DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 02/18/2025 has been entered.
Response to Amendment
The office action has been issued in response to amendment filed on 06/16/2025. Claims 1, 5, 11, 15, 19-20, and 23 are amended. Claims 2-4, 6, 12-14, and 21-22 are canceled. Claims 1, 5, 7-11, 15-20, and 23-29 are pending, rejected as detailed below.
Response to Arguments
Claim objections
Amendments of minor informalities in claims 1, 11, and 19 have been fully considered and are persuasive. Therefore, the claim objection has been withdrawn.
Prior art rejections
Applicant argues that the index reflection ratio in the invention of claim 1 is determined according to how much the user tolerates stress factors and is a value that is applied again to the calculated first stress index for each target route. Even if Chintakindi discloses that the road frustration index value may be customized for individuals, Chintakindi only discloses a concept similar to the first stress index of the present invention and does not suggest anything corresponding to the index reflection ratio.
More specifically, the road frustration index value in Chintakindi is a value that can be calculated for a route as a sum of the road frustration index values for the route segments comprising the total route (see, e.g., paragraph [0073] of Chintakindi). Similar to the invention if claim 1 in which the basic weight value may vary depending on the driver type and the first stress index for each target route is calculated by applying the varied basic weight value, Chintakindi discloses that the road frustration index value may vary depending on the driver. The reference, however, does not disclose or even suggest the concept of multiplying the calculated road frustration index value by a separate value for correction. That is, Chintakindi does not disclose the concept of a correction coefficient used to adjust a primary calculated stress index. Even the configuration in which the road frustration index value is customized for individuals merely suggests that the weighting factors used to calculate the road frustration index may differ by individual (see, e.g., paragraphs [0026] and [0031] of Chintakindi). Therefore, Chintakindi merely discloses that in the process of calculating the first stress index, the resulting value may vary depending on the driver type. In contrast, the invention of claims 1 discloses a two-stage index calculation method, which is a distinguishing feature, and has the effect of providing an improved route selection criterion that reflects the driver’s preferences and reduces driving stress through a separate correction step that takes into account individual driver tendencies.
Applicant’s arguments, with respect to the rejection(s) of claim(s) 1, 11, and 19 under 35 U.S.C. 103 have been fully considered and are not persuasive. More specifically, Chintakindi, disclose the concept of multiplying the calculated road frustration index value by a separate value for correction (Chintakindi 0033; “the road frustration index value may be combined with one or more other scores related to a risk that may be identified from the route, such as an objective risk score, a subjective risk score, etc.”). As stated, “combined with one or more other scores” can be seen as multiplication between the road frustration index and one or more other score. Furthermore, Chintakindi discloses that in the process of calculating the first stress index, the resulting value may vary not only depending on the driver type but also the experience level of each driver type (which is similar to an index reflection ratio) as stated in (Chintakindi 0027; “the mathematical algorithm customized for the first driver may predict that the first driver will experience lower frustration (e.g., a road frustration index value of 2, 3, etc.) based on expected rush hour traffic, while the mathematical algorithm customized for the second driver may predict that the second driver will experience a higher level of frustration with rush hour traffic along the same road segment. (e.g., a subjective risk score of 6, 7, etc.).”). Furthermore, Chintakindi also discloses how the mathematical algorithm can be executed with the driver profile so that the experience level can be accounted for each driver type or without the driver profile so that the experience level is not accounted for each driver type as stated in (Chintakindi 0027; “In some cases, the mathematical algorithm and/or the weighting factors used in the mathematical algorithm may be updated for the particular driver upon entry of new information in near real-time, at a defined interval, upon a driver profile update, when an application is started or stopped and/or the like. In some cases, the mathematical model may be substantially similar for all drivers, such as by using a mathematical model based on results of studies performed to measure actual frustration experienced on different road types as compared to a ratio of vehicle speed to the posted speed limit.”). As a result, driver type and the experience level of each driver type can be seen as the two-stage index calculation method of the instant application.
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.
Claim(s) 1, 5, 7-8, 11, 15-18, and 23-29 are rejected under 35 U.S.C. 103 as being unpatentable over Han (US20180080785A1), and further in view of Chintakindi (US 20220034678 A1) and Becker (US 20060129313 A1).
