DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Pending
1-11, 13, 15-22
Cancelled
12, 14, 23
35 U.S.C. 103
1-11, 13, 15-22
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/11/2026 has been entered.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d), regarding Application No. KR 10-2023-0096371, filed on 07/24/2023, which is being used as the earliest priority date for the recited claims. Examiner also acknowledges the “Request for USPTO to retrieve priority docs” filed 03/11/2026, and hopes the Patents Electronic Business Center and request for escalation will be fulfilled as soon as possible.
Claim Objections
Claim 1 and 17 are objected to because of the following informalities. Both claims recite “stuck mode determiner is configured apply the autonomous control mode”. These claims should be amended to recite “stuck mode determiner is configured to apply the autonomous control mode”. Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claim interpretations from the USPTO Office Action mailed 07/02/2025 remain invoked in regards to a receiver in claims 1, 17; a road surface severity estimator in claim 1; a stuck probability determiner in claims 1, 17; a start condition determiner in claims 5, 21; a post-processor in claims 1, 17; a stuck mode determiner in claims 1, 17; a notification unit in claim 15; an estimator including road surface severity estimator in claim 17; and a traveling speed estimator in claim 20.
The corresponding structure is recited in the following paragraphs of applicant’s specification: a receiver in paragraph(s) [0059]; a notification unit in paragraph(s) [0180] and [0229]; a road surface severity estimator in paragraph(s) [0057], [0241], and [0242]; a stuck probability determiner in paragraph(s) [0057], [0241], and [0242]; a start condition determiner in paragraph(s) [0057], [0241], and [0242]; a post-processor in paragraph(s) [0057], [0241], and [0242]; a stuck mode determiner in paragraph(s) [0057], [0241], and [0242]; an estimator including road surface severity estimator in paragraph(s) [0057], [0241], and [0242]; and a traveling speed estimator in paragraph(s) [0057], [0241], and [0242].
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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) 1-2, 5-11, 13, 16-19, 21-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ruybal et al. (US 2020/0398844 A1, “Ruybal”) and further in view of Nilsson et al. (US 2019/0360165 A1, “Nilsson”), and Koo et al. (US 2021/0261134 A1, “Koo”).
Regarding claim 1: Ruybal teaches: An off-road travel assistive device comprising: (see at least [0026]):
a receiver configured to receive travel data of a vehicle; (see at least [0046]; [0073]; [0097-0099]);
a road surface severity estimator configured to estimate road surface severity data based on the travel data of the vehicle; (see at least [0061]; [0062]; Fig. 3; [0097-0099]; [0100] Fig. 8);
a stuck probability determiner configured to determine a probability of a stuck state of the vehicle occurring [. . .], by using the travel data and the road surface severity data; (see at least [0047]; [0061]; [0062]; [0097-0099] process the upcoming terrain in region B; [0100] Fig. 8);
a post-processor configured to post-process a stuck probability score [. . .] ([0088] existing driver demand table may be calibrated to provide the desired wheel torque vs vehicle speed profile for each terrain; multiple maps to be calibrated and stored in the controller's memory; [0089] a new pedal map can be provided for an electric vehicle that is calibrated to provide off-roading capabilities; [0097] creep torque profile can be dynamically adjusted, in real-time, with changing terrain conditions; [0047] avoid sinking into ground and getting stuck; [0061] different terrain settings, normal, sand, snow, gravel; [0062]; [0097-0099] detect upcoming terrain and control vehicle; [0100] Fig. 8, loose gravel)
a stuck mode determiner configured to apply a stuck mode based on the stuck probability score received from the post-processor, (see at least [0061]; [0062]; [0097-0099]; [0100], [0047] off-road vehicles in situations where driver is trying to slowly cross rough terrain; if the surface is soft or slippery, vehicle needs constant vehicle speed and momentum to avoid sinking into the ground and getting stuck; [0061] creep torque based on different terrain settings, normal, sand, snow, gravel; [0062] downhill conditions; [0097-0099] vehicle sensors used to automatically detect upcoming terrain and control vehicle; [0100] Fig. 8, loose gravel at the base on the upcoming hill requires vehicle to perform creep torque blending to be controlled correctly for said terrain), [. . .], and [. . .], [. . .], and [. . .]
