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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 8/26/24 has been entered.
Status of Claims
Claims 1, 9 and 20 are amended.
Claims 3, 5, 10 and 13 are previously cancelled.
Claims 21-24 are new
Claims 1, 3, 4, 6-9, 11-12 and 14-24 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Independent claims 1, 9, and 20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The term “eco-roll” is not found in the Specification. And the eco-roll feature as shown in U-Tube: Scania Eco-roll: https://www.youtube.com/watch?v=7JVhdVoEHeQ ; 57,204 views Nov 15, 2013. Scania's new Eco-roll function will help customers in Europe reduce fuel use when it becomes available in early 2014. The feature, which chooses optimal times for trucks to roll downhill in neutral, will be available from the first quarter 2014 to European customers who purchase a truck fitted with Scania Opticruise and Scania Active Prediction. Eco-roll promises to cut fuel use by up to two percent, depending on the terrain in which a vehicle is travelling.” [as stated in the U-tube site indicated above).
Response to Arguments/remarks
Rejections under 35 U.S.C. 112a above
Applicant did not respond to this 112a for new matter. It is required to reply to all 112(a) and (b) rejections, Please correct. The 112A above is being maintained.
Rejections under 35 U.S.C. 112 (f)
The Rejections under 35 U.S.C. 112 (f) was not addressed in the Remarks, and the Specification has been fully considered. The 35 U.S.C. 112 (f) will stand. Plus a new 112(f) is included concerning the amendment.
Prior art rejection
Applicant’s broad arguments with respect to claims 1, 3-4, 6-9, 11-12 and 14-20 have been considered but are moot in view of the new ground(s) of rejection as necessitated by applicant's amendments
Note that under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification. The plain meaning of a term means the ordinary and customary meaning given to the term by those of ordinary skill in the art at the relevant time. The ordinary and customary meaning of a term may be evidenced by a variety of sources, including the words of the claims themselves, the specification, drawings, and prior art. However, the best source for determining the meaning of a claim term is the specification - the greatest clarity is obtained when the specification serves as a glossary for the claim terms. The words of the claim must be given their plain meaning unless the plain meaning is inconsistent with the specification. 2111.01 (I). See also In re Marosi, 710 F.2d 799, 802, 218 USPQ 289, 292 (Fed. Cir. 1983) ("'[C]laims are not to be read in a vacuum, and limitations therein are to be interpreted in light of the specification in giving them their ‘broadest reasonable interpretation.'"2111.01 (II)
With respect to the interpretation of claim terms, MPEP 2111 states:
The Patent and Trademark Office ("PTO") determines the scope of claims in patent applications not solely on the basis of the claim language, but upon giving claims their broadest reasonable construction "in light of the specification as it would be interpreted by one of ordinary skill in the art." In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364[, 70 USPQ2d 1827, 1830] (Fed. Cir. 2004). Indeed, the rules of the PTO require that application claims must "conform to the invention as set forth in the remainder of the specification and the terms and phrases used in the claims must find clear support or antecedent basis in the description so that the meaning of the terms in the claims may be ascertainable by reference to the description." 37 CFR 1.75(d)(1).
The words of the claim must be given their plain meaning unless the plain meaning is inconsistent with the specification In re Zletz, 893 F.2d 319, 13 USPQ2d 1320 (Fed. Cir. 1989).
"Though understanding the claim language may be aided by explanations contained in the written description, it is important not to import into a claim limitations that are not part of the claim. For example, a particular embodiment appearing in the written description may not be read into a claim when the claim language is broader than the embodiment." Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004).(see MPEP 2111.01).
During patent examination, the pending claims must be "given their broadest reasonable interpretation consistent with the specification." The broadest reasonable interpretation does not mean the broadest possible interpretation. Rather, the meaning given to a claim term must be consistent with the ordinary and customary meaning of the term (unless the term has been given a special definition in the specification), and must be consistent with the use of the claim term in the specification and drawings. Further, the broadest reasonable interpretation of the claims must be consistent with the interpretation that those skilled in the art would reach. In re Cortright, 165 F.3d 1353, 1359, 49 USPQ2d 1464, 1468 (Fed. Cir. 1999) (see PMEP 2111).
