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 .
Examiner Notes that the fundamentals of the rejections are based on the broadest reasonable interpretation of the claim language. Applicant is kindly invited to consider the reference as a whole. References are to be interpreted as by one of ordinary skill in the art rather than as by a novice. See MPEP 2141. Therefore, the relevant inquiry when interpreting a reference is not what the reference expressly discloses on its face but what the reference would teach or suggest to one of ordinary skill in the art.
Status of the Claims
This is a Final Office Action in response to Applicant’s amendment of 04 December 2025. Claims 1-8 and 10-21 are pending and have been considered as follows.
Response to Amendment and/or Argument
Applicant’s arguments with respect to claim(s) 1 and 12 under 35 U.S.C. 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant’s amendments and/or arguments with respect to the Claim Rejection of Claims 1-20 under 35 USC 101 as set forth in the office action of 11 September 2025 have been considered and are NOT persuasive. Specifically, Applicant argues:
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The Examiner’s Response:
The examiner has carefully considered Applicant’s arguments and respectfully disagrees for the following reasons:
Regarding Argument (i.):
Applicant asserts that the sensors and server are not generic because they obtain driver specific information (posture, voice, eye movement, grip force). Examiner respectfully disagrees with this argument. Generic components do not become non-generic merely because they are applied to obtain a particular type of data. The claim does not recite how the sensors technically capture posture, voice, eye movement or hand gripping force that indicating any IMPROVEMENT in sensor operations. Instead, the claim merely recites the result of obtaining information using conventional sensors known in the field. Applicant does not identify any improvement to sensor technology, new signal processing technique, new/improvement to server architecture. Therefore, the sensors and server are used in their ordinary capacity and remain generic.
Regarding Argument (ii.):
Applicant argues that because other devices (e.g. wearables, implanted sensors, manual input, PC) could be used, the claim meaningfully limits the abstract idea. Examiner respectfully disagrees for the following reason(s): (a) the eligibility analysis focuses on what is positively recited in the claim and whether those recited elements meaningfully limit the abstract idea to a practical application. The fact that other unclaimed/alternative method/devices could be used to achieve the same outcome does not change the nature of the claimed invention and the alternative devices does not demonstrate that the claimed elements are non-abstract or inventive. (b) Choosing one conventional input source (e.g. sensor) over another does not change the underlying operation of the system (i.e. using conventional sensor of gathering information). Hence, Applicant’s argument is NOT persuasive.
Regarding Argument (iii.):
Applicant’s argument that claim 1 is patent-eligible because “no human analog” exists is not persuasive. Patent eligibility analysis does not require that a human mind be capable of performing each claimed step, nor does it require the Office to demonstrate that a human could practically gather or analyze the recited information in the same manner. Claim 1 automates the process of observing a driver’s condition, assessing that condition, forming a judgement based on the observation and selecting a route accordingly. The use of onboard sensors and servers merely replaces human observation with conventional data-gathering components and does not change the underlying nature of the process. Moreover, the claim does not recite any specific technical manner in which posture, eye movement, or grip force are detected, analyzed, nor does it describe any technological improvement in sensing or computing. Accordingly, the absence of a precise human analog does not render the claim non-abstract and the claim remains directed to the abstract idea of collecting and analyzing information to make a routing decision.
Accordingly, Applicant’s argument regarding 35 U.S.C. 101 is NOT persuasive and the rejection is maintained. See 35 U.S.C. 101 rejections below for details.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1-8 and 10-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
101 Analysis – Step 1 – YES
Claim 1 is directed to a method; and claim 20 is directed to a system. Therefore, claims 1 and 12 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. The other analogous claims 12 is rejected for the same reasons as the representative claim 1 as discussed here. Claim 1 recites:
A method, performed by at least one processor of a system in a vehicle, for providing enhanced navigation, the method comprising:
obtaining, from a driver of the vehicle, information of a target destination;
determining, based on the information of the target destination, a plurality of possible routes from a current location of the vehicle to the target destination;
obtaining, from at least one onboard sensor of the vehicle, information associated with a current condition of the driver;
obtaining, from a server communicatively coupled to the system, information associated with a lifestyle of the driver;
predicting, based on the information associated with the current condition of the driver and the information associated with the lifestyle of the driver, a future condition of the driver;
selecting, from among the plurality of possible routes based on the predicted future condition of the driver, an optimal route from the current location to the target destination; and
presenting, to the driver, information of the optimal route;
wherein the information associated with the current condition of the driver comprises at least one of: a posture of the driver, an eye movement of the driver, or the driver’s hand grip force on a steering wheel of the vehicle.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, the “determining…”, “predicting…” and “selecting…” limitations in the context of this claim encompasses, e.g. a passenger travelling with a driver who frequently needs to stop for bathroom breaks, upon learning the destination they are visiting, mentally consider several routes, think about rest stops availability along each route, remembering that the driver skipped breakfast and drank a cup of coffee, and predicting the driver might soon need a break, and subsequently choosing a route with convenient rest areas and/or restaurants. The passenger then tells the driver which route to take; this example demonstrates that the claimed method amounts to mental evaluation and decision making based on driver’s lifestyle and current condition. Accordingly, the claim is directed to an abstract idea.