Regarding claim 1, Han teaches (Currently amended) A system for providing route guidance services (Han, at least one para. 0004; “An aspect of the disclosed embodiments is a method for selecting a navigation route for a vehicle.”), the system comprising:
a service providing server (Han, at least one para. 0018; “The remote computing system 142”) comprising a navigation module, a stress index calculating module, and an index reflection ratio applying module, the service providing server configured to:
receive a route guidance request from a user terminal (Han, at least one para. 0032; “based on an input received into a routing or navigation application associated with vehicle 120”);
derive a plurality of retrieved routes based on a departure point and a destination point (Han, at least one para. 0033; “In operation 404, candidate navigation routes extending between the current location and the destination location can be identified. The candidate navigation routes can include potentials paths of travel between the current location and the destination location.”);
predict a plurality of required times corresponding to the plurality of retrieved routes, respectively (Han, at least one para. 0033; “candidate navigation routes can include a variety of different types of navigation routes between the current location and the destination location such as a shortest route, a fastest route, a toll-free route, a highway-based route, etc”);
determine a target route of which a stress index is to be calculated among the plurality of retrieved routes (Han, at least one para. 0039; “The driver can also retain the ability to override an automated selection of the relaxed route by the controller apparatus 122 given personal preference at a given time while traveling the navigation route”, wherein the term “override” indicate that the driver is given multiple routes and ability to select a specific route from the multiple routes) considering the plurality of required times (Han, background; “Selection of the navigation route by the routing system can be based both on the input from the driver and a routing metric that gives weight to calculated and/or determined routing factors such as estimated time to traverse a route”) and (Han, at least one para. 0035; “calendar information associated with the driver of the vehicle 120 can indicate that the driver has a meeting in twenty minutes, construction information can indicate that the fastest route is currently blocked, and biometric information associated with the driver of the vehicle 120 can indicate that the driver has increased stress levels whenever she is late for a meeting”, wherein the terms “fastest” and “late” indicate that the target route is selected upon the consideration of time);
calculate a first stress index of the determined target route (Han, at least one para. 0037; “a weighted-sum cost function”) using information related to a plurality of stress factors (Han, at least one para. 0035; “Different types of passenger information can be used together with infrastructure information, construction information, and/or environment information as cognitive load component factors to determine the cognitive load parameter.”, wherein the cognitive load component factors are identified as the plurality of stress factors) and information related to a plurality of weight values (Han, at least one para. 0035; “The sensors 124 associated with the vehicle 120 can be used to collect biometric information based on situations where relaxation, happiness, irritation, or aggravation is present”, wherein the biometric information is identified as the plurality of weight values) corresponding to the plurality of stress factors, respectively, for the determined target route;
transmit information about target routes to the user terminal in response to the route guidance request (Han, at least one para. 0040; “In driver-based applications, the method 400 can further include the controller apparatus 122 sending a representation of the navigation route to support guidance along the navigation route to, for example, a display on a vehicle interface for viewing by the driver of the vehicle 120”);
wherein the navigation module is configured to retrieve the retrieved routes from the departure point to the destination point;
wherein the stress index calculating module is configured to:
check a driver type;
determine basic weight values of the respective stress factors for each of the target routes, the basic weight values being values given to the respective stress factors (Han, at least one para. 0020; “Each of the cognitive load component factors can be based on sensed or accessed information available to the vehicle 200. Each type of sensed or accessed information can be related to a score, for example, between zero and one, available in a lookup table or per a calculated function.”);
calculate a stress value of each of the stress factors (Han, at least one para. 0035; “Different types of passenger information can be used together with infrastructure information, construction information, and/or environment information as cognitive load component factors to determine the cognitive load parameter.”, wherein the cognitive load parameter is identified as the stress value) by multiplying the basic weight value for each of the stress factors (Han, at least one para. 0038; “Though a weighted-sum method is described here, other types of cost functions can be used to determine the cost values.”) by the number of times each of the stress factors is present (Han, at least one para. 0024; “Traffic information can also include density information related to traffic density (e.g., number of vehicles on the roadway 204), incident information related to traffic incidents (e.g. collisions, breakdowns, etc.), and speed information related to traffic speed.”, wherein a number of collisions and a number of breakdowns are seen as the total number of stress factors that are encountered within the route);
