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 .
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 1/13/20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “display a plurality of trip assignments, each of the plurality of trip assignments associated with a trip assignment provider of a plurality of trip assignment provider[s] ; receiving a selection of one or more of the plurality of trip assignments, each of the one or more selected trip assignments including trip information, the trip information including at least an origin and a destination; generating an optimal route based upon the trip information using an artificial intelligence (AI) model, wherein the AI model is trained using historical trip records including historical trip information associated with historical trips; and display the generated optimal route.”
The limitations above, as drafted, is a process that, under its broadest reasonable interpretation, covers generate an optimal route for a driver which is a method of organizing a human activity. That is, the method allows for the generation instructions for a person to follow which is a method of managing personal behavior or relationships or interactions (i.e. following rules or instructions).
This judicial exception is not integrated into a practical application. In particular, the claim recites “computing device including at least one processor in communication with at least one memory device”, “an application executing on the user device”, “user device” and “a trip assignment provider device of a plurality of trip assignment provider devices”, “wherein the AI model is trained using historical trip records including historical trip information associated with historical trips” (claim 1), “computing device including at least one processor in communication with at least one memory device”, “an application executing on the user device”, “user device” and “a trip assignment provider device of a plurality of trip assignment provider devices”, “wherein the AI model is trained using historical trip records including historical trip information associated with historical trips” (claim 13), “at least one non-transitory computer readable media”, “computing device including at least one processor in communication with at least one memory device”, “an application executing on the user device”, “user device” and “a trip assignment provider device of a plurality of trip assignment provider devices”, “wherein the AI model is trained using historical trip records including historical trip information associated with historical trips “(claim 20). Each of the additional limitations is recited at a high level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements, alone or in combination, are nothing more than mere instructions to apply the exception on a general computer.
Dependent claims 2-12 and 13-19 also directed to an abstract idea without significantly more because they further narrow the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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) 1-6, 13-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leoni (US 2018/0046964) in view of Woodard (US 2016/0202074).
As per claim 1/13/20, Leoni discloses a computing device comprising at least one processor in communication with at least one memory device and with a user device corresponding to a user, the at least one processor configured to:
cause, using an application executing on the user device, the user device to display a plurality of trip assignments, each of the plurality of trip assignments associated with a trip assignment provider device of a plurality of trip assignment provider devices ([0123] Referring to FIG. 12A, an exemplary load board screen 1200 of the logistics application is shown. Generally, the load board screen 1200 allows drivers to view and select pending loads submitted to the load board by a job creator, as described in the above job creation process, 0125] Generally, the load board comprises load deliveries scheduled by a job creator (e.g., carrier, receiver, shipper, broker, dispatcher). Though all roles within the platform may be able to view the load board, only qualified drivers may be allowed to execute a load delivery published through the load board.);
receive, from the user device, a selection of one or more of the plurality of trip assignments, each of the one or more selected trip assignments including trip information, the trip information including at least an origin and a destination ([0123] Referring to FIG. 12A, an exemplary load board screen 1200 of the logistics application is shown. Generally, the load board screen 1200 allows drivers to view and select pending loads submitted to the load board by a job creator, as described in the above job creation process. The load board screen 1200 may be accessed by, for example, selecting the “Load Board” option 1004 on the navigation screen 1000 (see FIG. 10), [0124] As shown in FIG. 12A, the load board screen provides one or more pending loads 1202 shown as stackable cards. In one embodiment, the pending loads 1202 display load details, such as the job name 1204, origin satellite photo 1206, destination satellite photo 1208, a summary of the load logistics, an accept button 1212 and/or a deny button 1214. Selecting the deny button 1214 may cause the corresponding card to vanish and remaining cards to move to the top of the list.).