Examiner would also note MPEP 2106.04(a)(2)(III): The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. Here, the determination is a form of making evaluation and judgement based on observation (driver behavior).
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A method, performed by at least one processor of a system in a vehicle, for providing enhanced navigation, the method comprising:
obtaining, from a driver of the vehicle, information of a target destination;
determining, based on the information of the target destination, a plurality of possible routes from a current location of the vehicle to the target destination;
obtaining, from at least one onboard sensor of the vehicle, information associated with a current condition of the driver;
obtaining, from a server communicatively coupled to the system, information associated with a lifestyle of the driver;
predicting, based on the information associated with the current condition of the driver and the information associated with the lifestyle of the driver, a future condition of the driver;
selecting, from among the plurality of possible routes based on the predicted future condition of the driver, an optimal route from the current location to the target destination; and
presenting, to the driver, information of the optimal route;
wherein the information associated with the current condition of the driver comprises at least one of: a posture of the driver, an eye movement of the driver, or the driver’s hand grip force on a steering wheel of the vehicle.
For the following reason(s), the examiner submits that the above identified limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitation of acquiring a switching request, the examiner submits that these limitation are insignificant extra-solution activities that merely uses a computer (processor) to perform the process. In particular, the “obtaining…” and “wherein the information…” steps are recited at a high level of generality (i.e. as a general means of acquiring data) and amounts to mere data gathering which is a form of insignificant extra-solution activity. The “presenting…” step amounts to mere post solution activities which is a form of insignificant extra-solution activities. Lastly, the additional limitations of “processor”, “onboard sensors” and “server” merely describes how to generally “apply” the otherwise abstract ideas and/or additional limitations in a generic or general-purpose computer environment, where processor is recited as generic processor performing a generic computer function of acquiring data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component and merely automates the steps.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impost any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional limitations of “processor”, “onboard sensors” and “server”, the examiner submits that the processor is recited at a high-level of generality (i.e. as a generic computer component performing generic calculation) such that it amounts no more than mere instruction to apply the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations discussed above are insignificant extra-solutions activities.
As explained, the additional elements are recited at a high level of generality to simply implement the abstract idea and are not themselves being technologically improved. See, e.g., MPEP §2106.05; Alice Corp. v. CLS Bank, 573 U.S., 208,223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention”). Electric Power Group, LLC v, Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) (Selecting information for collection, analysis and display constitute insignificant extra-solution activity). Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016)( Generating a second menu from a first menu and sending the second menu to another location as performed by generic computer components). Hence, the claims are not patent eligible.
Dependent Claims
Dependent claims 2-8, 10-11, and 13-21 do not recite any further limitations that causes the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial except and/or additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent claims 2-8, 10-11, and 13-21 are not patent eligible under the same rationale as provided for in the rejection of claim 1.
As such, claims 1-8 and 10-21 are rejected under 35 USC § 101 as being drawn to an abstract idea without significant more, and thus are ineligible.
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.
Claim(s) 1-2, 8, 10-13 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kronberg (US 2011/0022298 A1) in view of Mathada et al. (US 2023/0138025 A1 hereinafter Mathada) and Hatakeyama (US 2013/0021463 A1).
