DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This is the First Office Action on the merits.
Claims 1-10 are currently pending and addressed below.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. DE 102024203533.5, filed on 04/17/2024.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 05/28/2025 has been considered. An initialed copy of the IDS is enclosed herewith.
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.
Claims 3-4 and 7-8 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.
As to claim 3, the claim recites “. . . includes a plurality of values of the driving behavior of vehicles . . . wherein the values of the driving behavior of the vehicle include . . .”. There is insufficient antecedent basis for this limitation in the claim. Further, the claim recites “wherein the value of the swarm behavior of the second region includes a plurality of values of the driving behavior of the vehicles”. It is unclear to the Examiner how “the value” which appears to be a single value includes plurality of values (e.g. the values of the driving behavior of the vehicles).
As to claim 4, the claim recites “wherein the calculations are performed based on the swarm behavior of a behavior map, wherein target values for the calculations are defined from the swarm behavior, wherein the calculations are performed in iterative steps until the parameters provide a solution for achieving the target values, or until the parameters in a final iterative step provide the same number of achieved target values in a previously performed penultimate iterative step.” In view of the applicant’s specification, it is unclear to the Examiner what “calculations” are being performed and how are they being performed in “iterative steps”.
As to claim 7, the claim recites “includes a wealth of information about the driving behavior of vehicles”. The term “wealth” is a relative term which renders the claim indefinite. The term “wealth” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
As to claim 8, the claim is rejected for the same reasons stated in the rejection of claim 4.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 4, and 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Rupp et al. (US 20110301802 A1) in view of Max et al. (US 20210034072 A1).
Regarding claim 1, and similarly with respect to claims 9 and 10, Rupp et al. discloses A
method for controlling a driving function of a movable device, comprising the following steps: reading in parameters for controlling the driving function; (Abstract “A target (not-to-exceed) speed for a vehicle over a road segment ahead of the vehicle is established based on a desired relationship with a speed profile of the segment. The speed profile is generated by analyzing a statistical distribution of historical speed data over the segment collected by probe vehicles… applying the speed differential to the speed profile of the approaching segment”, and see at least [0050] and figures 1- 3)
using a map, ([0022] “utilizing a GPS navigation system and map database, as is well known. Progressing to block 120, the vehicle location is compared with a map data base to identify an approaching road segment, that is, a road segment that lies ahead of the vehicle as it progresses along its current and/or planned route of travel.”) wherein the map has at least a first region and a second region, wherein at least one value of a swarm behavior is entered in the second region; (Figure 1, [0017] “a length of roadway 10 divided into six segments labeled A through F. Road segments may be delineated/identified based upon a standard or uniform distance (every 10 meters for example). Or, the segments may be based upon changes in one or more roadway characteristics such as radius of curvature, incline (uphill/downhill), bank angle, camber, road surface quality (rough/smooth, asphalt/concrete), and/or posted speed limit.”, and [0018] “At least one historical speed profile is generated for each road segment A-F, the speed profile based upon data collected from probe vehicles that have previously driven over the segment.”)
locating the device in the map; (Figure 3, and [0022] “a method of monitoring the speed of
a vehicle and identifying that the vehicle may be likely to exceed a target speed on a road segment if no corrective action is taken. The method begins at block 100 and progresses to block 110 where the vehicle location is determined. This may be accomplished, for example, utilizing a GPS navigation system and map database, as is well known. Progressing to block 120, the vehicle location is compared with a map data base to identify an approaching road segment, that is, a road segment that lies ahead of the vehicle as it progresses along its current and/or planned route of travel.”)
