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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 04/25/2025 and 03/04/2025 were filed. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Rejections - 35 USC § 102
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.
Claims 11-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipatory by Goehl (DE102020109662A1, translation provided).
Re Claim 11, Goehl discloses a computer-implemented method for behavior planning of a vehicle, comprising the following steps: (Paragraph 0010-0011, “It is an object of the present invention to provide a method for trajectory planning for a vehicle which enables the consideration of uncertainties in an environment model. This task is solved by a computer-implemented method, a computing device, a computer program and a computer-readable (storage) medium according to the independent patent claims.”)
ascertaining at least one planned driving behavior of the vehicle depending on an environmental perception of a vehicle environment of the vehicle; (Paragraph 0035, “In one implementation variant, a first environment model is used in a first trajectory planning mode of the at least two trajectory planning modes,”)
ascertaining at least one spatially resolved degree of importance of a functional impairment of the environmental perception and a spatially resolved perception capability of the environmental perception, in each case in relation to the planned driving behavior; (Fig. 1A, Paragraph 0067, “Within the framework of the respective environmental model, each of the occupied areas B1, B2, B3, C1, C2, C3 is assigned an uncertainty.”; Paragraph 0063, “This uncertainty can relate, for example, to an inherent systematic and/or statistical limitation of sensor accuracy. The uncertainty can be... B. also depend on current weather and/or visibility conditions, whereby z. B. Fog can increase the uncertainty of optically recorded sensor data. Furthermore, the uncertainty can be influenced by whether all environmental sensors or only some of the potentially available environmental sensors are currently functional. This is how it can be done. For example, a (possibly temporary) failure of one of several environmental sensors could lead to the fused sensor data being subject to a higher overall uncertainty”; Examiner is treating the uncertainties of the occupied areas as the degree of importance of a functional impairment of the environmental perception.)
ascertaining a risk of the functional impairment of the environmental perception for the planned driving behavior at least depending on a degree of importance and the perception capability; (Paragraph 0067, “The meaning of the occupied areas B1, B2, B3, C1, C2, C3 is as follows: B. in that an object 3, such as a vehicle driving ahead, is located with a comparatively high probability in the first occupied area B1 (corresponding to the occupied area C1), with a lower probability in the second occupied area B2 (corresponding to the part of the occupied area C2 extending beyond the occupied area C1), and with an even lower probability in the third occupied area B3 (corresponding to the part of the occupied area C3 extending beyond the occupied area C2), taking into account the uncertainties of the environmental sensor data.”; Examiner is treating the probability of object 3 due to the uncertainties of the environmental sensor data as the risk of the functional impairment)
ascertaining a risk of the planned driving behavior for the vehicle and/or the vehicle environment depending on the risk of the functional impairment; (Paragraph 0074, “The partial cost functionals are each assigned a weighting factor within the first cost functional J, which forms the basis for trajectory planning in step 22. The weight factors can be... B. with a probability of existence of the preceding vehicle 3 in the respective occupied area B1, B2, B3 or B3. C1, C2, C3 are related. With reference to Fig. 2A-B, for example, it can be provided that the first weighting factor is proportional to the first interval limit s1, the second weighting factor is proportional to the second interval limit s2, and the third weighting factor is proportional to the third interval limit s3, i.e.”; Paragraph 0075, “In this way, the trajectory planning allows for the passage through the first occupied area B1 or... C1, in which an object 3 is highly likely to be present, is severely "penalized" by a correspondingly large weighting of the assigned partial cost function, so that the trajectory planning uses the first occupied area B1 or B1. C1 will tend to be avoided as a result. Areas of the vehicle's surroundings where there is only a low probability of an object 3 being located, such as... However, the third occupied area, B3, will not be disregarded. As a result of trajectory planning, they are also tended to be avoided, but they are included in the first cost functional with less weight than the first occupied area B1, C1.”; Examiner is treating the cost function generated by the probability of the uncertainties as the risk of the planned driving behavior)
And calculating a driving behavior to be applied depending on the planned driving behavior and the risk of the planned driving behavior. (Paragraph 0077, “The computing device of vehicle 1 can minimize the first cost functional J according to equation (3) taking into account certain constraints, such as... B. Initial conditions, final conditions and inequality restrictions, using common algorithmic methods, which z. B. as known from mathematical programming. This involves determining the temporal progression of the relevant control variables (and consequently the resulting temporal progression of the vehicle state variables) which defines the first cost functional up to a specific time horizon (i.e., temporally integrated up to a final time, which is defined as follows). U. itself is variable and can be the subject of optimization) minimized. The solution results, for example, in a trajectory T that corresponds to a lane change, as shown on the right side in Fig. 1. By changing lanes, the planned trajectory T avoids, if possible, a collision with the vehicle 3 ahead and in particular also avoids (if this is possible or more cost-effective in the solution space) driving into the third occupied area B3, in which the vehicle 3 ahead is only likely to be located according to the environmental sensor data.”; Paragraph 0081, “In a further step 24, one of the several trajectories is then selected based on the calculated costs. The trajectory T is preferably selected for which the lowest costs result when evaluating the relevant cost functional (i.e., the first cost functional or the second cost functional).”)
