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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 03/26/2025 has been entered.
Status of Claims
This action is in reply to the amendments filed on 03/26/2025.
Claims 1-7 and 9-21 are currently pending and have been examined.
Claims 1-6, 9-13, 15-16, and 18 have been amended.
Claims 1-7 and 9-21 are currently rejected.
This action is made NON-FINAL.
Response to Arguments
Applicant’s arguments filed 03/26/2025 have been fully considered but they are not fully persuasive.
Regarding the 101 rejection, applicants arguments are not persuasive. Applicant argues that the claims provide meaningful limits on the abstract idea and is tied to a particular machine. In the claims, the servers and vehicle computers are performing the mental process in lieu of a person from gathered data and is not tying the determinations to a specific machine and is only reciting generic computer hardware to perform the mental processes. Therefore the 101 rejections are being maintained below.
Applicant’s arguments with regards to the art rejections have been considered and appear to be directed solely to the instant amendments to the claims. Accordingly, the claims are addressed in the body of the rejections below.
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.
Claims 1-7 and 9-21are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-7 and 9-21 are directed to a system, method, or product, which are/is one of the statutory categories of invention. (Step 1: YES)
The examiner has identified independent system/method/product Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent Claim 6 and Claim 13. Claim 1 recites the limitations of:
determining vehicle degradation values for the available vehicle
selecting a first vehicle over one or more other vehicles
determining, with the server, an updated vehicle degradation value for the first vehicle based on the updated set of vehicle sensor measurements received after providing the destination to the application of the first vehicle;
re-assigning, with the server, the task to a second vehicle by providing, with the server, the destination of the preliminary navigation path to the second vehicle based on the result, wherein a second onboard computing device of the second vehicle generates a second navigation path from a current location of the second vehicle to the destination.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as mental processes. Determining values and selecting something based off calculated values recites concepts performed in the human mind. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a concept performed in the human mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. The servers and vehicles in Claim 1 is just applying generic computer components to the recited abstract limitations. The recitation of generic computer components in a claim does not necessarily preclude that claim from reciting an abstract idea. Claims 6 and 13 are also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims recite an abstract idea.)
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of: obtaining vehicle sensor measurements of a plurality of vehicles, obtaining a set of vehicle utilization parameters, and wirelessly providing a destination of the navigation path to an application of the first vehicle. These steps are insignificant pre- and post- solution activity that do not incorporate the mental process into a practical application. Therefore, claims 1, 6, and 13 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application.)
The claims do not include additional elements that are sufficient to amount to significantly more that the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. In the instant application, the vehicles, sensors, and computers/servers. Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Thus, claims 1, 6, and 13 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more.)
Dependent claims further define the abstract idea that is present in their respective independent claims 1, 6, and 13 and thus correspond to Mental Processes and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, the claims 1-7 and 9-21 are not patent-eligible.
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, 6, 9, and 13-14is/are rejected under 35 U.S.C. 103 as being unpatentable over Morizumi et. al. (US 2022/0005609), herein Morizumi in view of Liu et. al. (US 2021/0215491), herein Liu and Rakah et. al. (US 2018/0211541), herein Rakah.