[autonomous control can be applied] ([0075] selection of terrain and mode automatically made; [0097] sensors automatically detect upcoming terrain and select torque profile while operating vehicle).
However, Ruybal does not explicitly teach: in advance, before the vehicle enters the stuck state; determined by the stuck probability determiner, using an exponential moving average (EMA); and wherein the stuck mode includes an autonomous control mode, and wherein the stuck mode determiner is configured apply the autonomous control mode based on a prediction, derived from the stuck probability score, that the vehicle is likely to enter the stuck state, before the vehicle enters the stuck state, generate a stuck mode signal based on applying the autonomous control mode, and transmit the stuck mode signal to a controller to cause the controller to control the vehicle to travel autonomously so as to prevent the vehicle from entering the stuck state in response to receiving the stuck mode signal. See “[. . .]” above for general location(s) in claim.
Nilsson teaches: in advance, before the vehicle enters the stuck state; ([0070] determining shape of terrain segment ahead of vehicle. [0071] predicting distance between sensor of vehicle and ground at terrain segment, before vehicle moves into terrain segment. [0072] terrain segment is situated ahead of vehicle, in driving direction of vehicle. [0074] determining that terrain segment is to be avoided due to insufficient bearing capacity when predicted distance between sensor and ground exceeds measured distance between sensor and ground) [. . .]; and
wherein the stuck mode includes an autonomous control mode, and ([0032] vehicle may be driver controlled or driverless (autonomously controlled), in this disclosure certain focus is made on driverless vehicles. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment)
wherein the stuck mode determiner is configured apply the autonomous control mode based on a prediction, derived from the stuck probability score, that the vehicle is likely to enter the stuck state, before the vehicle enters the stuck state, ([0032] vehicle may be driver controlled or driverless (autonomously controlled), in this disclosure certain focus is made on driverless vehicles. [0042] If at least one of wheels of vehicle has sunk into ground, measured height from sensor to ground is less than it should have been if wheels had been on top of ground. It may then be deduced that ground is soft. With help of axle load and wheel shape one can also calculate how soft ground is. This may then be included in local map of vehicle and also may be reported via wireless communication interface to cloud, i.e. server, so that other vehicles can avoid detected soft ground. [0044] risk of vehicles in area getting stuck is thereby eliminated, or at least reduced. [0051] When vehicle has detected terrain segment having soft soil of insufficient bearing capacity, vehicle may avoid driving into terrain segment, by making route plan avoiding detected terrain segment. [0080] storing coordinates of established geographical position in database, and associating that with information concerning insufficient bearing capacity of terrain segment to be avoided. [0081] estimated softness value may be stored and associated with coordinates of established geographical position in database. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment)
generate a stuck mode signal based on applying the autonomous control mode, and ([0032] vehicle may be driver controlled or driverless (autonomously controlled), focus is made on driverless vehicles. [0051] When vehicle has detected terrain segment having soft soil of insufficient bearing capacity, vehicle may avoid driving into terrain segment, by making route plan avoiding detected terrain segment, or by outputting an alert, in case vehicle is operated by driver. Such an alert may be alerting sound via loudspeaker, light signal, haptic signal, display, projector, head-up display. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment)
transmit the stuck mode signal to a controller to cause the controller to control the vehicle to travel autonomously so as to prevent the vehicle from entering the stuck state in response to receiving the stuck mode signal ([0032] vehicle may be driver controlled or driverless (autonomously controlled), focus is made on driverless vehicles. [0051] When vehicle has detected terrain segment having soft soil of insufficient bearing capacity, vehicle may avoid driving into terrain segment, by making route plan avoiding detected terrain segment. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment. [0044] risk of vehicles in area getting stuck is thereby eliminated, or at least reduced).