calculate indexes of the respective stress factors (Han, at least one para. 0037; “cost values”) by multiplying a special weight value (Han, at least one para. 0038; “w={w.sub.j|j=1, . . . , n} represents the set of weights applied to specific parameters in the cost function.”) and (Han, at least one para. 0038; various weights can be applied to the various parameters depending on the preferences of the driver of the vehicle 120 or the underlying construction of the routing metric) to the calculated stress values of the respective stress factors (Han, at least one para. 0038; “various weights can be applied to the various parameters depending on the preferences of the driver of the vehicle 120 or the underlying construction of the routing metric.”, wherein the various parameters refers to the cognitive load parameter that is represented as “C.sub.CLk” in the weighted-method cost function is ƒ.sub.k=w.sub.jC.sub.Dk+w.sub.jC.sub.Sk+w.sub.jC.sub.CLk), wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length;
calculate the first stress index for each of the target routes by adding up the calculated indexes of the respective stress factors (Han, at least one para. 0037; “One example weighted-method cost function is ƒ.sub.k = w.sub.jC.sub.Dk + w.sub.jC.sub.Sk + w.sub.jC.sub.CLk.”) and (Han, at least one para. 0037; “Though a weighted-sum method is described here, other types of cost functions can be used to determine the cost values” in other words the weighted-method cost function can be altered to accommodate multiple stress factors with respect to infrastructure information, construction information, and/or environment information);
wherein the index reflection ratio applying module is configured to calculate a second stress index of each of the target routes by multiplying an index reflection ratio to the calculated first stress index for each of the target routes; and
wherein the service providing server is configured to transmit information about each of the target routes including the second stress index to the user terminal.
Han does not explicitly teach, comprising a navigation module, a stress index calculating module, and an index reflection ratio applying module,
wherein the navigation module is configured to retrieve the retrieved routes from the departure point to the destination point;
wherein the stress index calculating module is configured to:
check a driver type;
wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length;
wherein the index reflection ratio applying module is configured to calculate a second stress index of each of the target routes by multiplying an index reflection ratio to the calculated first stress index for each of the target routes; and
wherein the service providing server is configured to transmit information about each of the target routes including the second stress index to the user terminal.
However, Chintakindi in the same field of endeavor (Chintakindi, at least one para. 0021; “Systems and methods in accordance with aspects of this disclosure may be provided to generate a road frustration index value corresponding to a level of frustration being experienced (or predicted to be experienced) by a driver along one or more road segments.”) teaches comprising a navigation module (Chintakindi, at least one para 0097; “the road frustration analysis engine 252”), a stress index calculating module, and an index reflection ratio applying module (Chintakindi, at least one para. 0065; “the frustration index analysis system 250 may be configured to identify a level of frustration being experienced by a user and/or predicted to be experience when traveling over one or more route segments for one or more users”, Furthermore, Chintakindi also shows that the frustration index analysis system 250 is within the remote computing system 240 in reference to FIG. 2.),
wherein the navigation module is configured to retrieve the retrieved routes (Chintakindi, at least one para 0127;” For ease of understanding, the segments in FIG. 6A were treated as segments of a road (e.g., road segments)”) from the departure point to the destination point (Chintakindi, at least one para 0128; “FIG. 6B illustrates an example composition of a segment. Each segment may have a starting point 602, a middle portion 603, and an ending point 604.”);
wherein the stress index calculating module is configured to (Chintakindi, at least one para. 0065; “the frustration index analysis system 250 may be configured to identify a level of frustration being experienced by a user and/or predicted to be experience when traveling over one or more route segments for one or more users”, Furthermore, Chintakindi also shows that the frustration index analysis system 250 is within the remote computing system 240 in reference to FIG. 2.):
check a driver type (Chintakindi, at least one para. 0026; “a personalized mathematical algorithm may be generated for each driver or group of drivers, e.g., student drivers, drivers within a specified age range, etc.”);