Accordingly, the claims herein will be interpreted in accordance with the MPEP 2111.
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 claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation is: “Control arrangement” in claims 9-20 (note that it is not clear if this is software or hardware, even after reading the specification).Also in Claims 1, 9, 20, and 21, the terms sensitivity parameters and vehicle-specific influence are indefinite in that they are not explained clearly in the specification.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 9-20 for control arrangement and Claims 1, 9, 20, and 21 for sensitivity parameters and vehicle-specific influence” 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. There is no definition or explanation of what is exactly meant by the sensitivity parameters or what vehicle-specific influences are in detail, thus are indefinite.
Claim limitation “Control arrangement, sensitivity parameters and vehicle-specific influence” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function for control arrangement, sensitivity parameters or exactly what the vehicle-specific influences are. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claims so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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.
Claims 1, 3, 4, 6-10, 11-12, 14- 20 are rejected under 35 U.S.C. 103 as being unpatentable over Fridman [US 20180025235, now Fridman], with Siobbel et al. [WO2010081836, now Siobbel], with Yasui et al. [EP1407949, now Yasui], with Stankoulov [US20160153796, now Stank], further with Ramirez et al. [US10096038, now Ramirez], further with Applicant admitted prior art (AAPA), further with U-Tube: Scania Eco-roll: https://www.youtube.com/watch?v=7JVhdVoEHeQ ; 57,204 views Nov 15, 2013 [now U-tube]
Claim 1
Fridman discloses a computer implemented method adapted to determine road conditions for a road, the road comprising at least a first road segment [see at least Fridman, Abstract (“Systems and methods are provided for crowdsourcing road surface information collection. In one implementation, a method of collecting road surface information for a road segment may include receiving at least one image representative of a portion of the road segment, identifying in the at least one image at least one road surface feature along the portion of the road segment, determining a plurality of locations associated with the road surface feature according to a local coordinate system of the vehicle, and transmitting the determined plurality of locations from the vehicle to a server. The determined locations may be configured to enable determination by the server of a line representation of the road surface feature extending along the road segment.”); ¶ 0212 (“Data collected from traversing vehicles may also be used to identify road profile information, such as road width profiles, road roughness profiles, traffic line spacing profiles, road conditions, etc. Using the collected information, sparse map 800 may be generated and distributed (e.g., for local storage or via on-the-fly data transmission) for use in navigating one or more autonomous vehicles. However, in some embodiments, map generation may not end upon initial generation of the map. As will be discussed in greater detail below, sparse map 800 may be continuously or periodically updated based on data collected from vehicles as those vehicles continue to traverse roadways included in sparse map 800.”)];
one or more of the following: at least one of a weight of the first vehicle, a tire selection for the first vehicle, [[or]] a temperature at the first road segment, or a length of the first road segment [see at least Fridman, Abstract; ¶ 0011 (“ The navigation information from the plurality of vehicles may be associated with a common road segment. The method may further comprise storing, by the server, the navigation information associated with the common road segment, and generating, by the server, at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles. The autonomous vehicle road navigation model for the common road segment may include at least one line representation of a road surface feature extending along the common road segment, and each line representation may represent a path along the common road segment substantially corresponding with the road surface feature. Moreover, the road surface feature may be identified through image analysis of a plurality of images acquired as the plurality of vehicles traverse the common road segment. The method may further comprise distributing, by the server, the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating the one or more autonomous vehicles along the common road segment.”)]; Note; this correlates to the “vehicle independent road condition for the first segment.”];