Re Claim 12, Goehl discloses wherein the degree of importance and/or the perception capability is ascertained depending on a driving situation and/or vehicle environment. (Paragraph 0067, “Within the framework of the respective environmental model, each of the occupied areas B1, B2, B3, C1, C2, C3 is assigned an uncertainty.”; Examiner is treating the occupied areas in the environmental model as the perception capability ascertained on a vehicle environment.)
Re Claim 13, Goehl discloses wherein the degree of importance and/or the perception capability is ascertained so as to be spatially resolved into spatial zones of the vehicle environment. (Fig. 1A, Paragraph 0067, “Within the framework of the respective environmental model, each of the occupied areas B1, B2, B3, C1, C2, C3 is assigned an uncertainty.”; Examiner is treating occupied areas B1-3 and C1-3 as the spatial zones of the vehicle environment.)
Re Claim 14, Goehl discloses wherein the degree of importance and/or the perception capability is ascertained depending on environmental conditions of the vehicle. (Fig. 1A, Paragraph 0067, “Within the framework of the respective environmental model, each of the occupied areas B1, B2, B3, C1, C2, C3 is assigned an uncertainty.”; Paragraph 0063, “This uncertainty can relate, for example, to an inherent systematic and/or statistical limitation of sensor accuracy. The uncertainty can be... B. also depend on current weather and/or visibility conditions, whereby z. B. Fog can increase the uncertainty of optically recorded sensor data. Furthermore, the uncertainty can be influenced by whether all environmental sensors or only some of the potentially available environmental sensors are currently functional. This is how it can be done. For example, a (possibly temporary) failure of one of several environmental sensors could lead to the fused sensor data being subject to a higher overall uncertainty”)
Re Claim 15, Goehl discloses wherein the risk of the driving behavior associated with at least one risk event is further ascertained depending on a degree of importance of the risk event and/or a probability of occurrence of the risk event and/or a controllability of the risk event. (Paragraph 0067, “The meaning of the occupied areas B1, B2, B3, C1, C2, C3 is as follows: B. in that an object 3, such as a vehicle driving ahead, is located with a comparatively high probability in the first occupied area B1 (corresponding to the occupied area C1), with a lower probability in the second occupied area B2 (corresponding to the part of the occupied area C2 extending beyond the occupied area C1), and with an even lower probability in the third occupied area B3 (corresponding to the part of the occupied area C3 extending beyond the occupied area C2), taking into account the uncertainties of the environmental sensor data.”; Examiner is treating the probability of object 3 based on the uncertainties of the environmental sensor data as the probability of occurrence of the risk event.)
Re Claim 16, Goehl discloses wherein the risk of the driving behavior is indicated by at least one risk parameter. (Paragraph 0074, “The partial cost functionals are each assigned a weighting factor within the first cost functional J, which forms the basis for trajectory planning in step 22. The weight factors can be... B. with a probability of existence of the preceding vehicle 3 in the respective occupied area B1, B2, B3 or B3. C1, C2, C3 are related. With reference to Fig. 2A-B, for example, it can be provided that the first weighting factor is proportional to the first interval limit s1, the second weighting factor is proportional to the second interval limit s2, and the third weighting factor is proportional to the third interval limit s3, i.e.”; Examiner is treating the interval limit as the risk parameter.)