wherein the index reflection ratio applying module is configured to calculate a second stress index (Chintakindi, at least one para. 0026; “By using personalized algorithms, the same road segment may have a different road frustration index values based on the personalized weighting factors for each driver.”, wherein the term “road frustration index values” teaches the index reflection ratio) of each of the target routes by multiplying an index reflection ratio (Chintakindi, at least one para. 0026; “the road segment may be known to experience heavy traffic loading during particular times of day (e.g., rush hour, sporting event start or end times, etc.), where a first driver may be expecting heavier traffic, therefore an associated weighting factor may be used to provide a low weighting (e.g., 0.1, 0.2, etc.) at these times of day. However, a second person (e.g., an inexperienced driver) may have a greater sense of frustration when caught in rush hour traffic, so that the weighting factor may cause this traffic loading time to have an increased weight (e.g., 0.6, 0.7, etc.) in the calculation of the road frustration index.”) to the calculated first stress index for each of the target routes (Chintakindi, at least one para. 0033; “In some cases, the road frustration index value may be combined with one or more other scores related to a risk that may be identified from the route, such as an objective risk score, a subjective risk score, etc. The resulting combined risk score may be output by the computing device as an “overall” risk score.”, in other words, the road frustration index value can be combined with the calculated first stress index to attain the overall risk score); and
wherein the service providing server is configured to transmit information about each of the target routes including the second stress index to the user terminal (Chintakindi, at least one para. 0123; “The route frustration index risks described above may be variables in a multivariate model of insurance losses, frequencies, severities, and/or pure premiums. Interactions of the variables would also be considered. The coefficient the model produces for each variable (along with the coefficient for any interaction terms) would be the value to apply to each subjective risk type. The user device and/or the personal navigation device 110 may initially provide the quickest/shortest route from a start location A to an end location B, and then determine the route frustration index value by determining either the sum product of the number of each route frustration index parameters and the value for that route frustration index or the overall product of the number of each route frustration index and the value for that route frustration index. (Traffic and weather conditions could either be included or excluded from the determination of the route frustration index value for comparison of routes. If not included, an adjustment may be made to the route risk value once the route has been traveled). The driver may be presented with an alternate route which is less risky than the initial route calculated. The user device and/or the personal navigation device 110b may display the difference in route frustration between the alternate routes and permit the driver to select the preferred route. In some embodiments in accordance with this disclosure, a driver/vehicle may be provided a monetary benefit (e.g., a credit towards a future insurance policy) for selecting a route having lesser route frustration index values.”).
Han and Chintakindi are both considered to be analogous to the claimed invention because they are in the same field of vehicle navigation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the service provider of Han to incorporate the navigation module and the stress index calculating module of Chintakindi to calculate the stress value of each of the stress factors. One of ordinary skill in the art would have been obvious to a person of ordinary skill to applying a known multiplication technique that was ready for improvement, and the results would have been predictable.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the navigation route of Han to incorporate multiple routes between the departure points and the destination points of Chintakindi as multiple routes between the departure points and the destination points are seen as inherence features within a navigation route.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Han to incorporate the teachings of Chintakindi so that the stress index calculating module is able to check for different driver types. Doing so would allow the service providing server to accurately distinguish basic weight of the stress factors.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Han to incorporate the teachings of Chintakindi so that the stress index calculating module is able to apply different tolerance level for the first stress index to get the overall risk score thus providing an accurate prediction of how much risk may be caused due to a level of frustration being experienced along a particular road segment by a particular driver, or other drivers on the road at the same time (Chintakindi; 0028).
the combination of Han and Chintakindi does not explicitly teach, wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length;
However, Becker in the same field of endeavor (Becker, at least one para. 0014; “The following description details how the present invention is employed to calculate and convey map directions based on ambient and non-street-map factors, as well as optionally rewarding users for selecting and using certain routes.”) teaches wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length (Becker, at least one para. 0043; “Some users may employ the route provider to find the fastest route to a particular destination. For this objective, the route provider may check the number of traffic lights and duration of traffic light red signals along certain routes in order to suggest routes that avoid delays.”, wherein the number of traffic lights are identified as the stress factors and the duration of the red light signal is identified as the state of the stress factors with respect to the length);
Han, Chintakindi, and Becker are all considered to be analogous to the claimed invention because they are in the same field of vehicle navigation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the special weights of Han with the teaching of Becker to calculate the stress value of each of the stress factors so that fastest route can be accurately calculated (Becker; 0042).