using the parameters to ascertain the driving function, when the movable device is in the
first region of the map; (Figure 3, [0034] “the speed differential is applied to the speed profile of the approaching segment. This method has the advantage of considering the historic driving style of the vehicle/driver, and it may be applied even if the approaching segment is brand new to the vehicle/driver by selecting a baseline road segment having characteristics similar to that of the approaching segment.”, [0035] “a target speed for the approaching road segment is identified by applying the desired relationship (determined at block 140) to the speed profile of the approaching road segment. It should be noted that one or more of the factors and/or considerations discussed in relation to blocks 210-240 of FIG. 4 may be considered in combination with the methodology of FIG. 5 in order to arrive at a target speed. That is, even if the FIG. 5 method shows that the past speed of the vehicle/driver over a baseline road segment is high relative to a speed profile, the target speed may be adjusted downward if driver condition, vehicle condition, and/or external driving conditions indicate such a speed reduction.”, and [0036] “The target speed determined in this method does not take into account the geometry of the approaching road segment, but rather relies on the speed profile generated from historical data gathered from probe vehicles. This allows the use of a digital map that may not be accurate enough to rely upon to calculate road curvature and bank angle and hence lateral acceleration.”, and see at least [0050] and figure 5)
using the at least one value of the swarm behavior to ascertain the driving function, when
the movable device is in the second region of the map; (Figure 3, [0034] “the speed differential is applied to the speed profile of the approaching segment. This method has the advantage of considering the historic driving style of the vehicle/driver, and it may be applied even if the approaching segment is brand new to the vehicle/driver by selecting a baseline road segment having characteristics similar to that of the approaching segment.”, [0035] “a target speed for the approaching road segment is identified by applying the desired relationship (determined at block 140) to the speed profile of the approaching road segment. It should be noted that one or more of the factors and/or considerations discussed in relation to blocks 210-240 of FIG. 4 may be considered in combination with the methodology of FIG. 5 in order to arrive at a target speed. That is, even if the FIG. 5 method shows that the past speed of the vehicle/driver over a baseline road segment is high relative to a speed profile, the target speed may be adjusted downward if driver condition, vehicle condition, and/or external driving conditions indicate such a speed reduction.”, and at least [0050]) controlling the device with the ascertained driving function. (Figure 3, and [0050] “Driver alert system 40 may be activated to provide visual, audible, haptic and/or any other appropriate alert to the driver so that he/she may take action to reduce the vehicle speed over the approaching segment. Braking control module 42 and/or power train control module 44 may be activated to provide automatic interventions to reduce vehicle speed.”, and see at least figure 5)
However, Rupp et al. may be alleged to not explicitly disclose wherein at least one value of
a swarm behavior is entered in the second region and using the at least one value of the swarm behavior to ascertain the driving function, when the movable device is in the second region of the map;
Max et al. teaches wherein at least one value of a swarm behavior is entered in the
second region and using the at least one value of the swarm behavior to ascertain the driving function, when the movable device is in the second region of the map; ([0018] “numerous vehicles traveling in a given lane transmit their respective trajectories to a back-end computer, which then determines and stores a swarm trajectory from the trajectories it has received for a given lane.”, [0025] “The ego-vehicle may determine which boundary conditions, or combination of boundary conditions, are used for determining the swarm trajectory in the data base. This can take place, e.g., in that only the selected boundary conditions are sent to back-end computer, such that it can also execute a data base search using only these boundary conditions. It is also conceivable to send numerous swarm trajectories to the ego-vehicle, corresponding to the number of boundary conditions and/or the desired combinations of boundary conditions.”, [0026] “The current driving trajectory for the ego-vehicle may be corrected of affected by the swarm trajectories that have been sent to the ego-vehicle, e.g., in that the difference between the current driving trajectory and the swarm trajectory is determined, and this difference is used to correct the current trajectory of the ego-vehicle.”, and [0027] “The method can be extended accordingly for further route segments, and the respective route segments form a parameter for processing these further sections”)
It would have been obvious to one of ordinary skill in the art before the effective filling date
of the claimed invention with reasonable expectations of success to modify the invention of Rupp et al. to incorporate swarm trajectories of a plurality of other vehicles as taught by Max et al. for the purpose of improving navigation of the vehicle based on the plurality of other vehicles.