Re Claim 17, Goehl discloses wherein the driving behavior to be applied is changed so as to deviate from the planned driving behavior when the risk parameter exceeds or falls below a limit value. (Fig. 2A-2B, Paragraph 0075, “In this way, the trajectory planning allows for the passage through the first occupied area B1 or... C1, in which an object 3 is highly likely to be present, is severely "penalized" by a correspondingly large weighting of the assigned partial cost function, so that the trajectory planning uses the first occupied area B1 or B1. C1 will tend to be avoided as a result. Areas of the vehicle's surroundings where there is only a low probability of an object 3 being located, such as... However, the third occupied area, B3, will not be disregarded. As a result of trajectory planning, they are also tended to be avoided, but they are included in the first cost functional with less weight than the first occupied area B1, C1.”; Examiner is treating the avoidance of C1 due to its weight exceeding the interval limit as the deviation from the planned driving behavior.)
Re Claim 18, Goehl discloses wherein at least one planned second driving behavior is ascertained as the first driving behavior, in relation to which planned second driving behavior a risk of functional impairment and a risk of the planned second driving behavior are ascertained analogously to the first driving behavior, (Paragraph 0080, “Regarding the possible form of such a second cost functional, what was said above with reference to the first cost functional applies analogously. In some embodiments, the second cost functional can also be written, for example, in a form according to the preceding equation (3). In particular, the second cost functional can also contain several sub-cost functionals, each belonging to one of the occupied areas B1, B2, B3 or B3 respectively. are assigned to C1, C2, C3 and may contain the weight factors defined above. The further partial cost functionals J<sub>1</sub>, J<sub>2</sub> can be compared to the first cost functional J according to equation (3). B. be replaced by other partial cost functions or additional partial cost functions may be added that correspond to additional optimization criteria.”) and the calculation of the driving behavior to be applied includes a selection from the first and second driving behaviors depending on the risk of the planned driving behavior of the first and second driving behaviors. (Paragraph 0081, “In a further step 24, one of the several trajectories is then selected based on the calculated costs. The trajectory T is preferably selected for which the lowest costs result when evaluating the relevant cost functional (i.e., the first cost functional or the second cost functional).”)
Re Claim 19, Goehl discloses a processing device for a vehicle, the processing device configured for behavior planning of a vehicle, the processing device configured to: (Paragraph 0010-0011, “It is an object of the present invention to provide a method for trajectory planning for a vehicle which enables the consideration of uncertainties in an environment model. This task is solved by a computer-implemented method, a computing device, a computer program and a computer-readable (storage) medium according to the independent patent claims.”; Paragraph 0054, “According to a second aspect of the invention, a computing device is proposed, wherein the computing device is designed to carry out a method according to the first aspect of the invention. The computing unit can be part of a vehicle's control system, which may contain one or more processors (such as...). B. CPUs and/or GPUs) on which the necessary calculations for carrying out the procedure are performed.”)
ascertain at least one planned driving behavior of the vehicle depending on an environmental perception of a vehicle environment of the vehicle; (Paragraph 0035, “In one implementation variant, a first environment model is used in a first trajectory planning mode of the at least two trajectory planning modes,”)
ascertain at least one spatially resolved degree of importance of a functional impairment of the environmental perception and a spatially resolved perception capability of the environmental perception, in each case in relation to the planned driving behavior; (Fig. 1A, Paragraph 0067, “Within the framework of the respective environmental model, each of the occupied areas B1, B2, B3, C1, C2, C3 is assigned an uncertainty.”; Paragraph 0063, “This uncertainty can relate, for example, to an inherent systematic and/or statistical limitation of sensor accuracy. The uncertainty can be... B. also depend on current weather and/or visibility conditions, whereby z. B. Fog can increase the uncertainty of optically recorded sensor data. Furthermore, the uncertainty can be influenced by whether all environmental sensors or only some of the potentially available environmental sensors are currently functional. This is how it can be done. For example, a (possibly temporary) failure of one of several environmental sensors could lead to the fused sensor data being subject to a higher overall uncertainty”; Examiner is treating the uncertainties of the occupied areas as the degree of importance of a functional impairment of the environmental perception.)