Regarding claim 5, Chintakindi teaches (Currently amended) The system of claim 1,wherein, for each driver type, the stress factor having the highest value of the basic weight value is different (Chintakindi, at least one para. 0026; “an algorithm may include one or more weighting factors that may be adjusted based on characteristics of a particular driver or group. By using personalized algorithms, the same road segment may have a different road frustration index values based on the personalized weighting factors for each driver.”) and (Chintakindi, at least one para. 0026; “a first driver may be expecting heavier traffic, therefore an associated weighting factor may be used to provide a low weighting (e.g., 0.1, 0.2, etc.) at these times of day. However, a second person (e.g., an inexperienced driver) may have a greater sense of frustration when caught in rush hour traffic, so that the weighting factor may cause this traffic loading time to have an increased weight (e.g., 0.6, 0.7, etc.)”).
Regarding claim 7, Han teaches (Previously presented) The system of claim 1,wherein the basic weight value for each of the plurality of stress factors is determined based on weather information (Han, at least one para. 0027; “Environment information”), whether each of the plurality of stress factors is present or absent (Han, at least one para. 0027; “Environment information can also include weather information related to a presence of conditions such as rain, snow, sleet, ice, fog, glare from the sun, sulfurous odors, etc.”), the number of times each of the plurality of stress factors is present (Han, at least one para. 0024; “Traffic information can also include density information related to traffic density (e.g., number of vehicles on the roadway 204), incident information related to traffic incidents (e.g. collisions, breakdowns, etc.)”, wherein a number of collisions and a number of breakdowns are seen as the total number of stress factors that are encountered within the route), and whether each of the plurality of stress factors is consecutively present for each of the target routes (Han, at least one para. 0029; “various types of information be available at the same location at a common time can have a larger impact on the cognitive load parameter. In FIG. 3, for example, the roadway 304 curves around the tree group 308, blocking visibility of the construction-cone group 310 from the vehicle 300. In other words, the combination of scenic information and construction information available for this portion of the roadway 304 indicates a potentially greater increase in cognitive load than if each piece of information were considered individually”).
Regarding claim 8, Han teaches (Previously presented) The system of claim 7, wherein the weather information includes information about weather in a region on the target route, and the basic weight value for each of the stress factors is higher when the weather in the region on the target route is snowing or raining than when the weather in the region on the target route is sunny (Han, at least one para. 0026; “Some types of scenic information can indicate a decrease in cognitive load, for example, when the driver of the vehicle 300 indicates enjoyment in the presence of pleasant surroundings. Other types of scenic information can indicate an increase in cognitive load, for example, when the driver of the vehicle 300 suffers from motion sickness.”) and (Han, at least one para. 0027; “the presence of rain, snow, sleet, or fog will decrease visibility on the roadway 304”, it is understood and inherence that the sunny weather conditions decrease the cognitive load in comparison to the rain, snow, sleet, or fog that increases the cognitive load).
Regarding claim 11, Han teaches (Currently amended) A method for providing route guidance services (Han, at least one para. 0004; “An aspect of the disclosed embodiments is a method for selecting a navigation route for a vehicle.”), the method comprising:
receiving a route guidance request from a user terminal (Han, at least one para. 0032; “based on an input received into a routing or navigation application associated with vehicle 120”);
retrieving routes from a departure point to a destination point (Han, at least one para. 0033; “In operation 404, candidate navigation routes extending between the current location and the destination location can be identified. The candidate navigation routes can include potentials paths of travel between the current location and the destination location.”);
deriving a plurality of retrieved routes based on the departure point and the destination point (Han, at least one para. 0033; “In operation 404, candidate navigation routes extending between the current location and the destination location can be identified. The candidate navigation routes can include potentials paths of travel between the current location and the destination location.”);
predicting a plurality of required times corresponding to the plurality of retrieved routes, respectively (Han, at least one para. 0033; “candidate navigation routes can include a variety of different types of navigation routes between the current location and the destination location such as a shortest route, a fastest route, a toll-free route, a highway-based route, etc”);