Regarding claim 2, Rupp et al. in view of Max et al. discloses The method according to claim
1,
Rupp et al. discloses wherein the movable device is a vehicle or a robot. (Figure 1, and
[0050] “A driver alert system 40, a braking control module 42, and a power train control module 44 are in electronic communication with computational module 20. One of more of these systems may be activated if computational module 20 determines that the vehicle is likely to exceed the target speed. Driver alert system 40 may be activated to provide visual, audible, haptic and/or any other appropriate alert to the driver so that he/she may take action to reduce the vehicle speed over the approaching segment. Braking control module 42 and/or power train control module 44 may be activated to provide automatic interventions to reduce vehicle speed.”)
Regarding claim 4, as best understood by the Examiner, Rupp et al. in view of Max et al.
discloses The method according to claim 1,
Rupp et al. discloses wherein the parameters (6) for controlling the driving function come
from calculations, wherein the calculations are performed based on the swarm behavior of a behavior map, wherein target values for the calculations are defined from the swarm behavior, wherein the calculations are performed in iterative steps until the parameters provide a solution for achieving the target values, or until the parameters in a final iterative step provide the same number of achieved target values in a previously performed penultimate iterative step. (Figure 3, [0008] “the speed of an automotive vehicle is monitored and a vehicle system, such as a warning device, is activated if the vehicle speed is expected to exceed a target speed over an approaching road segment lying ahead of the vehicle. A speed profile of the approaching segment is accessed, the speed profile being generated by analyzing a statistical distribution of historical speed data collected from probe vehicles that have previously traveled over the approaching segment. The target speed is established based on a desired relationship with the speed profile, the desired relationship being based upon at least one of a driver condition factor, a driving conditions factor, a vehicle condition factor, and a driver input factor”, [0018] “At least one historical speed profile is generated for each road segment A-F, the speed profile based upon data collected from probe vehicles that have previously driven over the segment. In FIG. 1, historical speed profiles are identified as a through f related to road segments A through F respectively.”, and [0022] “a method of monitoring the speed of a vehicle and identifying that the vehicle may be likely to exceed a target speed on a road segment if no corrective action is taken. The method begins at block 100 and progresses to block 110 where the vehicle location is determined. This may be accomplished, for example, utilizing a GPS navigation system and map database, as is well known. Progressing to block 120, the vehicle location is compared with a map data base to identify an approaching road segment, that is, a road segment that lies ahead of the vehicle as it progresses along its current and/or planned route of travel.”)
Claims 3 and 5-8 are rejected under 35 U.S.C. 103 as being unpatentable over Rupp et al. (US 20110301802 A1) in view of Max et al. (US 20210034072 A1) and further in view of MacDonald et al. (US 20210278231 A1).
Regarding claim 3, Rupp et al. in view of Max et al. discloses The method according to claim
1,
Rupp et al. discloses wherein the value of the swarm behavior of the second region
includes a plurality of value of the second region includes a plurality of values of the driving behavior of the vehicle, wherein the values of the driving behavior of the vehicle includes velocities of the vehicles during driving maneuvers, (Figure 1, and [0008] “the speed of an automotive vehicle is monitored and a vehicle system, such as a warning device, is activated if the vehicle speed is expected to exceed a target speed over an approaching road segment lying ahead of the vehicle. A speed profile of the approaching segment is accessed, the speed profile being generated by analyzing a statistical distribution of historical speed data collected from probe vehicles that have previously traveled over the approaching segment. The target speed is established based on a desired relationship with the speed profile, the desired relationship being based upon at least one of a driver condition factor, a driving conditions factor, a vehicle condition factor, and a driver input factor. The likelihood that the vehicle will exceed the target speed is assessed based, at least in part, on at least one measured vehicle dynamic property.”)
However, Rupp et al. in combination with Max et al. fails to explicitly disclose wherein the
values of the swarm behavior describe an average value of the values of the driving behavior of vehicles.