Regarding claim 1 (similarly claim 12), Kronberg teaches A method, performed by at least one processor of a system in a vehicle, for providing enhanced navigation (see at least Abstract), the method comprising:
obtaining, from a driver of the vehicle, information of a target destination; (see at least Fig. 1- 5 [0019-0100]: When a driver has entered his vehicle, the driver inputs his personal data, e.g. a driver ID card into the system and a predetermined drive or route plan of the vehicle toward a desired destination.)
obtaining, from at least one onboard sensor of the vehicle, information associated with a current condition of the driver; (see at least Fig. 1- 5 [0019-0100]: A present level of impairment or drowsiness or alertness of the driver is measured by means of a driver state monitoring device, if such device is installed in the related vehicle.)
obtaining information associated with a lifestyle of the driver; (see at least Fig. 1- 5 [0019-0100]: The driver is requested by the system to input further data which are relevant for predicting the development of the level of a driver state, such as data which are related to his physical or health condition like the time of awakening, the duration of sleep during the prior night(s), the sleep quality and other vital contextual information. Additionally or alternatively, a part or all of these data can be retrieved in an optional second step from a first storage in which the data of the driver have been stored at the time of an earlier conduction of the method by the same driver.)
predicting, based on the information associated with the current condition of the driver and the information associated with the lifestyle of the driver, a future condition of the driver; (see at least Fig. 1- 5 [0019-0100]: The system calculates a prediction of the development of the level of alertness of the driver as a function of time beginning from the present time at t=0 and extending into the future on the basis of present level of driver alertness data (e.g. data related to driver’s physical or health condition like time of awakening, duration of sleep during the prior night(s), the sleep quality and any other vital contextual information recorded by a real-time driver state or drowsiness monitoring device ) and certain environment variables such as time of the day.)
selecting, based on the predicted future condition of the driver, an optimal route from the current location to the target destination; (see at least Fig. 1- 5 [0019-0100]: if there is no such high risk instance before the estimated time of reaching the destination or next planned stop, the driver is informed about a currently low risk or no risk of lack of alertness and the driver can start his drive. However, if it has been determined that a high risk instance will occur before the time of reaching the destination or the next planned stop, a modified drive (or route) plan or drive/rest schedule is calculated such that a next planned stop or rest will occur before or at the predicted next high risk instance.) and
presenting, to the driver, information of the optimal route. (see at least Fig. 1- 5 [0019-0100]:The established route is optimized with respect to the planning of stops and/or selection of a course during the route so that a desired or predetermined time of arrival at a desired destination can be kept. This adaptation is preferably presented to the driver in the form of an information on a display regarding a suggestion on how to change the established route, e.g. to make a stop at a certain place which is recommended by the driving support device on the basis of e.g. a navigation system including a database of stops which are appropriate for the related vehicle or truck along the route or an alternative segment of the route.)
It may be alleged that Kronberg does not explicitly disclosed determining, based on the information of the target destination, a plurality of possible routes from a current location of the vehicle to the target destination;
obtaining, from a server communicatively coupled to the system, information associated with a lifestyle of the driver;
selecting, from among the plurality of possible routes based on the predicted future condition of the driver, an optimal route from the current location to the target destination;
wherein the information associated with the current condition of the driver comprises at least one of: a posture of the driver, an eye movement of the driver, or the driver’s hand grip force on a steering wheel of the vehicle.
Mathada is directed to recommend routes in enhanced navigation system, Mathada teaches determining, based on the information of the target destination, a plurality of possible routes from a current location of the vehicle to the target destination; (see at least Fig. 1-5 [0028-0070]: The navigation program 110A, 110B obtains a tentative list of routes based on the input destination wherein the tentative list of routes may be utilized to identify one or more optimal routes.)
obtaining, from a server communicatively coupled to the system, information associated with a lifestyle of the driver; (see at least Fig. 1-5 [0028-0070]: The navigation program 110A, 110B (corresponds to server) may build a relationship tree between the primary user and each other user occupying the automobile, depicting the relationship of each other user to the primary user (i.e. driver). The relationship tree may be built so that once each user is identified, the health history (corresponds to life style) for each user may be extracted from a health repository. The health repository may host health data as well as the real-time biometric data.)
