 10 proceeds with the process to the step 1210, the vehicle driving assistance apparatus 10 starts a process from a step 1300 of the routine shown in FIG. 13 and proceeds with the process to a step 1305.”, [0146]), and
wherein the inverse conversion condition is determined by the first driving status, the second driving status, and the state of the driver (Figs. 2, 5, 11-13).
Regarding claim 3, and similarly claim 15, Ito in view of Luo teaches The autonomous driving control apparatus of claim 1, and Ito further teaches wherein the at least one processor is configured to:
determine a first prediction area, wherein the first prediction area is an area where the forward vehicle is capable of being identified by at least one of a RADAR sensor, a LiDAR sensor, or any combination thereof, and the RADAR sensor, the LiDAR sensor, or any combination thereof is included in the target vehicle (“The radio wave sensor 61 is a sensor which detects information on objects around the own vehicle 100 by using radio waves. The radio wave sensor 61 may include a radar sensor such as a millimeter wave radar, or a sonic sensor such as an ultrasonic sensor such as a clearance sonar, or an optical sensor such as a laser radar such as a LiDAR.”, [0098]);
determine a second prediction area, wherein the second prediction area is an area spaced from a location of the target vehicle by a predetermined distance in map information of the front road obtained from a navigation of the target vehicle (“the vehicle driving assistance apparatus 10 calculates and acquires the consumed energy amount of the driving apparatus 21 for moving the own vehicle 100 by the ordinary following control, based on the size of the preceding vehicle 200F, the predicted inter-vehicle distance D, and the predicted own vehicle moving speed V1.”, [0201], “as shown in FIG. 15, the vehicle driving assistance apparatus 10 previously stores a map or a look-up table for each kind of the preceding vehicle 200F for acquiring the consumed energy amount of the driving apparatus 21, based on the inter-vehicle distance D and the own vehicle moving speed V1. Therefore, the vehicle driving assistance apparatus 10 selects the map corresponding to the kind of the preceding vehicle 200F and acquires the consumed energy amount of the driving apparatus 21 for moving the own vehicle 100 by the ordinary following control by integrating the consumed energy amounts acquired by applying the inter-vehicle distance D and the own vehicle moving speed V1 predicted as described above to the selected map.”, [0202]); and
control the target vehicle in the first control mode based on the second driving status and the predicted energy consumption, wherein the second driving status is obtained through the first prediction area (“proceeds with the process to a step 530 to determine whether there is the preceding vehicle 200F”, [0189], “The ECU 90 acquires the inter-vehicle distance D between the preceding vehicle 200F and the own vehicle 100 and a preceding vehicle moving speed V2, i.e., a moving speed of the preceding vehicle 200F, based on the surrounding detection information IS”, [0101], “The radio wave sensor 61 is a sensor which detects information on objects around the own vehicle 100 by using radio waves. The radio wave sensor 61 may include a radar sensor such as a millimeter wave radar, or a sonic sensor such as an ultrasonic sensor such as a clearance sonar, or an optical sensor such as a laser radar such as a LiDAR.”, [0098], see also Fig. 12 and [0100]), and the predicted energy consumption is obtained through the second prediction area (“the optimum acceleration control may be a control to autonomously accelerate the own vehicle 100 by operating the driving apparatus 21 with an optimum consumed energy amount including the smallest consumed energy amount and the consumed energy amount slightly greater than the smallest consumed energy amount.”, [0116]).
Regarding claim 4, Ito in view of Luo teaches The autonomous driving control apparatus of claim 3, and Ito further teaches wherein the at least one processor is configured to:
determine at least one of a distance between the target vehicle and the forward vehicle, a relative speed between the target vehicle and the forward vehicle, or any combination thereof by identifying the forward vehicle in the first prediction area (“As shown in FIG. 2, the inter-vehicle distance D is a distance between the own vehicle 100 and the preceding vehicle 200F and is acquired, based on surrounding detection information IS described later in detail.”, [0087], “The ECU 90 acquires the inter-vehicle distance D between the preceding vehicle 200F and the own vehicle 100 and a preceding vehicle moving speed V2, i.e., a moving speed of the preceding vehicle 200F, based on the surrounding detection information IS.”, [0087]);
control the target vehicle in the first control mode based on at least one of the distance between the target vehicle and the forward vehicle, the relative speed between the target vehicle and the forward vehicle, the gradient of the front road, the curvature of the front road, or any combination thereof (“when the ECU 90 receives the requested inter-vehicle distance signal, the ECU 90 sets a set inter-vehicle distance Dset, based on the current own vehicle moving speed V1 and the requested inter-vehicle distance Dreq. In this regard, the ECU 90 may be configured to set the set inter-vehicle distance Dset, based on the requested inter-vehicle distance Dreq, independently of the current own vehicle moving speed V1.”, [0088], see also [0107]).