determining one or more target routes for each of which a stress index is to be calculated among the plurality of retrieved routes (Han, at least one para. 0039; “The driver can also retain the ability to override an automated selection of the relaxed route by the controller apparatus 122 given personal preference at a given time while traveling the navigation route”, wherein the term “override” indicate that the driver is given multiple routes and ability to select a specific route from the multiple routes) considering the plurality of required times (Han, background; “Selection of the navigation route by the routing system can be based both on the input from the driver and a routing metric that gives weight to calculated and/or determined routing factors such as estimated time to traverse a route”) and (Han, at least one para. 0035; “calendar information associated with the driver of the vehicle 120 can indicate that the driver has a meeting in twenty minutes, construction information can indicate that the fastest route is currently blocked, and biometric information associated with the driver of the vehicle 120 can indicate that the driver has increased stress levels whenever she is late for a meeting”, wherein the terms “fastest” and “late” indicate that the target route is selected upon the consideration of time);
determining basic weight values of the respective stress factors for each of the target routes, the basic weight values being values given to the respective stress factors (Han, at least one para. 0020; “Each of the cognitive load component factors can be based on sensed or accessed information available to the vehicle 200. Each type of sensed or accessed information can be related to a score, for example, between zero and one, available in a lookup table or per a calculated function.”);
calculating stress values of the respective stress factors (Han, at least one para. 0035; “Different types of passenger information can be used together with infrastructure information, construction information, and/or environment information as cognitive load component factors to determine the cognitive load parameter.”, wherein the cognitive load parameter is identified as the stress value) by multiplying the basic weight value for each of the stress factors (Han, at least one para. 0038; “Though a weighted-sum method is described here, other types of cost functions can be used to determine the cost values.”) by the number of times each of the stress factors is present (Han, at least one para. 0024; “Traffic information can also include density information related to traffic density (e.g., number of vehicles on the roadway 204), incident information related to traffic incidents (e.g. collisions, breakdowns, etc.), and speed information related to traffic speed.”, wherein a number of collisions and a number of breakdowns are seen as the total number of stress factors that are encountered within the route);
calculating a first stress index of the determined target route (Han, at least one para. 0037; “a weighted-sum cost function”) using information on a plurality of stress factors (Han, at least one para. 0035; “Different types of passenger information can be used together with infrastructure information, construction information, and/or environment information as cognitive load component factors to determine the cognitive load parameter.”, wherein the cognitive load component factors are identified as the plurality of stress factors) and a plurality of weight values (Han, at least one para. 0035; “The sensors 124 associated with the vehicle 120 can be used to collect biometric information based on situations where relaxation, happiness, irritation, or aggravation is present”, wherein the biometric information is identified as the plurality of weight values) corresponding to the plurality of stress factors, respectively, for the determined target route, wherein the calculating of the first stress index comprises:
checking a driver type;
calculating indexes of the respective stress factors (Han, at least one para. 0037; “cost values”) by applying a special weight value (Han, at least one para. 0038; “w={w.sub.j|j=1, . . . , n} represents the set of weights applied to specific parameters in the cost function.”) and (Han, at least one para. 0038; various weights can be applied to the various parameters depending on the preferences of the driver of the vehicle 120 or the underlying construction of the routing metric) to the calculated stress values of the respective stress factors (Han, at least one para. 0038; “various weights can be applied to the various parameters depending on the preferences of the driver of the vehicle 120 or the underlying construction of the routing metric.”, wherein the various parameters refers to the cognitive load parameter that is represented as “C.sub.CLk” in the weighted-method cost function is ƒ.sub.k = w.sub.jC.sub.Dk + w.sub.jC.sub.Sk + w.sub.jC.sub.CLk), wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length;
calculating the first stress index for each of the target routes by adding up the calculated indexes of the respective stress factors (Han, at least one para. 0037; “One example weighted-method cost function is ƒ.sub.k = w.sub.jC.sub.Dk + w.sub.jC.sub.Sk + w.sub.jC.sub.CLk.”) and (Han, at least one para. 0037; “Though a weighted-sum method is described here, other types of cost functions can be used to determine the cost values” in other words the weighted-method cost function can be altered to accommodate multiple stress factors with respect to infrastructure information, construction information, and/or environment information);
calculating a second stress index of each of the target routes by multiplying an index reflection ratio to the calculated first stress index for each of the target routes, after the calculating of the first stress index; and
wherein the service providing server is configured to transmit information about each of the target routes including the second stress index to the user terminal.
Han does not explicitly teach, checking a driver type;
wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length;
calculating a second stress index of each of the target routes by multiplying an index reflection ratio to the calculated first stress index for each of the target routes, after the calculating of the first stress index; and
wherein the service providing server is configured to transmit information about each of the target routes including the second stress index to the user terminal.