MacDonald et al. teaches wherein the values of the driving behavior of the vehicle includes
velocities of the vehicles during driving maneuvers, wherein the values of the swarm behavior describe an average value of the values of the driving behavior of vehicles. ([0005] “the system further includes the computerized processor being further operable to determine a speed of the closest in path vehicle to be followed, determine an average speed of the swarm of vehicles, and determine a relative position of the closest in path vehicle to be followed to the swarm of vehicles. The system further includes evaluating the data to determine whether the closest in path vehicle to be followed is exhibiting the good behavior in relation to the swarm of vehicles when a speed difference between the speed of the closest in path vehicle to be followed and the average speed of the swarm of vehicles is less than a threshold speed difference and when the relative position of the closest in path vehicle to be followed to the swarm of vehicles is closer than a threshold distance.”)
It would have been obvious to one of ordinary skill in the art before the effective filling date
of the claimed invention with reasonable expectations of success to modify the invention of Rupp et al. in combination with Max et al. to incorporate average speed of the swarm of vehicles as taught by MacDonald et al. for the purpose of “determin[ing] whether the closest in path vehicle to be followed is exhibiting the good behavior in relation to the swarm of vehicles.” ([0005], MacDonald et al.)
Regarding claim 5, Rupp et al. in view of Max et al. discloses The method according to claim
1,
However, Rupp et al. in combination with Max et al. fails to explicitly disclose wherein the
driving function controls the movable device in a partially or fully autonomous driving mode.
MacDonald et al. teaches wherein the driving function controls the movable device in a
partially or fully autonomous driving mode. ([0030] “A process and system for closest vehicle in path following for an autonomous or semi-autonomous host vehicle is provided including a real-time determination whether a closest vehicle in a current path for the vehicle being controlled is exhibiting good behavior worthy of being followed or bad behavior indicating that the host vehicle is not to be followed by the closest in path vehicle.”)
It would have been obvious to one of ordinary skill in the art before the effective filling date
of the claimed invention with reasonable expectations of success to modify the invention of Rupp et al. in combination with Max et al. to incorporate automatic driving control function as taught by MacDonald et al. for the purpose of allowing the vehicle to operate autonomously.
Regarding claim 6, Rupp et al. discloses A method for creating a map for ascertaining a
driving function of a movable device, the method comprising the following steps:
controlling the driving function of the movable device using specified parameters, (Abstract “A target (not-to-exceed) speed for a vehicle over a road segment ahead of the vehicle is established based on a desired relationship with a speed profile of the segment. The speed profile is generated by analyzing a statistical distribution of historical speed data over the segment collected by probe vehicles… applying the speed differential to the speed profile of the approaching segment”, figure 3, and see at least [0050])
locating the movable device within a behavior map, wherein the behavior map has
information about a swarm behavior of traveling devices; creating a map having at least a first region and a second region, (Figures 1 and 3, [0017] “a length of roadway 10 divided into six segments labeled A through F. Road segments may be delineated/identified based upon a standard or uniform distance (every 10 meters for example). Or, the segments may be based upon changes in one or more roadway characteristics such as radius of curvature, incline (uphill/downhill), bank angle, camber, road surface quality (rough/smooth, asphalt/concrete), and/or posted speed limit.”, [0018] “At least one historical speed profile is generated for each road segment A-F, the speed profile based upon data collected from probe vehicles that have previously driven over the segment.”, and [0022] “a method of monitoring the speed of a vehicle and identifying that the vehicle may be likely to exceed a target speed on a road segment if no corrective action is taken. The method begins at block 100 and progresses to block 110 where the vehicle location is determined. This may be accomplished, for example, utilizing a GPS navigation system and map database, as is well known.”)