Ruybal and Nilsson are analogous art to the claimed invention since they are from the similar field of vehicle controls and avoiding stuck situations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ruybal with the aspects of Nilsson to create, with a reasonable expectation for success, an off-road travel assistive device that determines a stuck probability in advance, before the vehicle enters the stuck state, includes an autonomous control mode, applies the control based on a prediction derived from the stuck probability state, that the vehicle is likely to enter the stuck state, before the vehicle enters the stuck state, generates a stuck mode signal based on applying the autonomous control mode, and transmits the stuck mode signal to a controller to cause the controller to control the vehicle to travel autonomously so as to prevent the vehicle from entering the stuck state in response to receiving the stuck mode signal. The motivation for modification would have been to have a proactive/predictive solution to vehicle getting stuck, to avoid costly and time consuming stop and assistive efforts (Nilsson, [0008]). It would thus be desired to be able to detect soft ground areas and provide this information to vehicles in order to avoid their getting stuck in soft soil, and thus improve vehicle route planning (Nilsson, [0011]-[0012]).
However, Ruybal-Nilsson do not explicitly teach: determined by the stuck probability determiner, using an exponential moving average (EMA). See “[. . .]” above for general location(s) in claim.
Koo teaches: [post-process a stuck probability score] determined by the stuck probability determiner, using an exponential moving average (EMA) ([0067]-[0068]).
Ruybal-Nilsson and Koo are analogous art to the claimed invention since they are from the similar field of vehicle controls based on road surface determination. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ruybal-Nilsson with the components of Koo to create, with a reasonable expectation for success, an off-road travel assistive device that determines a stuck probability using an exponential moving average. The motivation for modification would have been in order for the type of the road surface on which the vehicle is traveling may be identified with a high accuracy and an optimal terrain mode may be set, thereby improving not only travel stability but also riding comfort of the vehicle (Koo, [0010]).
Regarding claim 2: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 1, wherein the travel data comprises at least one of an accelerator open value of the vehicle, a wheel slip rate of the vehicle, a steering angle of the vehicle, a currently traveling gear ratio of the vehicle, a speed of the vehicle, or a type of road surface (Ruybal: [0071]; [0073]; [0095]).
Regarding claim 5: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 1, further comprising a start condition determiner configured to determine whether the travel data satisfies a preset start condition for determining the stuck probability (Ruybal: [0070]; [0073]; [0047]).
Regarding claim 6: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 5, wherein the start condition is determined based on at least one of a steering angle of the vehicle, a current gear state of the vehicle, or a speed of the vehicle (Ruybal: [0053]; [0047]; [0071]).
Regarding claim 7: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 1, wherein the stuck probability determiner determines the stuck probability using a meta-model (Ruybal: [0047]; [0086]), wherein the meta-model scores the stuck probability using at least one parameter determined by including at least one of a speed of the vehicle, a wheel slip rate of the vehicle, an accelerator open value of the vehicle, or road surface severity (Ruybal: [0061], FIG. 9).
Regarding claim 8: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 7, wherein the meta-model comprises a plurality of parameters determined by the speed of the vehicle, the wheel slip rate of the vehicle, the accelerator open value of the vehicle, and the road surface severity (Ruybal: [0047]; [0086]), wherein the meta-model scores the stuck probability as a product of the plurality of parameters (Ruybal: [0078]; [0080] FIG. 10).
Regarding claim 9: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 7, wherein the meta-model comprises a plurality of parameters determined by the speed of the vehicle, the wheel slip rate of the vehicle, the accelerator open value of the vehicle, and the road surface severity (Ruybal: [0047]; [0086]), wherein the meta-model scores the stuck probability as a sum of the plurality of parameters (Ruybal: [0078]; [0080] FIG. 10).