ascertain a risk of the functional impairment of the environmental perception for the planned driving behavior at least depending on a degree of importance and the perception capability; (Paragraph 0067, “The meaning of the occupied areas B1, B2, B3, C1, C2, C3 is as follows: B. in that an object 3, such as a vehicle driving ahead, is located with a comparatively high probability in the first occupied area B1 (corresponding to the occupied area C1), with a lower probability in the second occupied area B2 (corresponding to the part of the occupied area C2 extending beyond the occupied area C1), and with an even lower probability in the third occupied area B3 (corresponding to the part of the occupied area C3 extending beyond the occupied area C2), taking into account the uncertainties of the environmental sensor data.”; Examiner is treating the probability of object 3 due to the uncertainties of the environmental sensor data as the risk of the functional impairment)
ascertain a risk of the planned driving behavior for the vehicle and/or the vehicle environment depending on the risk of the functional impairment; (Paragraph 0074, “The partial cost functionals are each assigned a weighting factor within the first cost functional J, which forms the basis for trajectory planning in step 22. The weight factors can be... B. with a probability of existence of the preceding vehicle 3 in the respective occupied area B1, B2, B3 or B3. C1, C2, C3 are related. With reference to Fig. 2A-B, for example, it can be provided that the first weighting factor is proportional to the first interval limit s1, the second weighting factor is proportional to the second interval limit s2, and the third weighting factor is proportional to the third interval limit s3, i.e.”; Paragraph 0075, “In this way, the trajectory planning allows for the passage through the first occupied area B1 or... C1, in which an object 3 is highly likely to be present, is severely "penalized" by a correspondingly large weighting of the assigned partial cost function, so that the trajectory planning uses the first occupied area B1 or B1. C1 will tend to be avoided as a result. Areas of the vehicle's surroundings where there is only a low probability of an object 3 being located, such as... However, the third occupied area, B3, will not be disregarded. As a result of trajectory planning, they are also tended to be avoided, but they are included in the first cost functional with less weight than the first occupied area B1, C1.”; Examiner is treating the cost function generated by the probability of the uncertainties as the risk of the planned driving behavior)
And calculate a driving behavior to be applied depending on the planned driving behavior and the risk of the planned driving behavior. (Paragraph 0077, “The computing device of vehicle 1 can minimize the first cost functional J according to equation (3) taking into account certain constraints, such as... B. Initial conditions, final conditions and inequality restrictions, using common algorithmic methods, which z. B. as known from mathematical programming. This involves determining the temporal progression of the relevant control variables (and consequently the resulting temporal progression of the vehicle state variables) which defines the first cost functional up to a specific time horizon (i.e., temporally integrated up to a final time, which is defined as follows). U. itself is variable and can be the subject of optimization) minimized. The solution results, for example, in a trajectory T that corresponds to a lane change, as shown on the right side in Fig. 1. By changing lanes, the planned trajectory T avoids, if possible, a collision with the vehicle 3 ahead and in particular also avoids (if this is possible or more cost-effective in the solution space) driving into the third occupied area B3, in which the vehicle 3 ahead is only likely to be located according to the environmental sensor data.”; Paragraph 0081, “In a further step 24, one of the several trajectories is then selected based on the calculated costs. The trajectory T is preferably selected for which the lowest costs result when evaluating the relevant cost functional (i.e., the first cost functional or the second cost functional).”)
Re Claim 20, Goehl discloses a vehicle control device for a vehicle, the vehicle control device being configured to adjust a driving behavior of the vehicle to be applied depending on a driving behavior to be applied calculated by performing the following steps: (Paragraph 0010-0011, “It is an object of the present invention to provide a method for trajectory planning for a vehicle which enables the consideration of uncertainties in an environment model. This task is solved by a computer-implemented method, a computing device, a computer program and a computer-readable (storage) medium according to the independent patent claims.”; Paragraph 0054, “According to a second aspect of the invention, a computing device is proposed, wherein the computing device is designed to carry out a method according to the first aspect of the invention. The computing unit can be part of a vehicle's control system, which may contain one or more processors (such as...). B. CPUs and/or GPUs) on which the necessary calculations for carrying out the procedure are performed.”)