Regarding claim 1:
Morizumi teaches:
A method (method for managing shared vehicle [0001]) for selecting a vehicle (assigns the available vehicle to the reservation [0025]) based on utilization parameters (the processor 52 changes the status information of the vehicle A from “In use” to “Unavailable”, which will prohibit any future reservations from being assigned to the vehicle A [0146]) for fulfilling a destination-related task (a vehicle rental service and a car sharing service [0003]) comprising:
vehicle degradation values for a plurality of vehicles (the external server 50 may accumulate the data from the vehicles over the time and monitor a clue of the outbreak of the respiratory disease and/or allergy [0124]) based on (i) a set of vehicle utilization parameters (assessing the respiratory disease symptom of the passenger to generate infection risk information associated with an infection risk of a next passenger expected to ride the vehicle [0013])
determining an updated vehicle degradation value for the first vehicle based on the an updated set of vehicle sensor measurements (the processor 32 generates infection risk information based on the severity of the symptom. In addition or as an alternative, contamination information of the vehicle compartment 24 may be generated. The concentration of aerosols (i.e., the level of contamination) in the compartment 24 of the vehicle 20 depends on not only the frequency of respiratory disease symptoms but also the size or capacity of the compartment 24 of the vehicle 20 as well as the duration of the symptoms. Therefore, the vehicle compartment contamination information should be determined with considering these factors as well. That is, the infection risk information indicates a likelihood (risk) of an infection of a next passenger expected to ride the vehicle, while the vehicle compartment contamination information indicates a necessity of a disinfectant procedure after the vehicle is returned and prior to a next use of the vehicle. [0113]; updating the vehicle compartment contamination information after the disinfectant procedure is completed so as to indicate that the vehicle is clean [0036]);
sending, to the server (the external server 50 utilizes the information to manage an entire fleet schedule [0144]), an indication that the updated vehicle degradation value satisfies a vehicle degradation threshold (The risk degree may be defined in association with the likelihood (risk) of an infection of a next user expected to use the seat. For example, less than 1% may be defined as “low”, 1% or more and less than 20% may be defined as “middle”, and more than 20% may be defined as “high”. The risk degree may also be defined in association with the necessity of a disinfectant procedure prior to a next use of the seat. [0141]); and
re-selecting, with the server, a second vehicle for the task (Since the vehicle A needs to be disinfected prior to the next use and will be unavailable until the disinfectant procedure is completed, this reservation must be changed. Thus, the processor 52 searches an available vehicle in this time slot from the fleet schedule. As the vehicle B is available in this time slot, the processor 52 reassigns the reservation to the vehicle B and move the reservation information from the vehicle A to the vehicle B (S230) [0146])
Liu also teaches:
A method for selecting a vehicle (method for vehicle sharing include a vehicle having sensors [abstract]) based on utilization parameters (parameter values 830 based on sensor signals 812 [0060]) for fulfilling a destination-related task (vehicle sharing arrangements for purchase, lease, or ride sharing of a single vehicle or a group of shared vehicles [0002]) comprising:
vehicle degradation values for a plurality of vehicles (Due to the concern of vehicle maintenance, repairs, depreciation, insurance, and other costs, many vehicle owners hesitate to share their vehicles creating an obstacle to owner acceptance of new vehicle sharing ownership models or car sharing models. While the cost of “wear and tear” on a vehicle may be partially covered by a depreciation or mileage allocation, some types of “wear and tear” associated with a particular user or use may be very difficult to detect and allocate costs accordingly [0021]) based on (i) a set of vehicle utilization parameters (As previously described, some components may have wear and tear monitored based on odometer distance, time, speed or a combination of the two. Some components may function normally, then fail suddenly such as an engine low on oil, while other components wear gradually and predictably, such as tire treads. The wear and tear models used to determine vehicle sharing cost may be adjusted accordingly based on the type of component and types of wear associated with particular vehicle operation. [0064])
Morizumi does not explicitly teach, however Liu teaches:
comprising a preliminary navigation path (processor 106 may perform various calculations associated with determining real-time costs of vehicle wear and tear and display the costs to the user and/or communicate with a cloud-based network to provide data and receive costs associated with vehicle maintenance allocated to a particular use, user, route, weather, road condition etc. [0025]) and, (ii) vehicle sensor measurements indicating odometer measurements of the available plurality of vehicles (The instrument panel adds the wheel rotations to calculate the odometer measurement. The odometer value may be used for component wear estimates that are based on distance driven. [0046]);
providing, with the server, a destination of the preliminary navigation path (Vehicle sharing cost may be determined for a vehicle use, driver, route, road conditions, parking behavior, weather, etc. based on data from vehicle sensors and external sensors to detect ambient and operating conditions. [abstract]; The direction of the sun with respect to the vehicle can be determined by the navigation system from the bearing of the vehicle, longitude, latitude, date and time it receives from the global positioning system using a well-known equation [0079])
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Morizumi to include the teachings as taught by Liu with a reasonable expectation of success. Liu teaches the benefits of “a vehicle sharing method or system includes sensors and a processor programmed to receive sensor data associated with operation of a vehicle by a vehicle sharing user during a trip and calculate a vehicle sharing cost associated with anticipated maintenance of a vehicle component based on the sensor data from the trip, historical information and customer characteristics (e.g. repeated ride-sharing customers, or the years of owning a vehicle). The processor may be further programmed to communicate the vehicle sharing cost for display on a vehicle HMI. The sensor may be embedded within the vehicle, and the processor may receive data from external sensors to detect or determine a particular vehicle use, route, driver behavior, and the like. The processor may be programmed to calculate the vehicle sharing cost by comparing the sensor data to previously stored expected values in a vehicle component wear model, and to determine a route for the trip based on the sensor data from the trip. The vehicle sharing cost may be determined based on historical sensor data associated with the route for the trip. The vehicle sharing cost may be also determined based on historical driving behaviors and customers' characteristics. [Liu, 0003]”. The methods of calculating use cost/depreciation of Liu can be applied to the vehicle tasks as performed by the teachings of Lodhia to provide better cost calculations based on the details of the vehicle use.