Regarding claim 10: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 7, wherein, when the vehicle is controlled to travel autonomously (Ruybal: [0097]), the meta-model scores the stuck probability using the at least one parameter determined by including at least one of a speed of the vehicle, a wheel slip rate of the vehicle, an accelerator open value of the vehicle, or the road surface severity (Ruybal: [0071]; [0073]; [0095]; [0061]-[0062]; [0047]; [0086]).
Regarding claim 11: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 7, wherein the meta-model changes the at least one parameter that scores the stuck probability depending on a type of road surface on which the vehicle is traveling (Ruybal: [0073]; [0061]; [0062]; [0047]; [0086]).
Regarding claim 13: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 1, wherein the post-processor applies a second exponential constant value when the stuck probability determined by the stuck probability determiner is greater than a preset score, and applies a first exponential constant value when the stuck probability determined by the stuck probability determiner is lower than the preset score, wherein the first exponential constant value is set to be greater than the second exponential constant value (Koo: [0049]; Table 2; [0064]; [0069]; [0070]; [0071]; [0076]). The motivation for modification would have been in order for the type of the road surface on which the vehicle is traveling may be identified with a high accuracy and an optimal terrain mode may be set, thereby improving not only travel stability but also riding comfort of the vehicle (Koo, [0010]).
Regarding claim 16: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 1, wherein, in changing the stuck mode, the stuck mode determiner applies such that a reference score for changing from a lower stuck mode to an upper stuck mode is set to be higher than a reference score for changing from the upper stuck mode to the lower stuck mode (Ruybal: [0047]; [0061]; [0062]; [0097]-[0100] Fig. 8), wherein the upper stuck mode is a mode in which stuck occurrence probability is higher than the lower stuck mode (Ruybal: [0047]; [0061]; [0062]; [0097]-[0100] Fig. 8).
Regarding claim 17: Ruybal teaches: An off-road travel assistive device comprising: ([0026])
a receiver configured to receive travel data of a vehicle; ([0046]; [0073]; [0097-0099])
an estimator including a road surface severity estimator configured to estimate road surface severity data based on the travel data of the vehicle; and ([0061]; [0062]; Fig. 3; [0097-0099]; [0100] Fig. 8)
a stuck probability determiner configured to determine probability of a stuck state of the vehicle occurring [. . .] by using the travel data and the road surface severity data; ([0047]; [0061]; [0062]; [0097]-[0100] Fig. 8)
a post-processor configured to post-process a stuck probability score [. . .] ([0088]-[0089]; [0047]; [0061]-[0062]; [0097]-[0100] Fig. 8)
a stuck mode determiner configured to apply a stuck mode based on the stuck probability score received from the post- processor, ([0061]-[0062]; [0097]-[0100], [0047]; Fig. 8), [. . .],
[autonomous control can be applied] ([0075]; [0097]), [. . .], [. . .], and [. . .],
wherein the stuck probability determiner is configured to determine the stuck probability using the travel data of the vehicle and the road surface severity data, and ([0071]; [0073]; [0095])
wherein the travel data includes at least a speed of the vehicle, a wheel slip rate of the vehicle, or data regarding an accelerator open value of the vehicle ([0071]; [0073]; [0095]).
However, Ruybal does not explicitly teach: in advance, before the vehicle enters the stuck state, determined by the stuck probability determiner, using an exponential moving average (EMA); and wherein the stuck mode includes an autonomous control mode, and wherein the stuck mode determiner is configured apply the autonomous control mode based on a prediction, derived from the stuck probability score, that the vehicle is likely to enter the stuck state, before the vehicle enters the stuck state, generate a stuck mode signal based on applying the autonomous control mode, and transmit the stuck mode signal to a controller to cause the controller to control the vehicle to travel autonomously so as to prevent the vehicle from entering the stuck state in response to receiving the stuck mode signal. See “[. . .]” above for general location(s) in claim.