However, Chintakindi in the same field of endeavor (Chintakindi, at least one para. 0021; “Systems and methods in accordance with aspects of this disclosure may be provided to generate a road frustration index value corresponding to a level of frustration being experienced (or predicted to be experienced) by a driver along one or more road segments.”) teaches checking a driver type (Chintakindi, at least one para. 0026; “a personalized mathematical algorithm may be generated for each driver or group of drivers, e.g., student drivers, drivers within a specified age range, etc.”);
calculating a second stress index of each of the target routes (Chintakindi, at least one para. 0026; “By using personalized algorithms, the same road segment may have a different road frustration index values based on the personalized weighting factors for each driver.”, wherein the term “road frustration index values” teaches the index reflection ratio) by multiplying an index reflection ratio (Chintakindi, at least one para. 0026; “the road segment may be known to experience heavy traffic loading during particular times of day (e.g., rush hour, sporting event start or end times, etc.), where a first driver may be expecting heavier traffic, therefore an associated weighting factor may be used to provide a low weighting (e.g., 0.1, 0.2, etc.) at these times of day. However, a second person (e.g., an inexperienced driver) may have a greater sense of frustration when caught in rush hour traffic, so that the weighting factor may cause this traffic loading time to have an increased weight (e.g., 0.6, 0.7, etc.) in the calculation of the road frustration index.”) to the calculated first stress index for each of the target routes, after the calculating of the first stress index (Chintakindi, at least one para. 0033; “In some cases, the road frustration index value may be combined with one or more other scores related to a risk that may be identified from the route, such as an objective risk score, a subjective risk score, etc. The resulting combined risk score may be output by the computing device as an “overall” risk score.”, in other words, the road frustration index value can be combined with the calculated first stress index to attain the overall risk score); and
wherein the service providing server is configured to transmit information about each of the target routes including the second stress index to the user terminal (Chintakindi, at least one para. 0123; “The route frustration index risks described above may be variables in a multivariate model of insurance losses, frequencies, severities, and/or pure premiums. Interactions of the variables would also be considered. The coefficient the model produces for each variable (along with the coefficient for any interaction terms) would be the value to apply to each subjective risk type. The user device and/or the personal navigation device 110 may initially provide the quickest/shortest route from a start location A to an end location B, and then determine the route frustration index value by determining either the sum product of the number of each route frustration index parameters and the value for that route frustration index or the overall product of the number of each route frustration index and the value for that route frustration index. (Traffic and weather conditions could either be included or excluded from the determination of the route frustration index value for comparison of routes. If not included, an adjustment may be made to the route risk value once the route has been traveled). The driver may be presented with an alternate route which is less risky than the initial route calculated. The user device and/or the personal navigation device 110b may display the difference in route frustration between the alternate routes and permit the driver to select the preferred route. In some embodiments in accordance with this disclosure, a driver/vehicle may be provided a monetary benefit (e.g., a credit towards a future insurance policy) for selecting a route having lesser route frustration index values.”).
Han and Chintakindi are both considered to be analogous to the claimed invention because they are in the same field of vehicle navigation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Han to incorporate the teachings of Chintakindi so that the stress index calculating module is able to check for different driver types. Doing so would allow the service providing server to accurately distinguish basic weight of the stress factors.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Han to incorporate the teachings of Chintakindi so that the stress index calculating module is able to apply different tolerance level for the first stress index to get the overall risk score thus providing an accurate prediction of how much risk may be caused due to a level of frustration being experienced along a particular road segment by a particular driver, or other drivers on the road at the same time (Chintakindi; 0028).
the combination of Han and Chintakindi does not explicitly teach, wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length;
However, Becker in the same field of endeavor (Becker, at least one para. 0014; “The following description details how the present invention is employed to calculate and convey map directions based on ambient and non-street-map factors, as well as optionally rewarding users for selecting and using certain routes.”) teaches wherein the special weight value is a value for reflecting a state of the stress factor including consecution or length (Becker, at least one para. 0043; “Some users may employ the route provider to find the fastest route to a particular destination. For this objective, the route provider may check the number of traffic lights and duration of traffic light red signals along certain routes in order to suggest routes that avoid delays.”, wherein the number of traffic lights are identified as the stress factors and the duration of the red light signal is identified as the state of the stress factors with respect to the length);
Han, Chintakindi, and Becker are all considered to be analogous to the claimed invention because they are in the same field of vehicle navigation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the special weights of Han with the teaching of Becker to calculate the stress value of each of the stress factors so that fastest route can be accurately calculated (Becker; 0042).