selecting, from among the plurality of possible routes based on the predicted future condition of the driver, an optimal route from the current location to the target destination; (see at least Fig. 1-5 [0028-0070]: Next, the navigation program 110 A, 110 B identifies the one or more optimal routes. The one or more optimal routes are identified based on the current conditions and the characteristics. As described above with respect to step 208 , each route in the tentative list of routes may be assigned a road quality index. This road quality index may be compared against the health threshold score of each user described above with respect to step 206 ) and
presenting, to the driver, information of the optimal route. (see at least Fig. 1-5 [0028-0070]: The navigation program 110 A, 110 B recommends the one or more optimal routes to the primary user. The one or more optimal routes may be recommended to the primary user, via audio and/or visual on a navigation display, in descending order from most suitable to moderately suitable.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Kronberg’s system and method for modifying a drive plan of a vehicle toward a target destination to incorporate the technique of determining, based on the information of the target destination, a plurality of possible routes from a current location of the vehicle to the target destination; obtaining, from a server communicatively coupled to the system, information associated with a lifestyle of the driver; and selecting, from among the plurality of possible routes based on the predicted future condition of the driver, an optimal route from the current location to the target destination as taught by Mathada with reasonable expectation of success to have a system in place that consider all relevant information that could impact the safety of the occupants of the automobile when calculating a route including leveraging data obtained from sensors on an internet of things (IoT) device, making the occupants of an automobile safer, and considering relevant information in real-time to calculate an optimal route (Mathada [0017]) and giving the driver more controls by offering multiple possible routes before starting a drive plan.
The combination of Kronberg in view of Mathada teaches detecting a current condition of the driver but does not explicitly teach wherein the information associated with the current condition of the driver comprises at least one of: a posture of the driver, an eye movement of the driver, or the driver’s hand grip force on a steering wheel of the vehicle.
Hatakeyama is directed to a biological body state assessment device that assess a biological state of a vehicle driver, Hatakeyama teaches wherein the information associated with the current condition of the driver comprises at least one of: a posture of the driver, an eye movement of the driver, or the driver’s hand grip force on a steering wheel of the vehicle. (see at least Fig. 1-13 [0026-0069]: the biological body state assessment device acquires face information of a driver that calculates variation in the eye open time of the driver and assess the vigilance of the driver on the basis of the variation in the eye open time of the driver and variation in face direction of the driver; and subsequently predict the time at which drowsiness occurs in the driver.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg and Mathada to incorporate the technique of detecting a current condition of the driver based on detected eye movement of the driver to predict a future drowsiness occurrence time of the driver as taught by Hatakeyama with reasonable expectation of success to increase the assessment accuracy of the absentminded state of the driver and recommend a driver to get rest and thereby improving driver’s safety (Hatakeyama [0007-0010]).
Regarding claim 2 (similarly claim 13), the combination of Kronberg in view of Mathada and Hatakeyama teaches The method according to claim 1 (similarly claim 12), Kronberg further teaches wherein the optimal route comprises at least one resting point that allows the driver to take a break, and wherein the at least one resting point coincides with a time and a place where the future condition of the driver is predicted to exceed a predefined threshold. (see at least Fig. 1- 5 [0019-0100]: if there is no such high risk instance before the estimated time of reaching the destination or next planned stop, the driver is informed about a currently low risk or no risk of lack of alertness and the driver can start his drive. However, if it has been determined that a high risk instance will occur before the time of reaching the destination or the next planned stop, a modified drive (or route) plan or drive/rest schedule is calculated such that a next planned stop or rest will occur before or at the predicted next high risk instance.)
Regarding claim 8, the combination of Kronberg in view of Mathada and Hatakeyama teaches The method according to claim 2, Kronberg further teaches wherein the at least one resting point comprises at least one of: a rest area, a restaurant, a truck stop, a parking area, a travel plaza, a scenic view point, and an accommodation facility. (see at least Fig. 1- 5 [0019-0100]: the navigation system include a database of stops which are appropriate for the related vehicles or trucks along the route or an alternative segment of the route.)
Regarding claim 10, the combination of Kronberg in view of Mathada and Hatakeyama teaches The method according to claim 1,
Kronberg further teaches wherein the information associated with the lifestyle of the driver comprises: a work schedule, a type of work, a wake-up time, a sleep time, a meal time, a rest time, blood glucose transitions, health history, medical intake history, history of medications taken, history of restroom visits, work stress level history, and driving history. (see at least Fig. 1- 5 [0019-0100]: The driver is requested by the system to input further data which are relevant for predicting the development of the level of a driver state, in the following embodiments in the form of the level of alertness of the driver, such as data which are related to his physical or health condition like the time of awakening, the duration of sleep during the prior night(s), the sleep quality (any, none, or a quality score between them) and other vital contextual information. Additionally or alternatively, a part or all of these data can be retrieved in an optional second step 12 from a first storage 39 in which the data of the driver have been stored at the time of an earlier conduction of the method by the same driver.)