Nilsson teaches: in advance, before the vehicle enters the stuck state, ([0070] determining shape of terrain segment ahead of vehicle. [0071] predicting distance between sensor of vehicle and ground at terrain segment, before vehicle moves into terrain segment. [0072] terrain segment is situated ahead of vehicle, in driving direction of vehicle. [0074] determining that terrain segment is to be avoided due to insufficient bearing capacity when predicted distance between sensor and ground exceeds measured distance between sensor and ground) [. . .]; and
wherein the stuck mode includes an autonomous control mode, and ([0032] vehicle may be driver controlled or driverless (autonomously controlled), in this disclosure certain focus is made on driverless vehicles. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment)
wherein the stuck mode determiner is configured apply the autonomous control mode based on a prediction, derived from the stuck probability score, that the vehicle is likely to enter the stuck state, before the vehicle enters the stuck state, ([0032] vehicle may be driver controlled or driverless (autonomously controlled), in this disclosure certain focus is made on driverless vehicles. [0042] If at least one of wheels of vehicle has sunk into ground, measured height from sensor to ground is less than it should have been if wheels had been on top of ground. It may then be deduced that ground is soft. With help of axle load and wheel shape one can also calculate how soft ground is. This may then be included in local map of vehicle and also may be reported via wireless communication interface to cloud, i.e. server, so that other vehicles can avoid detected soft ground. [0044] risk of vehicles in area getting stuck is thereby eliminated, or at least reduced. [0051] When vehicle has detected terrain segment having soft soil of insufficient bearing capacity, vehicle may avoid driving into terrain segment, by making route plan avoiding detected terrain segment. [0080] storing coordinates of established geographical position in database, and associating that with information concerning insufficient bearing capacity of terrain segment to be avoided. [0081] estimated softness value may be stored and associated with coordinates of established geographical position in database. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment)
generate a stuck mode signal based on applying the autonomous control mode, and ([0032] vehicle may be driver controlled or driverless (autonomously controlled), focus is made on driverless vehicles. [0051] When vehicle has detected terrain segment having soft soil of insufficient bearing capacity, vehicle may avoid driving into terrain segment, by making route plan avoiding detected terrain segment, or by outputting an alert, in case vehicle is operated by driver. Such an alert may be alerting sound via loudspeaker, light signal, haptic signal, display, projector, head-up display. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment)
transmit the stuck mode signal to a controller to cause the controller to control the vehicle to travel autonomously so as to prevent the vehicle from entering the stuck state in response to receiving the stuck mode signal ([0032] vehicle may be driver controlled or driverless (autonomously controlled), focus is made on driverless vehicles. [0051] When vehicle has detected terrain segment having soft soil of insufficient bearing capacity, vehicle may avoid driving into terrain segment, by making route plan avoiding detected terrain segment. [0082] backing vehicle off terrain segment when it has been determined that terrain segment is to be avoided. [0083] prohibiting vehicle from stopping at terrain segment, that is determined to be avoided, soft soil segment. [0097] control unit may also be configured to plan vehicle route to destination of vehicle, without vehicle having to pass terrain segment. [0044] risk of vehicles in area getting stuck is thereby eliminated, or at least reduced).
Ruybal and Nilsson are analogous art to the claimed invention since they are from the similar field of vehicle controls and avoiding stuck situations. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ruybal with the aspects of Nilsson to create, with a reasonable expectation for success, an off-road travel assistive device that determines a stuck probability in advance, before the vehicle enters the stuck state, includes an autonomous control mode, applies the control based on a prediction derived from the stuck probability state, that the vehicle is likely to enter the stuck state, before the vehicle enters the stuck state, generates a stuck mode signal based on applying the autonomous control mode, and transmits the stuck mode signal to a controller to cause the controller to control the vehicle to travel autonomously so as to prevent the vehicle from entering the stuck state in response to receiving the stuck mode signal. The motivation for modification would have been to have a proactive/predictive solution to vehicle getting stuck, to avoid costly and time consuming stop and assistive efforts (Nilsson, [0008]). It would thus be desired to be able to detect soft ground areas and provide this information to vehicles in order to avoid their getting stuck in soft soil, and thus improve vehicle route planning (Nilsson, [0011]-[0012]).