receiving, by the server, a respective collection of vehicle data from a plurality of vehicles, the collection of vehicle data comprising the road resistance value for the first road segment for each respective vehicle, operational data for the respective vehicle for the first road segment and sensitivity parameters for the respective vehicle [see at least Fridman, ¶ 0010 * 0011(“Each line representation may represent a path along the road segment substantially corresponding with the road surface feature, and the road surface feature may be identified through image analysis of a plurality of images acquired as one or more vehicles traverse the road segment…In other embodiments, a system for generating a sparse map for autonomous vehicle navigation along a road segment may comprise at least one processing device. The at least one processing device may be configured to receive a plurality of images acquired as one or more vehicles traverse the road segment; identify, based on the plurality of images, at least one line representation of a road surface feature extending along the road segment; and identify, based on the plurality of images, a plurality of landmarks associated with the road segment. Each line representation may represent a path along the road segment substantially corresponding with the road surface feature.”); 0013 (“plurality of vehicles”)];
adjusting, by the ECU arranged onboard the second vehicle, operation of the second vehicle based on the estimated energy consumption, [see at least Fridman, ¶ 0212 (“Data collected from traversing vehicles may also be used to identify road profile information, such as road width profiles, road roughness profiles, traffic line spacing profiles, road conditions, etc. Using the collected information, sparse map 800 may be generated and distributed (e.g., for local storage or via on-the-fly data transmission) for use in navigating one or more autonomous vehicles. However, in some embodiments, map generation may not end upon initial generation of the map. As will be discussed in greater detail below, sparse map 800 may be continuously or periodically updated based on data collected from vehicles as those vehicles continue to traverse roadways included in sparse map 800.”); Update has the same as meaning adjust”)].
Siobbel also teaches a computer implemented method adapted to determine road conditions for a road, the road comprising at least a first road segment [see at least Siobbel, ¶ 0009; 0011 (“real life conditions”); 0013 (“road segments”); 0035 (“environmental conditions”); 0063 (“Rolling resistance is another parameter. The vehicle energy consumption is governed by the vehicle speed as described by the energy load equation stated previously. The quantification of this energy may be accomplished by adopting a similar approach as above - namely summing the length of the stretches of road where the vehicle speed falls within a specific category. Other parameters to assess the rolling resistance parameter can be to estimate the rolling resistance coefficient (Cn), assume vehicle mass per class, or the like.”)], wherein the method comprises the steps of:
determining , by a control unit arranged onboard a first vehicle a road resistance value for the first road segment where the first vehicle is currently travelling, wherein the road resistance value is dependent on a current operation of the first vehicle at the first road segment and at least one of a weight of the first vehicle, a tire selection for the first vehicle, or a temperature at or a length of the first road segment [see at least Siobbel, ¶ 0059 (“In fact, the energy consumption along a road can be even more accurately approximated if additional parameters are known such as: vehicle mass, air density, aerodynamic drag, frontal area, rolling resistance, gravitational acceleration, road gradient and rotational inertia of the power train. Calculating an energy cost may also include specialization by vehicle category, such as separate categories for trucks, passenger cars, buses, etc. The vehicle category-specific energy cost may then be derived from probe data bundled by vehicle category. In other words, probe data acquired from bus transits will be used to calculate an energy cost that is specific to buses, and so forth.”); 0062- 0063 (“length…Vehicle mass (weight)”); ,
providing, by the onboard control unit, a collection of vehicle data to a server arranged in networked communication with the control unit, the collection of vehicle data comprising the road resistance value for the first road segment, operational data for the first vehicle for the first road segment and sensitivity parameters for the first vehicle [see at least Siobbel, ¶ 0012 (“probe data”; 0031 (“The invention can be implemented in any type of standard navigation system available on the market, on mapping and navigation web sites/servers as far as energy efficient route planning is concerned, as well as suitable systems which may be developed in the future.”); 0059; 0063 (“rolling resistance”)]; and
normalizing the respective collection of vehicle data, including the collection of vehicle data from the first vehicle [see at least Siobbel, ¶ 0043 (“For some examples, an RRDSL 16 can be represented and stored as a parametric curve as a function of distance, or perhaps as a set of discrete optimal speeds between which to linearly interpolate, or normalized variations (percentages) above and below a legal speed limit/artificial threshold, to name a few possibilities…”); 0061 (“(This can also be normalized over the length of the road link.) This would give a count of positive and negative acceleration energy peaks which, as stated previously, may be used to more fully develop an energy cost and provide an efficient estimating tool.”); 0065 (“For some examples, an acceleration index can be represented and stored in a map database by approximation of the positive and negative peaks in terms of their position along a link together with the respective vertical size and horizontal width, or as a parametric curve as a function of distance, or perhaps as a set of discrete optimal speeds between which to linearly interpolate, normalized over the road link length, etc. Those of skill in the field of digital map database construction and implementation will readily appreciate these and possible other suitable techniques how to represent and store an acceleration index in a map database.”)],