Regarding claim 15, Chintakindi teaches (Currently amended) The method of claim 11, wherein, for each driver type, the stress factor having the highest value of the basic weight value is different (Chintakindi, at least one para. 0026; “an algorithm may include one or more weighting factors that may be adjusted based on characteristics of a particular driver or group. By using personalized algorithms, the same road segment may have a different road frustration index values based on the personalized weighting factors for each driver.”) and (Chintakindi, at least one para. 0026; “a first driver may be expecting heavier traffic, therefore an associated weighting factor may be used to provide a low weighting (e.g., 0.1, 0.2, etc.) at these times of day. However, a second person (e.g., an inexperienced driver) may have a greater sense of frustration when caught in rush hour traffic, so that the weighting factor may cause this traffic loading time to have an increased weight (e.g., 0.6, 0.7, etc.)”).
Regarding claim 16, Han teaches (Previously presented) The method of claim 11, wherein in the calculating of the indexes of the respective stress factors, the index of each of the stress factors is calculated (Han, at least one para. 0037; “cost values”) by multiplying the calculated stress value for each of the stress factors (Han, at least one para. 0038; “various weights can be applied to the various parameters depending on the preferences of the driver of the vehicle 120 or the underlying construction of the routing metric.”, wherein the various parameters refers to the cognitive load parameter that is represented as “C.sub.CLk” in the weighted-method cost function is ƒ.sub.k = w.sub.jC.sub.Dk + w.sub.jC.sub.Sk + w.sub.jC.sub.CLk) by the special weight value (Han, at least one para. 0038; “w={w.sub.j|j=1, . . . , n} represents the set of weights applied to specific parameters in the cost function.”), the special weight value is a value for reflecting a state of the stress factor, and
the state of the stress factor includes at least one of whether the stress factor is consecutively present and a length of the stress factor (Han, at least one para. 0028; “Other types of construction information include a presence of construction zones, an absence of lane markings based on construction on the roadway 304, and a presence of temporary lanes shifts during construction, each of which can increase cognitive load for a given portion of the navigation route 302.” wherein the term “given portion” indicates a specific length of stress factors) and (Han, at least one para. 0029; “the combination of scenic information and construction information available for this portion of the roadway 304 indicates a potentially greater increase in cognitive load than if each piece of information were considered individually.”, wherein combination of scenic and construction indicate consecution of the stress factors).
Han does not explicitly teach, the special weight value is a value for reflecting a state of the stress factor, and
However, Becker in the same field of endeavor (Becker, at least one para. 0014; “The following description details how the present invention is employed to calculate and convey map directions based on ambient and non-street-map factors, as well as optionally rewarding users for selecting and using certain routes.”) teaches the special weight value is a value for reflecting a state of the stress factor (Becker, at least one para. 0043; “Some users may employ the route provider to find the fastest route to a particular destination. For this objective, the route provider may check the number of traffic lights and duration of traffic light red signals along certain routes in order to suggest routes that avoid delays.”, wherein the number of traffic lights are identified as the stress factors and the duration of the red light signal is identified as the state of the stress factors with respect to the length), and
Han and Becker are both considered to be analogous to the claimed invention because they are in the same field of vehicle navigation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the special weights of Han with the teaching of Becker to calculate the stress value of each of the stress factors so that fastest route can be accurately calculated (Becker; 0042).
Regarding claim 17, Han teaches (Previously presented) The method of claim 11, wherein the basic weight value for each of the stress factors is determined based on weather information (Han, at least one para. 0027; “Environment information”), whether each of the stress factors is present or absent (Han, at least one para. 0027; “Environment information can also include weather information related to a presence of conditions such as rain, snow, sleet, ice, fog, glare from the sun, sulfurous odors, etc.”), the number of times each of the stress factors is present (Han, at least one para. 0024; “Traffic information can also include density information related to traffic density (e.g., number of vehicles on the roadway 204), incident information related to traffic incidents (e.g. collisions, breakdowns, etc.)”, wherein a number of collisions and a number of breakdowns are seen as the total number of stress factors that are encountered within the route), and whether each of the stress factors is consecutive