However, Ruybal-Nilsson do not explicitly teach: determined by the stuck probability determiner, using an exponential moving average (EMA). See “[. . .]” above for general location(s) in claim.
Koo teaches: determined by the stuck probability determiner, using an exponential moving average (EMA) ([0067]-[0068]).
Ruybal-Nilsson and Koo are analogous art to the claimed invention since they are from the similar field of vehicle controls based on road surface determination. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ruybal-Nilsson with the components of Koo to create, with a reasonable expectation for success, an off-road travel assistive device that determines a stuck probability using an exponential moving average. The motivation for modification would have been in order for the type of the road surface on which the vehicle is traveling may be identified with a high accuracy and an optimal terrain mode may be set, thereby improving not only travel stability but also riding comfort of the vehicle (Koo, [0010]).
Regarding claim 18: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 17, wherein the travel data further comprises at least one of a steering angle of the vehicle, a current traveling gear ratio of the vehicle, or a type of road surface (Ruybal: [0053]; [0073]; [0061]; [0062]; [0097-0099]; [0100] Fig. 8).
Regarding claim 19: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 17, wherein the road surface severity estimator estimates the road surface severity as a score in a preset range based on stuck occurrence probability depending on a road surface condition (Ruybal: [0047]; [0071]; [0073]; [0061] FIG. 9, Fig. 8).
Regarding claim 21: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 17, further comprising a start condition determiner configured to determine the stuck probability using the stuck probability determiner only when the travel data satisfies a preset start condition (Ruybal: [0070]; [0073]; [0047]), wherein the start condition determiner does not determine the stuck probability when the vehicle travels with a sharp turn, travels in reverse, or stops (Ruybal: [0042]; [0085]; [0086]).
Regarding claim 22: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 17, wherein the stuck probability determiner scores the stuck probability using at least one parameter determined by including at least one of the speed of the vehicle, the wheel slip rate of the vehicle, the accelerator open value of the vehicle, or the road surface severity (Ruybal: [0071]; [0073]; [0095]).
Claim(s) 3 and 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ruybal et al. (US 2020/0398844 A1), Nilsson et al. (US 2019/0360165 A1) and Koo et al. (US 2021/0261134 A1), and further in view of Zhou et al. (US 2023/0055334 A1, “Zhou”).
Regarding claim 3: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 1, […] estimates road surface […] using a deep-learned road surface […] model (Koo: [0039]-[0040]). The motivation for modification would have been in order for the type of the road surface on which the vehicle is traveling may be identified with a high accuracy and an optimal terrain mode may be set, thereby improving not only travel stability but also riding comfort of the vehicle (Koo, [0010]).
However, Ruybal-Nilsson-Koo do not explicitly teach: wherein the road surface severity estimator estimates road surface severity using a deep-learned road surface severity estimation model, wherein the road surface severity estimation model estimates a road surface having stuck probability that is higher than a preset standard, as a deep road surface, and estimates a road surface having stuck probability that is lower than the preset standard, as a shallow road surface.
Zhou teaches: wherein the road surface severity estimator estimates road surface severity using a deep-learned road surface severity estimation model ([0089], Fig. 10),
wherein the road surface severity estimation model estimates a road surface having stuck probability that is higher than a preset standard, as a deep road surface, and estimates a road surface having stuck probability that is lower than the preset standard, as a shallow road surface ([0078-0080]).
Ruybal-Nilsson-Koo and Zhou are analogous art to the claimed invention since they are from the similar field of vehicle controls based on road surface determination. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ruybal-Nilsson-Koo with the components of Zhou to create, with a reasonable expectation for success, an off-road travel assistive device that uses a deep-learned road surface severity estimation model that estimates a road surface having stuck probability that is higher than a preset standard, as a deep road surface, and estimates a road surface having stuck probability that is lower than the preset standard, as a shallow road surface. The motivation for modification would have been in order for the type of the road surface on which the vehicle is traveling may be identified with a high accuracy and an optimal terrain mode may be set, thereby improving not only travel stability but also riding comfort of the vehicle and overall safety.