ascertaining measured values of the driving function of the movable device; ([0008] “the speed of an automotive vehicle is monitored and a vehicle system, such as a warning device, is activated if the vehicle speed is expected to exceed a target speed over an approaching road segment lying ahead of the vehicle. A speed profile of the approaching segment is accessed, the speed profile being generated by analyzing a statistical distribution of historical speed data collected from probe vehicles that have previously traveled over the approaching segment. The target speed is established based on a desired relationship with the speed profile, the desired relationship being based upon at least one of a driver condition factor, a driving conditions factor, a vehicle condition factor, and a driver input factor. The likelihood that the vehicle will exceed the target speed is assessed based, at least in part, on at least one measured vehicle dynamic property.”) comparing the measured values and the values of the swarm behavior from the behavior map; ([0009] “the target speed is established by identifying a baseline road segment over which the vehicle has previously traveled, comparing a past speed of the vehicle over the baseline segment with a speed profile of the baseline segment, and applying the speed differential to the first speed profile.”, [0037] “one or more vehicle dynamic conditions are detected, including, for example, current vehicle speed and/or current longitudinal acceleration. At block 170, the vehicle dynamic conditions from block 160 are analyzed relative to the target speed to determine whether the vehicle is or is likely to exceed the target speed over the approaching road segment. Other factors may be included in making this target speed comparison, such as an available deceleration distance between the current vehicle position and the approaching road segment and/or an allowable vehicle deceleration rate.”, and see at least figure 3)
wherein the swarm behavior has values with a specifiable tolerance zone; ([0019] “Each
speed profile a-f is generated or calculated by statistically analyzing the cumulative data gathered by the probe vehicles. The data may be plotted graphically as shown in FIG. 2, showing the number of vehicle trips over the segment for falling into given vehicle speed ranges or bins. In the FIG. 2 embodiment, speed bins every 2 miles per hour are used for the plot. A statistical distribution may be determined from the plot. For example, the FIG. 2 distribution may be identified as a normal distribution having a mean value and a standard deviation (sigma)”)
wherein the first region of the map is defined as a region in which the comparison
between the measured values and the values of the swarm behavior lies within the tolerance zone, (Figure 3, [0022] “monitoring the speed of a vehicle and identifying that the vehicle may be likely to exceed a target speed on a road segment if no corrective action is taken. The method begins at block 100 and progresses to block 110 where the vehicle location is determined. This may be accomplished, for example, utilizing a GPS navigation system and map database, as is well known. Progressing to block 120, the vehicle location is compared with a map data base to identify an approaching road segment, that is, a road segment that lies ahead of the vehicle as it progresses along its current and/or planned route of travel.”, and [0024] “a desired relationship between the speed profile accessed for the approaching segment and the current vehicle (or vehicle/driver combination) is determined. The desired relationship may, for example, be expressed in terms of a statistical deviation from a mean value. If the speed profile is identified as having a normal distribution as in FIG. 2, the desired relationship may be that the vehicle should travel at a speed equal to the mean value for the road segment, or at a speed equal to one (or more) sigma above or below the mean value.”)
wherein the second region is defined as a region in which the comparison between the
measured values and the values of the swarm behavior lies outside the tolerance zone, (S130-S180, Figure 3, [0022] “monitoring the speed of a vehicle and identifying that the vehicle may be likely to exceed a target speed on a road segment if no corrective action is taken. The method begins at block 100 and progresses to block 110 where the vehicle location is determined. This may be accomplished, for example, utilizing a GPS navigation system and map database, as is well known. Progressing to block 120, the vehicle location is compared with a map data base to identify an approaching road segment, that is, a road segment that lies ahead of the vehicle as it progresses along its current and/or planned route of travel.”, [0024] “a desired relationship between the speed profile accessed for the approaching segment and the current vehicle (or vehicle/driver combination) is determined. The desired relationship may, for example, be expressed in terms of a statistical deviation from a mean value. If the speed profile is identified as having a normal distribution as in FIG. 2, the desired relationship may be that the vehicle should travel at a speed equal to the mean value for the road segment, or at a speed equal to one (or more) sigma above or below the mean value.”)
wherein at least one value of the swarm behavior from the behavior map is entered for
the second region. ; (Figure 1, [0017] “a length of roadway 10 divided into six segments labeled A through F. Road segments may be delineated/identified based upon a standard or uniform distance (every 10 meters for example). Or, the segments may be based upon changes in one or more roadway characteristics such as radius of curvature, incline (uphill/downhill), bank angle, camber, road surface quality (rough/smooth, asphalt/concrete), and/or posted speed limit.”, and [0018] “At least one historical speed profile is generated for each road segment A-F, the speed profile based upon data collected from probe vehicles that have previously driven over the segment.”)