Regarding claim 11 (similarly claim 20), the combination of Kronberg in view of Mathada and Hatakeyama teaches The method according to claim 1 (similarly claim 12) , further comprising:
Kronberg further teaches repeatedly performing, for at least a period of time, the obtaining the information associated with the current condition of the driver, the obtaining the information associated with the lifestyle of the driver, the predicting the future condition of the driver, the selecting the optimal route, and the presenting the information of the optimal route. (see at least Fig. 1- 5 [0019-0100]: Preferably, the prediction of the development of the level of the driver state (which is especially a level of alertness) is/are repeatedly updated during the drive with time intervals which are predetermined and/or determined by certain events during the drive like e.g. an actually reduced level of the driver state which occurs during the drive and has not been predicted, however, which is detected by means of a driver state monitoring device. In the latter case, not only the initiation of the conduction of the method, but as well the repetition frequency of these conductions can be determined by such an event. If e.g. a considerably decreased present level of alertness of the driver is detected by the driver state monitoring device, the repetition frequency can be appropriately increased, and vice versa.)
Regarding claim 19, the combination of Kronberg in view of Mathada and Hatakeyama teaches The system according to claim 13, Kronberg further teaches wherein the at least one resting point comprises at least one of: a rest area, a restaurant, a truck stop, a parking area, a travel plaza, a scenic view point, and an accommodation facility. (see at least Fig. 1- 5 [0019-0100]: the navigation system include a database of stops which are appropriate for the related vehicles or trucks along the route or an alternative segment of the route.)
wherein the information associated with the lifestyle of the driver comprises: a work schedule, a type of work, a wake-up time, a sleep time, a meal time, a rest time, blood glucose transitions, health history, medical intake history, history of medications taken, history of restroom visits, work stress level history, and driving history. (see at least Fig. 1- 5 [0019-0100]: The driver is requested by the system to input further data which are relevant for predicting the development of the level of a driver state, in the following embodiments in the form of the level of alertness of the driver, such as data which are related to his physical or health condition like the time of awakening, the duration of sleep during the prior night(s), the sleep quality (any, none, or a quality score between them) and other vital contextual information. Additionally or alternatively, a part or all of these data can be retrieved in an optional second step 12 from a first storage 39 in which the data of the driver have been stored at the time of an earlier conduction of the method by the same driver.)
Claim(s) 3 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kronberg in view of Mathada, Hatakeyama, Vogel (US 2014/0200800 A1) and Mason et al. (US 2015/0338226 A1 hereinafter Mason).
Regarding claim 3 (similarly claim 14), the combination of Kronberg in view of Mathada and Hatakeyama teaches The method according to claim 1 (similarly claim 12),
The combination of Kronberg in view of Matha and Hatakeyama does not explicitly teach wherein the predicting the future condition comprises predicting the future condition of the driver at a plurality of times and a plurality of places along each of the possible routes; and
wherein the optimal route comprises a plurality of resting points that allow the driver to take a break, each of the plurality of resting points coincides with a respective time from among of the plurality of times and a respective place from among of the plurality of places where the future condition of the driver is predicted to exceed a predefined threshold.
Vogel is directed to method and system for determining a suitability of a route for traveling on by a vehicle driver, Vogel teaches wherein the predicting the future condition comprises predicting the future condition of the driver at a plurality of times and a plurality of places along each of the possible routes; (see at least Fig. 1-3 [0005-0052]: A plurality of routes including sections between point A and a point Z are routes that are able to be traveled on by a vehicle driver. Each section of the respective route has its own maximum fatigue value assigned wherein the maximum fatigue value may be a function of characteristics of the respective section that refers to the attentiveness of the driver. For each section, a fatigue prediction value assigned to the driver may be determined that may be a function of the driving time of the driver up to the respective section already covered or to be covered. For each section, a comparison may be made between the maximum fatigue value of the section and the fatigue prediction value of the section.) and
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg, Mathada and Hatakeyama to incorporate the technique of predicting the future condition comprises predicting the future condition of the driver at a plurality of times and a plurality of places along each of the possible routes as taught by Vogel with reasonable expectation of success to provide a method for determining a suitability of a route for traveling based on a predicted fatigue state of a driver (Vogel [0003-0004]) and doing so would help a driver for effectively choosing a route.