Morizumi in view of Liu does not explicitly teach, however Rakah teaches:
providing, with the server, a destination of the preliminary navigation path to an application of a first client device by selecting a first vehicle for a task over one or more other vehicles of the plurality of vehicles based on a first vehicle degradation value for the first vehicle (At step 1111, server 150 may assign a first ridesharing vehicle to pick-up a first group of the plurality of users. For example, the first group may include a first user, a second user, a third user, etc. Some users may be included in the same request (e.g., if a first user and a second user are included in a first request). As explained above with regards to assignment module 920, server 150 may assemble the first group of the plurality of users based on the closeness of starting points of the assembled users, the closeness of the desired destinations of the assembled users, the closeness of the starting points of some of the first group to desired destinations of others of the first group, overlap between predicted routes from the starting points to the desired destinations of some of first group and predicted routes from the starting points to the desired destinations of others of the first group, or the like. [0239]), wherein the first client device performs operations (at least some of the steps of process 400 may be performed by a mobile communications device [0114]) comprising:
re-selecting, with the server, a second vehicle for the task (At step 1125, server 150 may re-assign the first user to the second ridesharing vehicle [0248]) by (l) receiving the indication from the first client device (when the predicted passing time is after the predicted arrival time. Optionally, server 150 may re-assign the first user only when the predicted passing time is within one or more thresholds after the predicted arrival time. For example, server 150 may re-assign the first user if the predicted passing time is less than 5 minutes, 10 minutes, etc. after the predicted arrival time and/or may re-assign the first user if the predicted passing time is more than 1 minute, 2 minutes, etc. after the predicted arrival time. [0248]) and (2) providing, with the server, the destination of the preliminary navigation path to the second vehicle based on the indication (In some embodiments, server 150 may guide the second ridesharing vehicle to the first pick-up location. For example, as explained above with respect to location module 910, server 150 may send a location (e.g., UPS coordinates) and/or an address of the first pick-up location to a second communications device associated with the second ridesharing vehicle and/or send driving directions to the first pick-up location to the second communications device. [0248]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Morizumi in view of Liu to include the teachings as taught by Rakah with a reasonable expectation of success. Rakah teaches the benefits of “software instructions for routing a ridesharing vehicle to pick up and/or transport one or more users. For example, in response to the ride requests received by input data collection module 1801 from the plurality of users headed to differing destinations, vehicle routing module 1803 may send the ridesharing vehicle to pick up the plurality of users headed to the different destinations. That is, vehicle routing module 1803 may direct the ridesharing vehicle along one or more routes through the surrounding environment based on the current state of one or more variables. Further, the route to which the ridesharing vehicle is assigned may be dynamically adjusted during transportation of the plurality of users to redirect the ridesharing vehicle to optimize one or more performance variables. [Rakah, 0366]”.
Regarding claim 2:
Morizumi in view of Liu and Rakah teaches all the limitations of claim 1, upon which this claim is dependent.