Rupp et al. may be alleged to not explicitly disclose wherein at least one value of
a swarm behavior is entered in the second region and using the at least one value of the swarm behavior to ascertain the driving function, when the movable device is in the second region of the map;
Max et al. teaches wherein at least one value of a swarm behavior is entered in the
second region and using the at least one value of the swarm behavior to ascertain the driving function, when the movable device is in the second region of the map; ([0018] “numerous vehicles traveling in a given lane transmit their respective trajectories to a back-end computer, which then determines and stores a swarm trajectory from the trajectories it has received for a given lane.”, [0025] “The ego-vehicle may determine which boundary conditions, or combination of boundary conditions, are used for determining the swarm trajectory in the data base. This can take place, e.g., in that only the selected boundary conditions are sent to back-end computer, such that it can also execute a data base search using only these boundary conditions. It is also conceivable to send numerous swarm trajectories to the ego-vehicle, corresponding to the number of boundary conditions and/or the desired combinations of boundary conditions.”, [0026] “The current driving trajectory for the ego-vehicle may be corrected of affected by the swarm trajectories that have been sent to the ego-vehicle, e.g., in that the difference between the current driving trajectory and the swarm trajectory is determined, and this difference is used to correct the current trajectory of the ego-vehicle.”, and [0027] “The method can be extended accordingly for further route segments, and the respective route segments form a parameter for processing these further sections”)
It would have been obvious to one of ordinary skill in the art before the effective filling date
of the claimed invention with reasonable expectations of success to modify the invention of Rupp et al. to incorporate swarm trajectories of a plurality of other vehicles as taught by Max et al. for the purpose of improving navigation of the vehicle based on the plurality of other vehicles.
However, Rupp et al. in combination with Max et al. fails to explicitly disclose wherein the
driving function controls the movable device in a partially or fully autonomous driving mode;
MacDonald et al. teaches wherein the driving function controls the movable device in a
partially or fully autonomous driving mode; ([0030] “A process and system for closest vehicle in path following for an autonomous or semi-autonomous host vehicle is provided including a real-time determination whether a closest vehicle in a current path for the vehicle being controlled is exhibiting good behavior worthy of being followed or bad behavior indicating that the host vehicle is not to be followed by the closest in path vehicle.”)
It would have been obvious to one of ordinary skill in the art before the effective filling date
of the claimed invention with reasonable expectations of success to modify the invention of Rupp et al. in combination with Max et al. to incorporate automatic driving control function as taught by MacDonald et al. for the purpose of allowing the vehicle to operate autonomously.
Regarding claim 7, Rupp et al. in view of Max et al. and MacDonald et al. discloses The
method according to claim 6,
Rupp et al. discloses wherein the swarm behavior of the behavior map comes from swarm
behavior data, (Figure 1) wherein the swarm behavior data includes a wealth of information about the driving behavior of vehicles, wherein the information includes velocities of vehicles during driving maneuvers, ([0008] “A speed profile of the approaching segment is accessed, the speed profile being generated by analyzing a statistical distribution of historical speed data collected from probe vehicles that have previously traveled over the approaching segment. The target speed is established based on a desired relationship with the speed profile, the desired relationship being based upon at least one of a driver condition factor, a driving conditions factor, a vehicle condition factor, and a driver input factor. The likelihood that the vehicle will exceed the target speed is assessed based, at least in part, on at least one measured vehicle dynamic property.”) wherein the swarm behavior of the behavior map describes an average value of the information from the swarm behavior data. ([0019] “Each speed profile a-f is generated or calculated by statistically analyzing the cumulative data gathered by the probe vehicles. The data may be plotted graphically as shown in FIG. 2, showing the number of vehicle trips over the segment for falling into given vehicle speed ranges or bins. In the FIG. 2 embodiment, speed bins every 2 miles per hour are used for the plot. A statistical distribution may be determined from the plot. For example, the FIG. 2 distribution may be identified as a normal distribution having a mean value and a standard deviation (sigma).”, and [0024] “a desired relationship between the speed profile accessed for the approaching segment and the current vehicle (or vehicle/driver combination) is determined. The desired relationship may, for example, be expressed in terms of a statistical deviation from a mean value. If the speed profile is identified as having a normal distribution as in FIG. 2, the desired relationship may be that the vehicle should travel at a speed equal to the mean value for the road segment, or at a speed equal to one (or more) sigma above or below the mean value.”)