the normalization being based on the sensitivity parameters and the operational data to compensate for vehicle-specific influences,[see at least Siobbel, ¶ 0043; 0061; 0065],
estimating, at the server, a vehicle independent road condition for the first segment based on [[a]] the normalized collections of vehicle data for the first road segment [see at least Siobbel, ¶ 0059 (“ ¶ 0060 (“single index which can be attributed to a link in a digital map database per travel direction or even per lane.”); 0061; 0065];
distributing, using the server, the vehicle independent road condition for the first segment to a second vehicle using the networked connection, the second vehicle travelling along the road, and estimating, using an ECU arranged onboard the second vehicle, an energy consumption for the second vehicle when travelling at the first segment based on the vehicle independent road condition for the first segment and a current operation of the second vehicle at the first road segment [see at least Siobbel, ¶ 0059 (“The vehicle category-specific energy cost may then be derived from probe data bundled by vehicle category. In other words, probe data acquired from bus transits will be used to calculate an energy cost that is specific to buses, and so forth.”); Note: This statement proves that the “road condition” value calculated is not specific to a vehicle but it could be specific to a category of vehicles if need be. ¶ 0060 (“This value can then be considered in the routing algorithm to prefer those links which most precisely minimize the energy consumption.”); 0065].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Yasui more specifically teaches computer implemented method adapted to determine road conditions for a road [see at least Yasui, ¶ 0001 (“road condition estimation apparatus, particularly relates to an apparatus for estimating a grip factor indicative of a grip level of tire on a road surface in a lateral direction of a vehicle wheel, and/or estimating a coefficient of friction of each wheel to a road surface on the basis of the grip factor, to estimate a road condition on the basis of at least one of road factors including the grip factor and the coefficient of friction.”)];
determining , an electronic control unit (ECU) arranged onboard a first vehicle a road resistance value [see at least Yasui, ¶ 0013 (“On the contrary, if the grip factor as described before is used directly for the various controls, they can be achieved appropriately in accordance with a road condition, at the early stage well before the friction between the road surface and the tire comes to its limit. In addition, the coefficient of friction of the road surface can be estimated on the basis of the grip factor, as will be described later in detail. Therefore, if the grip factor and the coefficient of friction are employed as the road factors, to estimate the road condition on the basis of the road factors, the road condition can be estimated at the early stage well before the friction between the road surface and the tire comes to its limit.”); ¶ 0015-0017 (“road condition estimation apparatus”); control unit [see at least Yasui, under Description ¶ 0004 (“control system”); 0008 (“Control system”); 0027 (“control system”); 0028 (“As shown in FIG.3, at the wheels WH1-WH4, 25 there are provided wheel speed sensors WS1-WS4, re- sportively, which are connected to the electronic con- troller ECU, and by each of which a signal having pulses proportional to a rotational speed of each wheel, i.e., a wheel speed signal is fed to the electronic controller 30 ECU. Furthermore, there are provided a brake switch BS which turns on when the brake pedal BP is de- pressed, and turns off when the brake pedal BP is re- leased, steering angle sensor FS for detecting a steer-ing angle 8xxofthe front wheels WH1 and WH2, a steer-ing angle sensor RS for detecting a steering angle 8r of the rear wheels WH3 and WH4, a longitudinal acceleration sensor XG for detecting a vehicle longitudinal ac- calibration Gx, a lateral acceleration sensor YG for detecting a vehicle lateral acceleration Gy, a yaw rate sensor YR for detecting a yaw rate y of the vehicle, and so on, which are electrically connected to the electronic controller ECU.”); 0029 (“control system…control unit”)];
road resistance value [see at least Yasui, Abstract (“A grip factor estimation unit (M10) approximates the grip factor of the tire of the wheel based on the relationship between the aligning torque and wheel factor.”) and uses an ECU for compiling data].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel, with the more specific estimation of road conditions taught in Yasui. Thus providing a more effective and efficient technique for determining and estimating the best route.