However, Leoni does not disclose but Woodard discloses generate an optimal route based upon the trip information using an artificial intelligence (AI) model, wherein the Al model is trained using historical trip records including historical trip information associated with historical trips ([0027] The mapping application 124 may utilize the information specified by the user 110 (e.g., a destination 116, start time for a trip, preferences, etc.) and any other contextual information, such as the time of day, weather conditions, traffic information, and so on, to plan routes and to predict travel time variability for those routes using the prediction component 126 that is configured to access the machine learning model 102 for making such predictions, [0004]“A machine learning model may be trained from historical trip data and used to predict the variability in (probability distribution of) travel time—a random variable—along a given route from the origin to the destination, at a particular time.”
cause, using the application, the user device to display the generated optimal route ([0028] …. For example, a display of the computing device 108 may provide a visual output of the recommended route(s) 118 on a map as part of the mapping application 124. In addition, a measure of driving time may be output by the mapping application 124.).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Woodard in the teaching of Leoni, in order to predict variability of travel time for a trip at a particular time (please see Woodard abstract).
As per claim 2/14, Leoni discloses wherein the at least one processor is further configured to: retrieve driver information corresponding to the user ([0042] Among other functions, the platform allows stakeholders to create/update a personal profile, create/update a company profile, create/update a loading site profile, upload license or certification information, create load delivery requests, assign load delivery requests, accept load delivery requests, track status events associated with a load delivery, upload relevant load delivery information, and manage communications with other stakeholders., [0077] Referring to FIG. 5, exemplary profile databases are shown. The central data store 510 may comprise a personal profiles database 512, a company profiles database 513, and a site profiles database 514. Profile data can include personal profile data, company profile data, and site profile data.); and select the plurality of trip assignments to display based upon the driver information ([0082] Staffing analysis 416 allows the application to match a driver (or other vehicle/equipment operator) with a particular set of certifications to a job according to the staffing and compliance needs of the job's load delivery, or according to the relative decrease in liability risk that the job is purported to incur based on the driver's past history through the platform.).
As per claim 3/15, Leoni discloses wherein the driver information indicates trip assignment provider devices with which the user has registered ([0078] Personal profile data comprise user information, including at least the name and the role of the user and any licensing and certification information for the user. Company profile data comprise company information, including at least the name, address, and phone number of the company. Site profile data comprise loading site info, including location, policies/procedures, delivery hours, and available equipment for use by drivers. Though all users would have a personal profile, not all users may be associated with a company profile. Certain roles, such as carriers, dispatchers, receivers, shippers, and brokers would be associated with a company profile and with the exception of most brokers, would typically also be associated with at least one site profile.).
As per claim 4/16, Leoni discloses wherein the at least one processor is further configured to receive the plurality of trip assignments from the plurality of trip assignment provider devices ([0101] In a step 806, the job creator and other stakeholders (e.g., origin and destination site owners) may approve the job, at which point the job creator may publish the job to a load board in a further step 808 or assign the job to a driver in a further step 810.. [0123] Referring to FIG. 12A, an exemplary load board screen 1200 of the logistics application is shown. Generally, the load board screen 1200 allows drivers to view and select pending loads submitted to the load board by a job creator, as described in the above job creation process. The load board screen 1200 may be accessed by, for example, selecting the “Load Board” option 1004 on the navigation screen 1000 (see FIG. 10).)
As per claim 5/17, Leoni discloses wherein the at least one processor is further configured to transmit an acceptance message to trip assignment provider devices of the plurality of trip assignment provider devices that are associated with the selected one or more of the plurality of trip assignments ([0127] The job creator may be notified when the job is accepted by a driver. In one embodiment, the job creator may manually provide the driver authorization to proceed with the load delivery through the application.).
As per claim 6/18, Leoni does not disclose but Woodard discloses wherein the at least one processor is further configured to train the Al model based upon the historical trip records ([0004]“A machine learning model may be trained from historical trip data and used to predict the variability in (probability distribution of) travel time—a random variable—along a given route from the origin to the destination, at a particular time.).
Claim(s) 7 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leoni (US 2018/0046964) in view of Woodard (US 2016/0202074), as disclosed in the rejection of claim 1, in further view of Aman (US 2021/0073734).