The combination of Kronberg in view of Mathada, Hatakeyama and Vogel does not explicitly teach wherein the optimal route comprises a plurality of resting points that allow the driver to take a break, each of the plurality of resting points coincides with a respective time from among of the plurality of times and a respective place from among of the plurality of places where the future condition of the driver is predicted to exceed a predefined threshold.
Mason is directed to route optimization for vehicle, Mason teaches wherein the optimal route comprises a plurality of resting points that allow the driver to take a break, each of the plurality of resting points coincides with a respective time from among of the plurality of times and a respective place from among of the plurality of places where the future condition of the driver is predicted to exceed a predefined threshold. (see at least Fig. 4A-6 [0085-0112]: In addition, the route may be generated such that the driver is at a particular location when the route ends or when it is time for the driver to take a break. Advantageously, in certain embodiments, by defining the route so that the driver is at a particular location at a particular time, the drivers mealtimes and resting times can be all aligned with when the driver is at an optimal location for taking a meal break or a sleeping break. In other words, the route can be defined so that the driver is near a restaurant when it is time for a meal break or is near a location where it is permissible for the driver to stop the vehicle and sleep, such as at a site the permits drivers to sleep in the parking lot. Further, the route may be defined based on the condition of the vehicle. For example, if an in-vehicle device 105 indicates that the vehicle will need gas at a particular time or needs to stop for maintenance, the route can be calculated such that the vehicle is near a gas station or a repair station at a particular point in time.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg, Mathada, Hatakeyama and Vogel to incorporate the technique of selecting an optimal route that comprises a plurality of resting points that allow the driver to take a break, each of the plurality of resting points coincides with a respective time from among of the plurality of times and a respective place from among of the plurality of places where the future condition of the driver is predicted to exceed a predefined threshold as taught by Mason with reasonable expectation of success because selecting a route with plenty of rest stops allow drivers to take mandatory breaks and sleep and thus reducing the risk of drowsy driving because well-rested drivers a more alert which lead to fewer accidents.
Claim(s) 4-7 and 15-18 are rejected under 35 U.S.C. 103 as being unpatentable over Kronberg in view of Mathada, Hatakeyama and Mason.
Regarding claim 4 (similarly claim 15), the combination of Kronberg in view of Mathada and Hatakeyama teaches The method according to claim 1 (similarly claim 12),
Kronberg further teaches wherein the current condition comprises a current drowsiness level of the driver and the future condition comprises a future drowsiness level of the driver; (see at least Fig. 1- 5 [0019-0100]: The system calculates a prediction of the development of the level of alertness of the driver as a function of time beginning from the present time at t=0 and extending into the future on the basis of present level of driver alertness data (e.g. data related to driver’s physical or health condition like time of awakening, duration of sleep during the prior night(s), the sleep quality and any other vital contextual information recorded by a real-time driver state or drowsiness monitoring device ) and certain environment variables such as time of the day.)
The combination of Kronberg in view of Matha and Hatakeyama does not explicitly teach wherein the selecting the optimal route comprises: determining, based on the information associated with the driver and the information associated with the lifestyle of the driver, one or more resting points that allow the driver to take a break along each of the possible routes, wherein one or more resting points coincide with a time and a place where the future drowsiness level of the driver is predicted to exceed a predefined threshold; and
selecting, from among the plurality of possible routes, the route which has a highest number of resting point as the optimal route.
Mason is directed to route optimization for vehicle, Mason teaches wherein the selecting the optimal route comprises: determining, based on the information associated with the driver and the information associated with the lifestyle of the driver, one or more resting points that allow the driver to take a break along each of the possible routes, wherein one or more resting points coincide with a time and a place where the future drowsiness level of the driver is predicted to exceed a predefined threshold; and (see at least Fig. 4A-6 [0085-0112]: In addition, the route may be generated such that the driver is at a particular location when the route ends or when it is time for the driver to take a break. Advantageously, in certain embodiments, by defining the route so that the driver is at a particular location at a particular time, the drivers mealtimes and resting times can be all aligned with when the driver is at an optimal location for taking a meal break or a sleeping break. In other words, the route can be defined so that the driver is near a restaurant when it is time for a meal break or is near a location where it is permissible for the driver to stop the vehicle and sleep, such as at a site the permits drivers to sleep in the parking lot. Further, the route may be defined based on the condition of the vehicle. For example, if an in-vehicle device 105 indicates that the vehicle will need gas at a particular time or needs to stop for maintenance, the route can be calculated such that the vehicle is near a gas station or a repair station at a particular point in time.)