Examiner’s Note: Fridman is a more general patent for estimating road conditions and using the different vehicles and different actions/conditions to determine a conclusion that can be used in vehicles and is supported by Soibble. Yasui is more specific in how it determines that road estimation.
Stank also teaches in more detail resistance…operational data…estimating… road condition… energy consumption…energy cost [see at least Stank, Abstract (“cost”); ¶ 0008 (target cost”); 0055 (“cost”); 0074 (“The system 100 may also report or send to remote servers, a smartphone, tablets, and/or other appropriate devices, estimated range, logging information, status information, a display range polygon, etc.”); 0015 (“rolling resistance”); 0015 (“aerodynamic drag”); 0016 (climbing resistance”)];
wherein the operation includes at least one of eco-roll or energy management [see at least Stank, Abstract; 0008, 0055].
Note the New Matter rejection above that Indicates that neither eco-roll or energy management are indicated in the Specification. Stank does teach to these concepts, as shown above. The eco-roll is well known in the art and it shows in the new Matter statement above a U-tube reference from 2013, the eco-roll concept. (see reference stated in New Matter rejection) (see further rejection on eco-roll below).
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles, with the process of determining and calculating the best route of Siobbel, with the more specific estimation of road conditions taught in Yasui, further with the ability to use multiple factors associated with the vehicle, roadways, etc. to estimate and determine routes, costs, and energy consumption shown in Stank. Thus providing a more effective and efficient technique for determining and estimating the best route.
Ramirez also teaches the normalization being based on the sensitivity parameters and the operational data to compensate for vehicle-specific influences in general terms [see at least Ramirez, Col. 12, lines 6-12 (explains normalizing factors based on all types of data which includes sensitivity and operational date for influences of a vehicle operation)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles, with the process of determining and calculating the best route of Siobbel, with the more specific estimation of road conditions taught in Yasui, further with the ability to use multiple factors associated with the vehicle, roadways, etc. to estimate and determine routes, costs, and energy consumption shown in Stank. Thus providing a more effective and efficient technique for determining and estimating the best route.
None of the references specifically teach but U-Tube: Scania Eco-roll: https://www.youtube.com/watch?v=7JVhdVoEHeQ ; 57,204 views Nov 15, 2013 teaches the operation includes at least one of eco-roll or energy management [see U-tube].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles, with the process of determining and calculating the best route of Siobbel, with the more specific estimation of road conditions taught in Yasui, further with the ability to use multiple factors associated with the vehicle, roadways, etc. to estimate and determine routes, costs, and energy consumption shown in Stank, further with the U-Tube video on eco-roll, an energy management system. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 2 cancelled.