Luo further teaches
determine at least one of a gradient of the front road, curvature of the front road, or any combination thereof based on the map information in the second prediction area (“to facilitate data collection, under the condition that the vehicle's ACC is normally activated, information such as the time of the driver's active braking, weather information, relative speed and relative distance to target objects (such as vehicles, pedestrians, obstacles, etc.), vehicle deceleration, road curvature, and braking distance of the driver's active braking can be collected under different time periods, different scenarios, different weather conditions, and different road conditions.”, [0091], see also [0082-0083, 0118-0119]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to further modify the invention of Ito with the teachings of Luo such that the controlling the target vehicle in the first control mode is further based on a curvature of the front road, as suggested by Luo, with a reasonable expectation of success. The motivation for doing so would be to “improv[e] safety and driver comfort” by “analyz[ing] the driver's active braking behavior data when the ACC function is activated” [0118] based on “the current driving behavior data…including…road curvature” [0083], as taught by Luo.
Regarding claim 10, and similarly claim 19, Ito in view of Luo teaches The autonomous driving control apparatus of claim 1, and Ito further teaches wherein the at least one processor is configured to:
identify driving information for determining a driving tendency of the driver based on at least one of the first driving status, the second driving status, or any combination thereof not being identified (“the own vehicle 100 is installed with an accelerator pedal 41, an accelerator pedal operation amount sensor 42, a brake pedal 43, a brake pedal operation amount sensor 44, a steering wheel 45, a steering angle sensor 46, a steering torque sensor 47, a vehicle moving speed detection apparatus 48”, [0065], see also [0065] and Fig. 5);
Luo further teaches
store an acceleration/deceleration tendency of the driver obtained from the driving information in the target vehicle at a predetermined time interval (“In one implementation, the rule model can be obtained by analyzing historical behavioral data of drivers taking active braking when the ACC function is activated, and training a machine learning model based on the results of the analysis. When ACC cruise control or follow mode is activated, the rule model can output the corresponding braking distance based on different driving behavior data, thereby meeting the driver's ideal braking distance.”, [0085], “to facilitate data collection, under the condition that the vehicle's ACC is normally activated, information such as the time of the driver's active braking, weather information, relative speed and relative distance to target objects (such as vehicles, pedestrians, obstacles, etc.), vehicle deceleration, road curvature, and braking distance of the driver's active braking can be collected under different time periods, different scenarios, different weather conditions, and different road conditions.”, [0091]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to further modify the invention of Ito with the teachings of Luo such that an acceleration/deceleration tendency of the driver obtained from the driving information is stored, as suggested by Luo, with a reasonable expectation of success. The motivation for doing so would be to “output the corresponding braking distance based on different driving behavior data, thereby meeting the driver's ideal braking distance” [0085], as taught by Luo.
Claim(s) 5, 11-12, 16, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ito et al. (US 20230234587 A1) in view of Luo et al. (WO2023125849 (A1)) in view of Suzuki (US 20250018942 A1).
Regarding claim 5, and similarly claim 16, Ito in view of Luo teaches The autonomous driving control apparatus of claim 2, and Ito further teaches wherein the at least one processor is configured to:
determine first control torque of the first control mode based on at least one of the first driving status, the second driving status, the state of the driver, or any combination thereof (“The ordinary constant speed acceleration control is a control to (i) calculate and acquire the driving torque to be output from the driving apparatus 21 so as to maintain the own vehicle moving speed V1 at the set speed Vset, (ii) set the acquired driving torque as the system requested driving torque TQ1sys_req, and (iii) cause the driving apparatus 21 to output the driving torque corresponding to the set system requested driving torque TQ1sys_req.”, [0161]); and
control the target vehicle such that the speed of the target vehicle follows the target speed section, by applying the first control torque to the target vehicle (see [0161] citation above and Fig. 14).