Morizumi further teaches:
and wherein a set of vehicle degradation values comprises the first vehicle degradation value and is associated with the first vehicle (At the step S140, the processor 32 generates infection risk information based on the severity of the symptom. In addition or as an alternative, contamination information of the vehicle compartment 24 may be generated. The concentration of aerosols (i.e., the level of contamination) in the compartment 24 of the vehicle 20 depends on not only the frequency of respiratory disease symptoms but also the size or capacity of the compartment 24 of the vehicle 20 as well as the duration of the symptoms [0113]), the method further comprising:
Rakah further teaches:
predicting a time point for when the set of vehicle degradation values satisfies a threshold based on a subset of records sharing a vehicle category of the second vehicle (send data to the group of the plurality of users indicating appointed pick-up times at the determined pick-up locations; use information received from at least one of the plurality of ridesharing vehicles to predict when the first ridesharing vehicle will arrive to a first pick-up location assigned to a first user; prior to a first pick-up time associated with the first user, estimate that the first ridesharing vehicle is going to be late to the first pick-up location by more than a time threshold; identify a second ridesharing vehicle to be assigned to pick-up the first user; cancel the assignment of the first ridesharing vehicle to the first user while maintaining the assignment of the first ridesharing vehicle to others of the group of the plurality of users; and assign the second ridesharing vehicle to pick up the first user. [0009]);
in response to a determination that the set of vehicle degradation values satisfies the threshold, updating the set of vehicle degradation values based on an additional navigation path (ridesharing management server 150 may decline to re-assign the second ridesharing vehicle even if the updated total waiting time is less than the initial total waiting time. For example, one or more thresholds (e.g., 10 minutes, 15 minutes, or the like) may be applied to a predicted waiting time for an individual user. In this example, ridesharing management server 150 may decline to re-assign the second ridesharing vehicle if the re-assignment would result in a predicted waiting time for a user exceeding the threshold. Accordingly, inconveniences to individual users may be capped in order to encourage such users to become repeat riders and enjoy the advantages of fleet-wide optimization on one or more future trips. [0234]);
selecting a third vehicle based on the set of vehicle degradation values after the updating of the set of vehicle degradation values (comparing the predicted passing time of the second ridesharing vehicle with the arrival time of the first user; and re-assigning the first user to the second ridesharing vehicle when the predicted passing time is after the predicted arrival time [0008]); and
wirelessly providing a destination of the additional navigation path to the third vehicle (ridesharing management server 150 may include software that, when executed by a processor, provides communications with network 140 through communications interface 360 to one or more mobile communications devices 120A-F. In some embodiments, transmission module 2110 may further send to the user, via the communications interface, information that causes a display of walking directions from a starting point to a pick-up location and from a drop-off location to a desired destination. Transmission module 2110 may further send (e.g., via a communications interface) messages to the passengers of a ridesharing vehicle when a route other than the reduced-backtracking route has been selected. [0398]).
Regarding claim 6:
Morizumi teaches:
One or more tangible, non-transitory, machine-readable media storing instructions that, when executed by one or more processors (the memory 42 may store a system program [0095]), effectuating operations comprising:
determining a plurality of values associated with a plurality of vehicles (assigns the available vehicle to the reservation [0025]) based on a set of vehicle utilization parameters (the processor 52 changes the status information of the vehicle A from “In use” to “Unavailable”, which will prohibit any future reservations from being assigned to the vehicle A [0146]) for fulfilling a destination-related task (a vehicle rental service and a car sharing service [0003]) comprising:
vehicle degradation values for a plurality of vehicles (the external server 50 may accumulate the data from the vehicles over the time and monitor a clue of the outbreak of the respiratory disease and/or allergy [0124]) based on a set of vehicle utilization parameters (assessing the respiratory disease symptom of the passenger to generate infection risk information associated with an infection risk of a next passenger expected to ride the vehicle [0013])
determining an updated vehicle degradation value for the first vehicle based on the an updated set of vehicle sensor measurements (the processor 32 generates infection risk information based on the severity of the symptom. In addition or as an alternative, contamination information of the vehicle compartment 24 may be generated. The concentration of aerosols (i.e., the level of contamination) in the compartment 24 of the vehicle 20 depends on not only the frequency of respiratory disease symptoms but also the size or capacity of the compartment 24 of the vehicle 20 as well as the duration of the symptoms. Therefore, the vehicle compartment contamination information should be determined with considering these factors as well. That is, the infection risk information indicates a likelihood (risk) of an infection of a next passenger expected to ride the vehicle, while the vehicle compartment contamination information indicates a necessity of a disinfectant procedure after the vehicle is returned and prior to a next use of the vehicle. [0113]; updating the vehicle compartment contamination information after the disinfectant procedure is completed so as to indicate that the vehicle is clean [0036]);