selecting, from among the plurality of possible routes, the route which has a highest number of resting point as the optimal route. (see at least Fig. 4A-6 [0085-0112]: In addition, the route may be generated such that the driver is at a particular location when the route ends or when it is time for the driver to take a break. Advantageously, in certain embodiments, by defining the route so that the driver is at a particular location at a particular time, the drivers mealtimes and resting times can be all aligned with when the driver is at an optimal location for taking a meal break or a sleeping break. In other words, the route can be defined so that the driver is near a restaurant when it is time for a meal break or is near a location where it is permissible for the driver to stop the vehicle and sleep, such as at a site the permits drivers to sleep in the parking lot. Further, the route may be defined based on the condition of the vehicle. For example, if an in-vehicle device 105 indicates that the vehicle will need gas at a particular time or needs to stop for maintenance, the route can be calculated such that the vehicle is near a gas station or a repair station at a particular point in time. The selecting multiple potential access paths and calculating multiple potential routes to determine the combination of access paths and routes that provide a lowest-cost solution)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg, Mathada and Hatakeyama to incorporate the technique of selecting an optimal route that comprises a plurality of resting points that allow the driver to take a break, each of the plurality of resting points coincides with a respective time from among of the plurality of times and a respective place from among of the plurality of places where the future condition of the driver is predicted to exceed a predefined threshold and selecting a route with the highest number of rest stops as taught by Mason with reasonable expectation of success because selecting a route with plenty of rest stops allow drivers to take mandatory breaks and sleep and thus reducing the risk of drowsy driving because well-rested drivers a more alert which lead to fewer accidents.
Regarding claim 5 (similarly claim 16), the combination of Kronberg in view of Mathada, Hatakeyama and Mason teaches The method according to claim 4 (similarly claim 15), wherein the selecting the optimal route further comprises:
the combination of Kronberg in view of Mathada and Hatakeyama does not explicitly teach based on determining that the plurality of possible routes have the same number of resting points, selecting the route which has a shortest distance to the target destination as the optimal route.
Mason is directed to route optimization for vehicle, Mason teaches based on determining that the plurality of possible routes have the same number of resting points, selecting the route which has a shortest distance to the target destination as the optimal route. (see at least Fig. 4A-6 [0006,0085-0112, 0159]: The selecting multiple potential access paths and calculating multiple potential routes to determine the combination of access paths and routes that provide a lowest-cost solution. In certain embodiments, multiple access paths exist between a gate of the site and at least one site location within the site. Further, multiple access paths may exist to or from at least one site location with the site. In addition, multiple access paths may exist to a gate of the site. In certain implementations, the lowest-cost solution includes a path configured to satisfy at least one of the following set of criteria: shortest route, fastest route, maximize use of highways, minimize use of highways, minimize toll roads, and maximize use of bonded roads.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg, Mathada and Hatakeyama to incorporate the technique of selecting the shortest path out of multiple potential access paths as taught by Mason with reasonable expectation of success because selecting a route with plenty of rest stops allow drivers to take mandatory breaks and sleep and thus reducing the risk of drowsy driving because well-rested drivers a more alert which lead to fewer accidents.
Regarding claim 6 (similarly claim 17), the combination of Kronberg in view of Mathada, Hatakeyama and Mason teaches The method according to claim 4 (similarly claim 15), wherein the selecting the optimal route further comprises:
the combination of Kronberg in view of Mathada and Hatakeyama does not explicitly teach based on determining that the plurality of possible routes have the same number of resting points, selecting the route which has a cheapest traveling cost as the optimal route.
Mason is directed to route optimization for vehicle, Mason teaches based on determining that the plurality of possible routes have the same number of resting points, selecting the route which has a cheapest traveling cost as the optimal route. (see at least Fig. 4A-6 [0006,0085-0112, 0159]: The selecting multiple potential access paths and calculating multiple potential routes to determine the combination of access paths and routes that provide a lowest-cost solution. In certain embodiments, multiple access paths exist between a gate of the site and at least one site location within the site. Further, multiple access paths may exist to or from at least one site location with the site. In addition, multiple access paths may exist to a gate of the site. In certain implementations, the lowest-cost solution includes a path configured to satisfy at least one of the following set of criteria: shortest route, fastest route, maximize use of highways, minimize use of highways, minimize toll roads, and maximize use of bonded roads.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg, Mathada and Hatakeyama to incorporate the technique of selecting the cheapest traveling cost route out of multiple potential access paths as taught by Mason with reasonable expectation of success because selecting a route with plenty of rest stops allow drivers to take mandatory breaks and sleep and thus reducing the risk of drowsy driving because well-rested drivers a more alert which lead to fewer accidents.