Claim 3
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Fridman does not disclose but Siobbel further teaches estimating, onboard the second vehicle a total energy consumption for the second vehicle when travelling along the road [see at least Siobbel, ¶ 0065 (“a formula to calculate or estimate the energy consumption more accurately over each link in the map database may include any or all of the components mentioned above, but in all cases includes at least the speed-acceleration index (i.e., LSPs) as defined.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Stank also teaches estimating…energy consumption [see at least Stark, Abstract (“cost”); ¶ 0008 (target cost”); 0055 (“cost”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles, with the process of determining and calculating the best route of Siobbel, with the more specific estimation of road conditions taught in Yasui, further with the ability to use multiple factors associated with the vehicle, roadways, etc. to estimate and determine routes, costs, and energy consumption shown in Stank. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 4
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Fridman does not disclose but Siobbel teaches the total energy consumption is further dependent on a predicted speed for the first road segment [see at least Siobbel, ¶ 0065 (“speed acceleration index”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 5 cancelled.
Claim 6
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Fridman does not disclose but Siobbel teaches wherein the sensitivity parameters for the first vehicle are related to aerodynamic properties for the first vehicle [see at least Siobbel, ¶ 0038 (“The RRDSL is thus characteristic for specific locations along a road link and renders all effects which physically restrict the vehicles from going faster. As the information is derived from vehicle probes and reflects true driving, it may at times exceed the legal speed restriction. When the RRDSL is represented along a road in a continuous or semi continuous way, one could call it an undisturbed speed which, when driven, is influenced primarily by the physical attributes of the road segment (e.g., its geometry) and the posted speed limits (if any). The RRDSL can therefore be classified an attribute of a road segment; it does not vary over time of day. Only when road construction changes or road furniture is changed, or probe statistics change, is the RRDSL expected to change. As an attribute, it is possible to consider future applications of this concept in which, for example, a percentage of the stored RRDSL could be taken in case weather/surface conditions are known. As probe data content and resolution improvements are available, lane and/or vehicle category dependencies may be represented in the RRDSL. For example, with sufficient data content, the RRDSL may reflect regulatory situations such as higher speed limit on left lane or lower speed limit for commercial vehicles, etc. That is, the RRDSL can optionally be dependent on the specific vehicle type, or more generalized in vehicle categories (e.g. Powered Two Wheeler, Heavy Truck, Light Commercial Vehicle or Passenger car). The RRDSL is particularly useful for Advanced Driver Assistance (ADAS) and other driving control purposes.”); 0041 (“In the case of multi-lane road segments, e.g., dual carriageways, variations in such profiles can also be lane dependent. In addition, a sub attribute representing the statistical signal of the RRDSL 16, e.g. in the form of a standard deviation, can be stored in the map as well. Either as an average value, or as a longitudinal varying representation along the road element.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 7
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Fridman further discloses wherein the step of estimating the vehicle independent road condition for the first segment is further based on a weather report for the road received at the server [see at least Fridman, ¶ 0330 (“ This database may include a representative sample of drives (with respect to various properties: e.g., time of day, season, weather condition, type of roadway).”);
Siobbel also teaches wherein the step of estimating the vehicle independent road condition for the first segment is further based on a weather report for the road received at the server [see at least Siobbel, ¶ 0046 (“As shown, an optional step "Dynamic real time parameter or coefficient (e.g. weather, road surface or visibility)" may feed into the step "Navigation Device or In-vehicle Driver Assist system to monitor current speed and compare with OLSP on road segment ahead of current position."”)].
Stank also teaches step of estimating the vehicle independent road condition for the first segment is further based on a weather report for the road received at the server [see at least Stank, 0109 (“Vehicle “costs” may include various elements (e.g., energy usage, fuel usage, driving time, driving distance, etc.). Thus some embodiments may determine not only whether a particular route is within an energy usage range but may determine whether a particular destination is within a time threshold.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the process of determining and calculating the best route of Siobbel, with the ability to use multiple factors associated with the vehicle, roadways, etc. to estimate and determine routes. This providing a more effective and efficient technique for determining and estimating the best route.