sending an indication that the updated vehicle degradation value satisfies a vehicle degradation threshold (The risk degree may be defined in association with the likelihood (risk) of an infection of a next user expected to use the seat. For example, less than 1% may be defined as “low”, 1% or more and less than 20% may be defined as “middle”, and more than 20% may be defined as “high”. The risk degree may also be defined in association with the necessity of a disinfectant procedure prior to a next use of the seat. [0141]); and
re-selecting a second vehicle for the task (Since the vehicle A needs to be disinfected prior to the next use and will be unavailable until the disinfectant procedure is completed, this reservation must be changed. Thus, the processor 52 searches an available vehicle in this time slot from the fleet schedule. As the vehicle B is available in this time slot, the processor 52 reassigns the reservation to the vehicle B and move the reservation information from the vehicle A to the vehicle B (S230) [0146])
Liu also teaches:
vehicle degradation values for a plurality of vehicles (Due to the concern of vehicle maintenance, repairs, depreciation, insurance, and other costs, many vehicle owners hesitate to share their vehicles creating an obstacle to owner acceptance of new vehicle sharing ownership models or car sharing models. While the cost of “wear and tear” on a vehicle may be partially covered by a depreciation or mileage allocation, some types of “wear and tear” associated with a particular user or use may be very difficult to detect and allocate costs accordingly [0021]) based on a set of vehicle utilization parameters (As previously described, some components may have wear and tear monitored based on odometer distance, time, speed or a combination of the two. Some components may function normally, then fail suddenly such as an engine low on oil, while other components wear gradually and predictably, such as tire treads. The wear and tear models used to determine vehicle sharing cost may be adjusted accordingly based on the type of component and types of wear associated with particular vehicle operation. [0064])
Morizumi does not explicitly teach, however Liu teaches:
comprising a preliminary navigation path (processor 106 may perform various calculations associated with determining real-time costs of vehicle wear and tear and display the costs to the user and/or communicate with a cloud-based network to provide data and receive costs associated with vehicle maintenance allocated to a particular use, user, route, weather, road condition etc. [0025]) and a vehicle sensor measurements indicating odometer measurements of the available plurality of vehicles (The instrument panel adds the wheel rotations to calculate the odometer measurement. The odometer value may be used for component wear estimates that are based on distance driven. [0046]);
providing a destination of the preliminary navigation path (Vehicle sharing cost may be determined for a vehicle use, driver, route, road conditions, parking behavior, weather, etc. based on data from vehicle sensors and external sensors to detect ambient and operating conditions. [abstract]; The direction of the sun with respect to the vehicle can be determined by the navigation system from the bearing of the vehicle, longitude, latitude, date and time it receives from the global positioning system using a well-known equation [0079])
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Morizumi to include the teachings as taught by Liu with a reasonable expectation of success. Liu teaches the benefits of “a vehicle sharing method or system includes sensors and a processor programmed to receive sensor data associated with operation of a vehicle by a vehicle sharing user during a trip and calculate a vehicle sharing cost associated with anticipated maintenance of a vehicle component based on the sensor data from the trip, historical information and customer characteristics (e.g. repeated ride-sharing customers, or the years of owning a vehicle). The processor may be further programmed to communicate the vehicle sharing cost for display on a vehicle HMI. The sensor may be embedded within the vehicle, and the processor may receive data from external sensors to detect or determine a particular vehicle use, route, driver behavior, and the like. The processor may be programmed to calculate the vehicle sharing cost by comparing the sensor data to previously stored expected values in a vehicle component wear model, and to determine a route for the trip based on the sensor data from the trip. The vehicle sharing cost may be determined based on historical sensor data associated with the route for the trip. The vehicle sharing cost may be also determined based on historical driving behaviors and customers' characteristics. [Liu, 0003]”. The methods of calculating use cost/depreciation of Liu can be applied to the vehicle tasks as performed by the teachings of Lodhia to provide better cost calculations based on the details of the vehicle use.