However, Rupp et al. in combination with Max et al. may be alleged to not explicitly disclose
wherein the swarm behavior of the behavior map describes an average value of the information from the swarm behavior data.
MacDonald et al. teaches wherein the swarm behavior
average value of the information from the swarm behavior data. ([0005] “the system further includes the computerized processor being further operable to determine a speed of the closest in path vehicle to be followed, determine an average speed of the swarm of vehicles, and determine a relative position of the closest in path vehicle to be followed to the swarm of vehicles. The system further includes evaluating the data to determine whether the closest in path vehicle to be followed is exhibiting the good behavior in relation to the swarm of vehicles when a speed difference between the speed of the closest in path vehicle to be followed and the average speed of the swarm of vehicles is less than a threshold speed difference and when the relative position of the closest in path vehicle to be followed to the swarm of vehicles is closer than a threshold distance.”)
It would have been obvious to one of ordinary skill in the art before the effective filling date
of the claimed invention with reasonable expectations of success to modify the invention of Rupp et al. in combination with Max et al. to incorporate average speed of the swarm of vehicles as taught by MacDonald et al. for the purpose of “determin[ing] whether the closest in path vehicle to be followed is exhibiting the good behavior in relation to the swarm of vehicles.” ([0005], MacDonald et al.)
Regarding claim 8, as best understood by the Examiner, Rupp et al. in view of Max et al. and
MacDonald et al. discloses The method according to claim 6,
Rupp et al. discloses wherein the parameters for controlling the driving function come
from calculations, wherein the calculations are performed based on the swarm behavior of the behavior map, wherein target values for the calculations are defined from the swarm behavior, wherein the calculations are performed in iterative steps until the parameters provide a solution for achieving the target values, or until the parameters in a final iterative step provide the same number of achieved target values as in a previously performed penultimate iterative step. (Figure 3, [0008] “the speed of an automotive vehicle is monitored and a vehicle system, such as a warning device, is activated if the vehicle speed is expected to exceed a target speed over an approaching road segment lying ahead of the vehicle. A speed profile of the approaching segment is accessed, the speed profile being generated by analyzing a statistical distribution of historical speed data collected from probe vehicles that have previously traveled over the approaching segment. The target speed is established based on a desired relationship with the speed profile, the desired relationship being based upon at least one of a driver condition factor, a driving conditions factor, a vehicle condition factor, and a driver input factor”, [0018] “At least one historical speed profile is generated for each road segment A-F, the speed profile based upon data collected from probe vehicles that have previously driven over the segment. In FIG. 1, historical speed profiles are identified as a through f related to road segments A through F respectively.”, and [0022] “a method of monitoring the speed of a vehicle and identifying that the vehicle may be likely to exceed a target speed on a road segment if no corrective action is taken. The method begins at block 100 and progresses to block 110 where the vehicle location is determined. This may be accomplished, for example, utilizing a GPS navigation system and map database, as is well known. Progressing to block 120, the vehicle location is compared with a map data base to identify an approaching road segment, that is, a road segment that lies ahead of the vehicle as it progresses along its current and/or planned route of travel.”)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Munning et al. (WO 2022111992 A1) teaches determining a target speed for a lateral assistance system of an at least partially assisted motor vehicle.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MISA HUYNH NGUYEN whose telephone number is (571)270-5604. The examiner can normally be reached Monday-Friday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anne Antonucci can be reached at (313) 446-6519. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MISA H NGUYEN/ Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/ Supervisory Patent Examiner, Art Unit 3666
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