Luo further teaches
identify the state of the driver based on an acceleration/deceleration tendency of the driver determined repeatedly for a predetermined period of time (“In one implementation, the rule model can be obtained by analyzing historical behavioral data of drivers taking active braking when the ACC function is activated, and training a machine learning model based on the results of the analysis. When ACC cruise control or follow mode is activated, the rule model can output the corresponding braking distance based on different driving behavior data, thereby meeting the driver's ideal braking distance.”, [0085], “to facilitate data collection, under the condition that the vehicle's ACC is normally activated, information such as the time of the driver's active braking, weather information, relative speed and relative distance to target objects (such as vehicles, pedestrians, obstacles, etc.), vehicle deceleration, road curvature, and braking distance of the driver's active braking can be collected under different time periods, different scenarios, different weather conditions, and different road conditions.”, [0091]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to further modify the invention of Ito with the teachings of Luo such that the first torque control of Ito is further based the acceleration/deceleration tendency of the driver determined repeatedly for a predetermined period of time, as suggested by Luo, with a reasonable expectation of success. The motivation for doing so would be to “output the corresponding braking distance based on different driving behavior data, thereby meeting the driver's ideal braking distance” [0085], as taught by Luo.
Further, Suzuki teaches
identify the first driving status based on weight of the target vehicle determined based on at least one of acceleration of the target vehicle, the speed of the target vehicle, longitudinal acceleration of the target vehicle, a wheel speed of the target vehicle, or any combination thereof (“The weight calculation unit M11 uses the following expression 3 to calculate the weight m of the vehicle 10 from the thrusts FL, FR of the drive wheels 21, 22 and the acceleration u in the traveling direction of the vehicle.”, [0046]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Ito in view of Luo with the teachings of Suzuki such that the first driving status of Ito is based on a weight of the target vehicle determined by an acceleration of the vehicle, as suggested by Suzuki, with a reasonable expectation of success. This would achieve the predictable result of calculating a torque of the target vehicle based on a weight of the vehicle, which was a well-known practice at the time of filing, as suggested by Suzuki [0022-0023]. KSR International Co. v. Teleflex Inc. (KSR), 550 U.S. 398, 82 USPQ2d 1385 (2007).
Regarding claim 12, Ito in view of Luo and Suzuki teaches The autonomous driving control apparatus of claim 5, and Ito further teaches wherein the target vehicle includes an electric vehicle configured to move by applying the first control torque to a drive motor (“The driving apparatus 21 is an apparatus which outputs a driving force or a driving torque to be applied to the own vehicle 100 to move the same. In this embodiment, the driving apparatus 21 includes two power sources, i.e., a first power source 211 and a second power source 212. The first power source 211 and the second power source 212 have different power output properties. For example, the first power source 211 is an internal combustion engine, and the second power source 212 is at least one electric motor.”, [0059]).
Regarding claim 11, and similarly claim 20, Ito in view of Luo teaches The autonomous driving control apparatus of claim 1, and Ito further teaches wherein the at least one processor is configured to:
obtain first control torque of the first control mode by applying the first driving status, the second driving status, the state of the driver, (“The ordinary constant speed acceleration control is a control to (i) calculate and acquire the driving torque to be output from the driving apparatus 21 so as to maintain the own vehicle moving speed V1 at the set speed Vset, (ii) set the acquired driving torque as the system requested driving torque TQ1sys_req, and (iii) cause the driving apparatus 21 to output the driving torque corresponding to the set system requested driving torque TQ1sys_req.”, [0161], “The optimum acceleration control is a control to autonomously accelerate the own vehicle 100 by calculating and acquiring an optimum driving torque, setting the acquired optimum driving torque as a system requested driving torque TQ1sys_req, and causing the driving apparatus 21 to output the driving torque corresponding to the system requested driving torque TQ1sys_req. The optimum driving torque is the driving torque which realizes a greatest energy efficiency of the driving apparatus 21 or an energy efficiency of the driving apparatus 21 close to the greatest energy efficiency, depending on the current own vehicle moving speed V1.”, [0111], “when the accelerator pedal 41 is released, and the driver requested driving torque TQ1drv_req becomes equal to or smaller than the system requested driving torque TQ1sys_req, the vehicle driving assistance apparatus 10 restarts to execute the ordinary following control.”, [0157]); and
control the target vehicle such that the speed of the target vehicle follows the target speed section, by applying the first control torque to the target vehicle (see [0161] citation above and Fig. 14).