Claim 8
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Neither Fridman, Siobbel or Yasui specifically disclose/teach but Stank teaches estimating an operational range for the second vehicle based on the total energy consumption for the second vehicle [see at least Stank, Abstract (“range projection”); Fig. 9; ¶ 0003 - 0005 (“range”); 0053 (“Although various examples above and below may refer to roundtrip range projections, roundtrip range projection algorithms, and/or other factors associated with range, range is used as one example of the capabilities of some embodiments. In addition to (or instead of) projecting roundtrip vehicle range, some embodiments may include the capability of determining roundtrip vehicle routes and/or estimating vehicle emissions using the same systems, algorithms, data structures, etc. as those described above and below.”); 0072 (“range”); 0075 (“range projection system”); 0143 (“FIG. 9 illustrates a schematic block diagram of a system that uses a vehicle cost model 900 of some embodiments. As shown, the system (or “engine”) may include a route calculation element (or “module”) 910, a map display element 920, a range projection element 940, a vehicle cost element 940, and a route cost element 950.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles, with the process of determining and calculating the best route of Siobbel, with the more specific estimation of road conditions taught in Yasui, further with the ability to use multiple factors associated with the vehicle, roadways, etc. to estimate and determine routes, costs, and energy consumption shown in Stank. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 9
Claim 9 is the control apparatus for the method of Claim 1, thus has similar limitations to claim 1, therefore claim 9 is rejected with the same rationale as claim 1.
Claim 10 cancelled.
Claim 11
Claim 11 has similar limitations to claim 3, therefore claim 11 is rejected with the same rationale as claim 3.
Claim 12
Claim 12 has similar limitations to claim 4, therefore claim 12 is rejected with the same rationale as claim 4.
Claim 14
Claim 14 has similar limitations to claim 6, therefore claim 14 is rejected with the same rationale as claim 6.
Claim 15
Claim 15 has similar limitations to claim 7, therefore claim 15 is rejected with the same rationale as claim 7.
Claim 16
Claim 16 has similar limitations to claim 8, therefore claim 17 is rejected with the same rationale as claim 8.
Claim 17
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 9.
Fridman further discloses the first and the second vehicle [see at least Fridman, ¶ 0243 (“a first reconstructed trajectory 1101 may be determined based on data received from a first vehicle traversing road segment 1100 at a first time period (e.g., day 1), a second reconstructed trajectory 1102 may be obtained from a second vehicle traversing road segment 1100 at a second time period (e.g., day 2), and a third reconstructed trajectory 1103 may be obtained from a third vehicle traversing road segment 1100 at a third time period (e.g., day 3). Each trajectory 1101, 1102, and 1103 may be represented by a polynomial, such as a three-dimensional polynomial. It should be noted that in some embodiments, any of the reconstructed trajectories may be assembled onboard the vehicles traversing road segment 1100.”)].
Siobbel also teaches the first and the second vehicle [see at least Siobbel, ¶ 0035 (“it is known that improved fuel efficiency can be achieved by maintaining a constant, optimal vehicle speed. As a rule of thumb, this constant vehicle speed may be approximately 45-60 mph, however that range may vary from one vehicle type to another, as well as being influenced by environmental conditions, road geographies, and the like. It is further known that various road characteristics such as sharp turns, speed bumps, lane expansions/consolidations, traffic controls and other features can influence the ability to safely travel at a constant speed along a particular segment.”) Note: if there are different vehicles, then that discloses/teaches a first and second vehicle.].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 18
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 9.
Fridman further discloses at least one of the first and the second vehicle is a truck, a bus or a car [see at least Fridman, ¶ 0111 (“ system 100 may transmit data to a server according to an “intermediate” privacy level and include additional information not included under a “high” privacy level, such as a make and/or model of a vehicle and/or a vehicle type (e.g., a passenger vehicle, sport utility vehicle, truck, etc.)”); 0115 (“may be applicable to all types of vehicles including automobiles, trucks, trailers, and other types of vehicles.”)].