ascertaining at least one planned driving behavior of the vehicle depending on an environmental perception of a vehicle environment of the vehicle; (Paragraph 0035, “In one implementation variant, a first environment model is used in a first trajectory planning mode of the at least two trajectory planning modes,”)
ascertaining at least one spatially resolved degree of importance of a functional impairment of the environmental perception and a spatially resolved perception capability of the environmental perception, in each case in relation to the planned driving behavior; (Fig. 1A, Paragraph 0067, “Within the framework of the respective environmental model, each of the occupied areas B1, B2, B3, C1, C2, C3 is assigned an uncertainty.”; Paragraph 0063, “This uncertainty can relate, for example, to an inherent systematic and/or statistical limitation of sensor accuracy. The uncertainty can be... B. also depend on current weather and/or visibility conditions, whereby z. B. Fog can increase the uncertainty of optically recorded sensor data. Furthermore, the uncertainty can be influenced by whether all environmental sensors or only some of the potentially available environmental sensors are currently functional. This is how it can be done. For example, a (possibly temporary) failure of one of several environmental sensors could lead to the fused sensor data being subject to a higher overall uncertainty”; Examiner is treating the uncertainties of the occupied areas as the degree of importance of a functional impairment of the environmental perception.)
ascertaining a risk of the functional impairment of the environmental perception for the planned driving behavior at least depending on a degree of importance and the perception capability; (Paragraph 0067, “The meaning of the occupied areas B1, B2, B3, C1, C2, C3 is as follows: B. in that an object 3, such as a vehicle driving ahead, is located with a comparatively high probability in the first occupied area B1 (corresponding to the occupied area C1), with a lower probability in the second occupied area B2 (corresponding to the part of the occupied area C2 extending beyond the occupied area C1), and with an even lower probability in the third occupied area B3 (corresponding to the part of the occupied area C3 extending beyond the occupied area C2), taking into account the uncertainties of the environmental sensor data.”; Examiner is treating the probability of object 3 due to the uncertainties of the environmental sensor data as the risk of the functional impairment)
ascertaining a risk of the planned driving behavior for the vehicle and/or the vehicle environment depending on the risk of the functional impairment; (Paragraph 0074, “The partial cost functionals are each assigned a weighting factor within the first cost functional J, which forms the basis for trajectory planning in step 22. The weight factors can be... B. with a probability of existence of the preceding vehicle 3 in the respective occupied area B1, B2, B3 or B3. C1, C2, C3 are related. With reference to Fig. 2A-B, for example, it can be provided that the first weighting factor is proportional to the first interval limit s1, the second weighting factor is proportional to the second interval limit s2, and the third weighting factor is proportional to the third interval limit s3, i.e.”; Paragraph 0075, “In this way, the trajectory planning allows for the passage through the first occupied area B1 or... C1, in which an object 3 is highly likely to be present, is severely "penalized" by a correspondingly large weighting of the assigned partial cost function, so that the trajectory planning uses the first occupied area B1 or B1. C1 will tend to be avoided as a result. Areas of the vehicle's surroundings where there is only a low probability of an object 3 being located, such as... However, the third occupied area, B3, will not be disregarded. As a result of trajectory planning, they are also tended to be avoided, but they are included in the first cost functional with less weight than the first occupied area B1, C1.”; Examiner is treating the cost function generated by the probability of the uncertainties as the risk of the planned driving behavior)
And calculating a driving behavior to be applied depending on the planned driving behavior and the risk of the planned driving behavior. (Paragraph 0077, “The computing device of vehicle 1 can minimize the first cost functional J according to equation (3) taking into account certain constraints, such as... B. Initial conditions, final conditions and inequality restrictions, using common algorithmic methods, which z. B. as known from mathematical programming. This involves determining the temporal progression of the relevant control variables (and consequently the resulting temporal progression of the vehicle state variables) which defines the first cost functional up to a specific time horizon (i.e., temporally integrated up to a final time, which is defined as follows). U. itself is variable and can be the subject of optimization) minimized. The solution results, for example, in a trajectory T that corresponds to a lane change, as shown on the right side in Fig. 1. By changing lanes, the planned trajectory T avoids, if possible, a collision with the vehicle 3 ahead and in particular also avoids (if this is possible or more cost-effective in the solution space) driving into the third occupied area B3, in which the vehicle 3 ahead is only likely to be located according to the environmental sensor data.”; Paragraph 0081, “In a further step 24, one of the several trajectories is then selected based on the calculated costs. The trajectory T is preferably selected for which the lowest costs result when evaluating the relevant cost functional (i.e., the first cost functional or the second cost functional).”)
Conclusion
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/A.K.P./Examiner, Art Unit 3657 /KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656
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