Regarding claim 4: Ruybal-Nilsson-Koo-Zhou further teach: The off-road travel assistive device of claim 3, wherein the road surface severity estimation model estimates the road surface severity as a score having a predetermined range (Zhou: [0078-0080]). The motivation for modification would have been in order for the type of the road surface on which the vehicle is traveling may be identified with a high accuracy and an optimal terrain mode may be set, thereby improving not only travel stability but also riding comfort of the vehicle and overall safety.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ruybal et al. (US 2020/0398844 A1), Nilsson et al. (US 2019/0360165 A1) and Koo et al. (US 2021/0261134 A1), and further in view of Foster et al. (US 2017/0101103 A1, “Foster”).
Regarding claim 15: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 1. However, Ruybal-Nilsson-Koo does not explicitly teach: further comprising a notification unit configured to inform a driver of a traveling status using at least one of a display or a sound, wherein the stuck mode determiner informs the driver of the stuck probability through the notification unit when the stuck probability score is greater than a preset score.
Foster teaches: further comprising a notification unit configured to inform a driver of a traveling status using at least one of a display or a sound, wherein the stuck mode determiner informs the driver of the stuck probability through the notification unit when the stuck probability score is greater than a preset score ([0039]; [0064]; [0083]).
Ruybal-Nilsson-Koo and Foster are analogous art to the claimed invention since they are from the similar field of vehicle controls in off-road surface conditions. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ruybal-Nilsson-Koo with the components of Foster to create, with a reasonable expectation for success, an off-road travel assistive device that notifies the operator when a stuck mode probability is greater than a preset score. The motivation for modification would have been to alert the operator to upcoming or impending areas of becoming stuck while driving, thus enabling the operator to adapt to the situation, thereby reducing the possibility of the off-road vehicle becoming stuck in the soil (Foster, [0064]).
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ruybal et al. (US 2020/0398844 A1), Nilsson et al. (US 2019/0360165 A1) and Koo et al. (US 2021/0261134 A1), and further in view of Coerman et al. (US 2024/0369592 A1, “Coerman”).
Regarding claim 20: Ruybal-Nilsson-Koo further teach: The off-road travel assistive device of claim 17. However, Ruybal-Nilsson-Koo does not explicitly teach: wherein the estimator further comprises a traveling speed estimator configured to estimate an off-road traveling speed using a deep-learned wheel slip rate estimation model, wherein the traveling speed estimator estimates a wheel slip rate using the travel data and the wheel slip rate estimation model, and estimates the off-road traveling speed using the estimated wheel slip rate, and wherein the speed of the vehicle includes the off-road traveling speed.
Coerman teaches: wherein the estimator further comprises a traveling speed estimator configured to estimate an off-road traveling speed using a deep-learned wheel slip rate estimation model ([0023]; [0073]; [0067]),
wherein the traveling speed estimator estimates a wheel slip rate using the travel data and the wheel slip rate estimation model, and estimates the off-road traveling speed using the estimated wheel slip rate ([0073]; [0067]), and
wherein the speed of the vehicle includes the off-road traveling speed ([0073]; [0067]).
Ruybal-Nilsson-Koo and Coerman are analogous art to the claimed invention since they are from the similar field of vehicle controls in off-road surface conditions. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ruybal-Nilsson-Koo with the components of Coerman to create, with a reasonable expectation for success, an off-road travel assistive device that uses deep learning to account for wheel slip when determining vehicle traveling speed. The motivation for modification would have been to determine a vehicle’s driving state with high accuracy and an optimal terrain mode may be set, thereby improving not only travel stability but also riding comfort of the vehicle.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-11, 13, and 15-22 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MADISON B EMMETT whose telephone number is (303)297-4231. The examiner can normally be reached Monday - Friday 9:00 - 5:00 ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tommy Worden can be reached at (571)272-4876. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MADISON B EMMETT/Examiner, Art Unit 3658
Prosecution Insights