Morizumi in view of Liu does not explicitly teach, however Rakah teaches:
providing a destination of the preliminary navigation path to an application of a first client device by selecting a first vehicle for a task over one or more other vehicles of the plurality of vehicles based on a first vehicle degradation value for the first vehicle (At step 1111, server 150 may assign a first ridesharing vehicle to pick-up a first group of the plurality of users. For example, the first group may include a first user, a second user, a third user, etc. Some users may be included in the same request (e.g., if a first user and a second user are included in a first request). As explained above with regards to assignment module 920, server 150 may assemble the first group of the plurality of users based on the closeness of starting points of the assembled users, the closeness of the desired destinations of the assembled users, the closeness of the starting points of some of the first group to desired destinations of others of the first group, overlap between predicted routes from the starting points to the desired destinations of some of first group and predicted routes from the starting points to the desired destinations of others of the first group, or the like. [0239]), wherein the first client device performs operations (at least some of the steps of process 400 may be performed by a mobile communications device [0114]) comprising:
re-selecting a second vehicle for the task (At step 1125, server 150 may re-assign the first user to the second ridesharing vehicle [0248]) by (1) receiving the indication from the first client device (when the predicted passing time is after the predicted arrival time. Optionally, server 150 may re-assign the first user only when the predicted passing time is within one or more thresholds after the predicted arrival time. For example, server 150 may re-assign the first user if the predicted passing time is less than 5 minutes, 10 minutes, etc. after the predicted arrival time and/or may re-assign the first user if the predicted passing time is more than 1 minute, 2 minutes, etc. after the predicted arrival time. [0248]) and (2) providing, with the server, the destination of the preliminary navigation path to the second vehicle based on the indication (In some embodiments, server 150 may guide the second ridesharing vehicle to the first pick-up location. For example, as explained above with respect to location module 910, server 150 may send a location (e.g., UPS coordinates) and/or an address of the first pick-up location to a second communications device associated with the second ridesharing vehicle and/or send driving directions to the first pick-up location to the second communications device. [0248]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Morizumi in view of Liu to include the teachings as taught by Rakah with a reasonable expectation of success. Rakah teaches the benefits of “software instructions for routing a ridesharing vehicle to pick up and/or transport one or more users. For example, in response to the ride requests received by input data collection module 1801 from the plurality of users headed to differing destinations, vehicle routing module 1803 may send the ridesharing vehicle to pick up the plurality of users headed to the different destinations. That is, vehicle routing module 1803 may direct the ridesharing vehicle along one or more routes through the surrounding environment based on the current state of one or more variables. Further, the route to which the ridesharing vehicle is assigned may be dynamically adjusted during transportation of the plurality of users to redirect the ridesharing vehicle to optimize one or more performance variables. [Rakah, 0366]”.
Regarding claim 9:
Morizumi in view of Liu and Rakah teaches all the limitations of claim 6, upon which this claim is dependent.
Liu further teaches:
obtaining a plurality of time series (processor 106 may perform various calculations associated with determining real-time costs of vehicle wear and tear and display the costs to the user and/or communicate with a cloud-based network to provide data and receive costs associated with vehicle maintenance allocated to a particular use, user, route, weather, road condition etc. [0025]), wherein each time series of the plurality of time series is associated with a respective vehicle of the plurality of vehicles (Accurate analysis and assessment of vehicle maintenance and repair costs may encourage more vehicle owners to participate in vehicle sharing programs and more accurately allocate costs to the users in proportion to actual uses of the vehicle. As described in greater detail herein, vehicle sharing prices or charges may be based on real-time driving behaviors, routes driven, road/parking conditions, etc. [0023]);
determining a vehicle status of the first vehicle based on a time series of the plurality of time series (The detection corridor or contour may be determined based on a statistical probability that the data excursion corresponds or is likely to correlate with a particular condition or component failure that requires maintenance or repair. [0087]), wherein the time series is associated with the first vehicle (Model builders 370 may use the data from vehicle sensors/computers 320 to build and calibrate maintenance models and associated pricing models based on the sensor data. Insurers 372 receive data reflecting actual use of vehicles that may be used to determine the current status/condition of insured vehicles, and for pricing of policies based on actual vehicle uses. [0042]);
sending the vehicle status to the first vehicle (A GPS clock determines when and where a braking event occurs based on notification 834. ECU module 814 may store the ambient temperature, barometric pressure, humidity, rain, and similar information received over vehicle network 862 and associated with a particular braking event. The antilock braking system 810 reports when ABS control is triggered indicating a low traction or hard braking event. Wheel height or suspension sensors may also provide date to determine the vehicle weight and weight shift during braking. A brake performance model can then use the data collected by the vehicle sensors to estimate the amount of brake pad and rotor (or drum and lining for drum brakes) wear for each braking event. The events may be logged by the VCS and the wear of brake components estimated with a corresponding price determined for the particular vehicle use or trip. [0063]), wherein a vehicle computer system performs operations comprising:
providing the vehicle status and a set of vehicle sensor measurements to a machine learning model to obtain an output (Based on collected characteristics of events, a machine learning method, such as a support vector machine may be used to classify the events according to: [0048]);
determining whether the output satisfies a threshold (A detection corridor may be defined by a lower threshold 1064 and an upper threshold 1066 with a trigger or flag set when the vehicle data is outside of the corridor, beginning at 1070, for example. [0087]); and
displaying a notification on a visual display of the first vehicle in response to a determination that the output satisfies the threshold (The sensor or the models may also trigger an alert that is sent to the lenders to perform some maintenance work related to specific or accumulated wear and tear. One or more extended service plans may also be priced accordingly and offered or recommended to the vehicle owner/lender. [0047]).