Regarding claim 7 (similarly claim 18), the combination of Kronberg in view of Mathada, Hatakeyama and Mason teaches The method according to claim 4 (similarly claim 15), wherein the selecting the optimal route further comprises:
the combination of Kronberg in view of Mathada and Hatakeyama does not explicitly teach based on determining that the plurality of possible routes have the same number of resting points, selecting the route which has a least congested traffic as the optimal route.
Mason is directed to route optimization for vehicle, Mason teaches based on determining that the plurality of possible routes have the same number of resting points, selecting the route which has a least congested traffic as the optimal route. (see at least Fig. 4A-6 [0006, 0075-0112, 0159]: The selecting multiple potential access paths and calculating multiple potential routes to determine the combination of access paths and routes that provide a lowest-cost solution. In some cases, the routes before or after the access path may be calculated using constraints such as least traffic. In certain embodiments, multiple access paths exist between a gate of the site and at least one site location within the site. Further, multiple access paths may exist to or from at least one site location with the site. In addition, multiple access paths may exist to a gate of the site. In certain implementations, the lowest-cost solution includes a path configured to satisfy at least one of the following set of criteria: shortest route, fastest route, maximize use of highways, minimize use of highways, minimize toll roads, and maximize use of bonded roads.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg, Mathada and Hatakeyama to incorporate the technique of selecting the least congested route out of multiple potential access paths as taught by Mason with reasonable expectation of success because selecting a route with plenty of rest stops allow drivers to take mandatory breaks and sleep and thus reducing the risk of drowsy driving because well-rested drivers a more alert which lead to fewer accidents.
Claim(s) 21 is rejected under 35 U.S.C. 103 as being unpatentable over Kronberg in view of Mathada, Hatakeyama and Shirakata (JP2009198217 A-English Translation).
Regarding claim 21, the combination of Kronberg in view of Mathada and Hatakeyama teaches The method according to claim 1,
the combination of Kronberg in view of Mathada and Hatakeyama further teaches determining a future condition of a driver but does not teach wherein the future condition of the driver comprises at least one of: a future eye dryness level, a future level of stiffness, a future level of inadequate vision, future urge to urinate, or future bowel movement.
Shirakata is directed to a breaking promoting device for providing breaking reminder to a vehicle driver, Shirakata teaches wherein the future condition of the driver comprises at least one of: a future eye dryness level, a future level of stiffness, a future level of inadequate vision, future urge to urinate, or future bowel movement. (see at least Fig. 1-5 [0005-0027]: This break facilitating equipment 10 has a map data storage part 12 which stores road network information provided with the information on a break location, a driver information storage part 13 which stores the information on the driver of the driver's own vehicle, a present location detecting part 21 which detects the present location of the driver's own vehicle, a navigation processing part 22 which acquires the break location at which the driver's own vehicle can arrive after a prescribed time passes, based on the present location of the driver's own vehicle, a needed drink quantity estimating part 24 which estimates the total quantity of drink needed for the driver to have a desire to urinate, based on the information on the driver, and a drink supply control part 25 and a drink supply device 16 which supply the driver of the driver's own vehicle with the estimated total quantity of the drink for a time to be taken to arrive at the break location from the present location.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Kronberg, Mathada and Hatakeyama to incorporate the technique of estimating a future driver condition of having desire to urinate based on the information on the driver and vehicle’s location as taught by Shirakata with reasonable expectation to prevent a driver continuing driver over a long period of time excessively by prompting a driver to take a break at appropriate time (Shirakata [0002]).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANA F ARTIMEZ whose telephone number is (571)272-3410. The examiner can normally be reached M-F: 9:00 am-3:30 pm EST.
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/DANA F ARTIMEZ/ Examiner, Art Unit 3667
/FARIS S ALMATRAHI/ Supervisory Patent Examiner, Art Unit 3667