Siobbel further discloses wherein at least one of the first and the second vehicle is a truck, a bus or a car [see at least Siobbel, ¶ 0038 (“That is, the RRDSL can optionally be dependent on the specific vehicle type, or more generalized in vehicle categories (e.g. Powered Two Wheeler, Heavy Truck, Light Commercial Vehicle or Passenger car). The RRDSL is particularly useful for Advanced Driver Assistance (ADAS) and other driving control purposes.”); 0047 (“It may also be a function of vehicle category (passenger car, bus/truck, powered two-wheeler)”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 19
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Neither Fridman, Siobbel, Yasui or Stank disclose but Ramirez teaches wherein the truck is autonomously operated [see at least Ramirez, Column 24, line 53 – Column 25, line 3 (“In certain embodiments, vehicle sensors, vehicle on-board diagnostic systems (OBDs) and other vehicle-based systems and/or vehicle communication systems, may collect and/or transmit data pertaining to autonomous driving of the vehicles. In autonomous driving, the vehicle fulfills all or part of the driving without being piloted by a human. An autonomous car can be also referred to as a driverless car, self-driving car, or robot car. For example, in autonomous driving, a vehicle control computer 717 may be configured to operate all or some aspects of the vehicle driving, including but not limited to acceleration, braking, steering, and/or route navigation. A vehicle with an autonomous driving capability may sense its surroundings using the vehicle sensor 711 and/or receive inputs regarding control of the vehicle from the vehicle communications systems, including but not limited to short range communication system 712 telematics device 713, or other vehicle communication systems.”); Note: the vehicle can be any type of vehicle].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles, with the process of determining and calculating the best route of Siobbel, with the more specific estimation of road conditions taught in Yasui, further with the ability to use multiple factors associated with the vehicle, roadways, etc. to estimate and determine routes, costs, and energy consumption shown in Stank. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 20
Claim 20 is the computer program product comprising a non-transitory computer readable medium for the method of Claim 1, thus has similar limitations to claim 1, therefore claim 9 is rejected with the same rationale as claim 1.
Claim 21
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Fridman does not specifically disclose but Siobbel teaches the normalizing comprises adjusting the road resistance value using the sensitivity parameters and the operational data to compensate for vehicle-specific influences ,[see at least Siobbel, ¶ 0043; 0061; 0065].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 22
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Friedman further discloses the vehicle independent road condition represents a physical road or environmental condition affecting energy consumption for the first road segment [see at least Fridman, ¶ 0212].
Siobbel also teaches bases on energy consumption [see at least Siobbel, ¶ 0009; 0011].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 23
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Fiedman does not disclose but Siobbel teaches the operational data comprises vehicle speed, and the sensitivity parameters comprise aerodynamic properties of the vehicle [see at least Siobbel, ¶ 013 (“From this information, energy cost can be introduced and used by the routing algorithms in much the same way that current routing algorithms utilize other cost factors like travel time or distance information. While a full calculation of energy cost requires additional parameters such as aerodynamic drag, rolling resistance and road grade data, it has been discovered by the applicants that an energy cost parameter can be used in at least a basic capacity to predict or estimate energy/fuel consumption characteristics without resorting to vehicle specific information such as mass, frontal area, aerodynamic drag and the like.”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Claim 24
Fridman, Siobbel, Yasui, Stank, Ramirez and U-tube disclose/teach the method of Claim 1.
Fridman does not specifically disclose but Siobbel does teach the vehicle independent road condition is used for estimating energy consumption of different vehicles traveling on the first road segment [see at least Siobbel, ¶ 0035 (discusses using energy-efficient techniques for driving at a specific section of the road and considering the road conditions of the road) ].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the system and method proving crowdsourcing road surface information from numerous vehicles of Fridman, with the process of determining and calculating the best route of Siobbel. Thus providing a more effective and efficient technique for determining and estimating the best route.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOAN T GOODBODY whose telephone number is (571) 270-7952. The examiner can normally be reached on M-TH 7-3 (US Eastern time).
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/JOAN T GOODBODY/
Primary Examiner, Art Unit 3664
(571) 270-7952
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