Regarding claim 13:
Morizumi teaches:
A system (shared vehicles managing system 10 [0096]) comprising:
one or more processors (processor 32 [0095]); and
memory storing computer program instructions that, when executed by the one or more processors (the memory 42 may store a system program [0095]), cause the one or more processors to effectuate operations comprising:
determining a plurality of values associated with a plurality of vehicles (assigns the available vehicle to the reservation [0025]) based on a set of vehicle utilization parameters (the processor 52 changes the status information of the vehicle A from “In use” to “Unavailable”, which will prohibit any future reservations from being assigned to the vehicle A [0146]) for fulfilling a destination-related task (a vehicle rental service and a car sharing service [0003]) comprising:
vehicle degradation values for a plurality of vehicles (the external server 50 may accumulate the data from the vehicles over the time and monitor a clue of the outbreak of the respiratory disease and/or allergy [0124]) based on a set of vehicle utilization parameters (assessing the respiratory disease symptom of the passenger to generate infection risk information associated with an infection risk of a next passenger expected to ride the vehicle [0013])
determining an updated vehicle degradation value for the first vehicle based on the an updated set of vehicle sensor measurements (the processor 32 generates infection risk information based on the severity of the symptom. In addition or as an alternative, contamination information of the vehicle compartment 24 may be generated. The concentration of aerosols (i.e., the level of contamination) in the compartment 24 of the vehicle 20 depends on not only the frequency of respiratory disease symptoms but also the size or capacity of the compartment 24 of the vehicle 20 as well as the duration of the symptoms. Therefore, the vehicle compartment contamination information should be determined with considering these factors as well. That is, the infection risk information indicates a likelihood (risk) of an infection of a next passenger expected to ride the vehicle, while the vehicle compartment contamination information indicates a necessity of a disinfectant procedure after the vehicle is returned and prior to a next use of the vehicle. [0113]; updating the vehicle compartment contamination information after the disinfectant procedure is completed so as to indicate that the vehicle is clean [0036]);
sending an indication that the updated vehicle degradation value satisfies a vehicle degradation threshold (The risk degree may be defined in association with the likelihood (risk) of an infection of a next user expected to use the seat. For example, less than 1% may be defined as “low”, 1% or more and less than 20% may be defined as “middle”, and more than 20% may be defined as “high”. The risk degree may also be defined in association with the necessity of a disinfectant procedure prior to a next use of the seat. [0141]); and
re-selecting a second vehicle for the task (Since the vehicle A needs to be disinfected prior to the next use and will be unavailable until the disinfectant procedure is completed, this reservation must be changed. Thus, the processor 52 searches an available vehicle in this time slot from the fleet schedule. As the vehicle B is available in this time slot, the processor 52 reassigns the reservation to the vehicle B and move the reservation information from the vehicle A to the vehicle B (S230) [0146])
Liu also teaches:
vehicle degradation values for a plurality of vehicles (Due to the concern of vehicle maintenance, repairs, depreciation, insurance, and other costs, many vehicle owners hesitate to share their vehicles creating an obstacle to owner acceptance of new vehicle sharing ownership models or car sharing models. While the cost of “wear and tear” on a vehicle may be partially covered by a depreciation or mileage allocation, some types of “wear and tear” associated with a particular user or use may be very difficult to detect and allocate costs accordingly [0021]) based on a set of vehicle utilization parameters (As previously described, some components may have wear and tear monitored based on odometer distance, time, speed or a combination of the two. Some components may function normally, then fail suddenly such as an engine low on oil, while other components wear gradually and predictably, such as tire treads. The wear and tear models used to determine vehicle sharing cost may be adjusted accordingly based on the type of component and types of wear associated with particular vehicle operation. [0064])
Morizumi does not explicitly teach, however Liu teaches:
comprising a preliminary navigation path (processor 106 may perform various calculations associated with determining real-time costs of vehicle wear and tear and display the costs to the user and/or communicate with a cloud-based network to provide data and receive costs associated with vehicle maintenance allocated to a particular use, user, route, weather, road condition etc. [0025]) and a vehicle sensor measurements indicating odometer measurements of the available plurality of vehicles (The instrument panel adds the wheel rotations to calculate the odometer measurement. The odometer value may be used for component wear estimates that are based on distance driven. [0046]);