However, Suzuki teaches
weight of the target vehicle (“The weight calculation unit M11 uses the following expression 3 to calculate the weight m of the vehicle 10 from the thrusts FL, FR of the drive wheels 21, 22 and the acceleration u in the traveling direction of the vehicle.”, [0046]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Ito in view of Luo with the teachings of Suzuki such that the first control torque of Ito is further based on a weight of the target vehicle, as suggested by Suzuki, with a reasonable expectation of success. This would achieve the predictable result of calculating a torque of the target vehicle based on a weight of the vehicle, which was a well-known practice at the time of filing, as suggested by Suzuki [0022-0023]. KSR International Co. v. Teleflex Inc. (KSR), 550 U.S. 398, 82 USPQ2d 1385 (2007).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ito et al. (US 20230234587 A1) in view of Luo et al. (WO2023125849 (A1)) in view of Suzuki (US 20250018942 A1) in view of Fallah (“The car that slows down for speed cameras”).
Regarding claim 6, Ito in view of Luo and Suzuki teaches The autonomous driving control apparatus of claim 5, wherein the at least one processor is configured to:
release the first control mode applied to the target vehicle by identifying an external device configured to detect a speed at a predetermined distance based on a location of the target vehicle from the first driving status.
However, Fallah teaches
release the first control mode applied to the target vehicle by identifying an external device configured to detect a speed at a predetermined distance based on a location of the target vehicle from the first driving status (“We tested this system in Seoul last week by having the active cruise control set to 150km/h and allowing the car’s computers to take full control of the Genesis’ speed. The onboard computers used GPS data to gradually slow the car down to match the 100km/h speed camera zone from around 800m before the speed camera’s location, only to resume the set speed once the camera was passed.”, pg. 1, last two paragraphs).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Ito in view of Luo and Suzuki with the teachings of Fallah such that the first control mode of Ito is released by identifying an external device configured to detect a speed of the target vehicle, as suggested by Fallah, with a reasonable expectation of success. The motivation for doing so would be because “the car’s ability to slow itself down should help reduce the number of accidents and allow the driver to concentrate on driving rather than focusing so thoroughly on the vehicle’s speed” (pg. 2, last paragraph), as taught by Fallah.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ito et al. (US 20230234587 A1) in view of Luo et al. (WO2023125849 (A1)) in view of Suzuki (US 20250018942 A1) in view of Wada (US 20190071085 A1).
Regarding claim 7, Ito in view of Luo and Suzuki teaches The autonomous driving control apparatus of claim 5, wherein the at least one processor is configured to:
However, Wada teaches
release the first control mode applied to the target vehicle by identifying that the distance between the forward vehicle and the target vehicle is smaller than or equal to a predetermined distance from the second driving status (“a terminating distance DC is set which is a distance for the individual controller Hm (transport vehicle 2) to terminate (end) the vehicle following mode F. So, the vehicle following mode F is terminated if the inter-vehicle distance D between a transport vehicle (transport vehicle 2R traveling behind) and a transport vehicle 2F traveling ahead of it becomes less than, or equal to, the terminating distance DC.”, [0048]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the invention of Ito in view of Luo and Suzuki with the teachings of Wada such that the first control mode of Ito is released when a distance between the forward vehicle and the target vehicle is smaller than or equal to a predetermined distance, as suggested by Wada, with a reasonable expectation of success. The motivation for doing so would be to decrease the possibility of collision and increase occupant comfort by not allowing the target vehicle to travel within a threshold distance of the forward vehicle.
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 extension fee 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 date of this final action.
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/AMELIA VORCE/ Primary Examiner, Art Unit 3666
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