providing a destination of the preliminary navigation path (Vehicle sharing cost may be determined for a vehicle use, driver, route, road conditions, parking behavior, weather, etc. based on data from vehicle sensors and external sensors to detect ambient and operating conditions. [abstract]; The direction of the sun with respect to the vehicle can be determined by the navigation system from the bearing of the vehicle, longitude, latitude, date and time it receives from the global positioning system using a well-known equation [0079])
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Morizumi to include the teachings as taught by Liu with a reasonable expectation of success. Liu teaches the benefits of “a vehicle sharing method or system includes sensors and a processor programmed to receive sensor data associated with operation of a vehicle by a vehicle sharing user during a trip and calculate a vehicle sharing cost associated with anticipated maintenance of a vehicle component based on the sensor data from the trip, historical information and customer characteristics (e.g. repeated ride-sharing customers, or the years of owning a vehicle). The processor may be further programmed to communicate the vehicle sharing cost for display on a vehicle HMI. The sensor may be embedded within the vehicle, and the processor may receive data from external sensors to detect or determine a particular vehicle use, route, driver behavior, and the like. The processor may be programmed to calculate the vehicle sharing cost by comparing the sensor data to previously stored expected values in a vehicle component wear model, and to determine a route for the trip based on the sensor data from the trip. The vehicle sharing cost may be determined based on historical sensor data associated with the route for the trip. The vehicle sharing cost may be also determined based on historical driving behaviors and customers' characteristics. [Liu, 0003]”. The methods of calculating use cost/depreciation of Liu can be applied to the vehicle tasks as performed by the teachings of Lodhia to provide better cost calculations based on the details of the vehicle use.
Morizumi in view of Liu does not explicitly teach, however Rakah teaches:
providing a destination of the preliminary navigation path to an application of a first client device by selecting a first vehicle for a task over one or more other vehicles of the plurality of vehicles based on a first vehicle degradation value for the first vehicle (At step 1111, server 150 may assign a first ridesharing vehicle to pick-up a first group of the plurality of users. For example, the first group may include a first user, a second user, a third user, etc. Some users may be included in the same request (e.g., if a first user and a second user are included in a first request). As explained above with regards to assignment module 920, server 150 may assemble the first group of the plurality of users based on the closeness of starting points of the assembled users, the closeness of the desired destinations of the assembled users, the closeness of the starting points of some of the first group to desired destinations of others of the first group, overlap between predicted routes from the starting points to the desired destinations of some of first group and predicted routes from the starting points to the desired destinations of others of the first group, or the like. [0239]), wherein the first client device performs operations (at least some of the steps of process 400 may be performed by a mobile communications device [0114]) comprising:
re-selecting a second vehicle for the task (At step 1125, server 150 may re-assign the first user to the second ridesharing vehicle [0248]) by (1) receiving the indication from the first client device (when the predicted passing time is after the predicted arrival time. Optionally, server 150 may re-assign the first user only when the predicted passing time is within one or more thresholds after the predicted arrival time. For example, server 150 may re-assign the first user if the predicted passing time is less than 5 minutes, 10 minutes, etc. after the predicted arrival time and/or may re-assign the first user if the predicted passing time is more than 1 minute, 2 minutes, etc. after the predicted arrival time. [0248]) and (2) providing, with the server, the destination of the preliminary navigation path to the second vehicle based on the indication (In some embodiments, server 150 may guide the second ridesharing vehicle to the first pick-up location. For example, as explained above with respect to location module 910, server 150 may send a location (e.g., UPS coordinates) and/or an address of the first pick-up location to a second communications device associated with the second ridesharing vehicle and/or send driving directions to the first pick-up location to the second communications device. [0248]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Morizumi in view of Liu to include the teachin