As per claim 7/19, Leoni does not disclose but Aman discloses wherein the optimal route includes each origin and each destination associated with of the one or more selected trip assignments ([0004]…. The method comprises the step of generating an optimized route of a multi-trip itinerary for the driver to follow to perform the on time pickup and on time to drop off within the set of DTC and WCL constraints. [0039] In a truck transportation example, process 100 can generate and provide a multi-trip itinerary for requesting truck drivers. For example, process 100 can build a multi-hop route from point A-to-B-to-C-to-D.).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Aman in the teaching of Leoni, in order to reduce empty miles by applying the rigor of data science and optimization algorithms (please see Aman paragraph 3).
Claim(s) 8-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leoni (US 2018/0046964) in view of Woodard (US 2016/0202074), as disclosed in the rejection of claim 1, in further view of Fields (US 10769954).
As per claim 8, Leoni does not disclose but Fields discloses wherein the at least one processor is further configured to receive telematics data generated by the user device executing the application while the user is traveling the optimal route (5:32-39, “24) To address these and other problems, telematics data (and/or driver behavior or vehicle information) may be captured in real-time, or near real-time, by a computing device, such as a vehicle-mounted computer, smart vehicle controller, or a mobile device of a vehicle driver (or passenger). The computing device may be specifically configured for gathering, collecting, and/or generating telematics and/or other data as a vehicle is traveling.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Fields in the teaching of Leoni, in order to provide vehicular driver alerts (please see Fields abstract).
As per claim 9, Leoni discloses wherein the at least one processor is further configured to determine a first trip assignment of the one or more selected trip assignments has been completed based upon the telematics data ([0131] In another embodiment, the application may be configured to periodically detect the location of the client device of the driver. As the active load progress through delivery, updates may be automatically generated based on the location of the driver (and presumably also the driver's vehicle and the load being delivered). For example, if the application detects that the driver's client device is approaching the origin site of Job A, the application may automatically update the current status 1304 of Job A to ‘Origin Site Reached.’ Subsequently, if the application detects that the driver's client device is leaving the origin site, the application may automatically update the current status 1304 to ‘Pick Up Confirmed.’).
As per claim 10, Leoni discloses wherein the at least one processor is further configured to transmit a completion message indicating the first trip assignment has been completed to the trip assignment provider devices associated with the first trip assignment ([0132] As shown in FIG. 13A, the active load deliveries screen 1300 comprises another active load 1312 titled ‘Job C’ that is at a separate stage of the load delivery process. As shown, the current status 1314 of Job C may be ‘Confirmed Delivery,’ and the job details 1316 may display that the route is complete (i.e., the driver has reached the destination site). The driver assigned to Job C may select a ‘Upload Bill of Lading’ button 1318, thus completing the load delivery process as described in FIG. 8B.. [0157] Referring to FIG. 14D, the dashboard 1400 is shown illustrating an exemplary notification card for the final stages of a load delivery. Upon reaching a destination site and confirming delivery, the driver may complete the load delivery process through the application by uploading a signed Bill of Lading. Once uploaded, the dashboard 1400 may display a notification card 1448 to all stakeholders showing a preview 1449 of the Bill of Lading and a facility for a stakeholder to leave feedback 1450 for the driver. [0079] Referring back to FIG. 4, load management 412 allows stakeholders to schedule a load delivery, assign the delivery to available drivers, view and update active loads, and access a dashboard that functions as a notifications feed for all active loads associated with the stakeholder. Load management also allows the various stakeholders of a pending load to send, upload and access up-to-date information regarding the load delivery, such as current location, text/image updates from stakeholders, weather conditions, delivery status (e.g., on route, delayed, awaiting signature, etc.), feedback/ratings/reviews, documents (such as Bills of Lading), and other relevant information.”)
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leoni (US 2018/0046964) in view of Woodard (US 2016/0202074) and Fields (US 10769954), as disclosed in the rejection of claim 8, in further view of Sweany (US 2019/0180645).
As per claim 11, Leoni does not disclose but Sweany discloses wherein the at least one processor is further configured to: compute a cost or score based upon the received telematics data; and cause, using the application, the user device to display the computed cost or score (fig. 11, [0083] The capabilities of telematics unit 160 are particularly useful to fleet operators. Telematics unit 160 is configured to collect position data from the vehicle (to enable vehicle owners to track the current location of their vehicles, and where they have been) and to collect vehicle operational data (including but not limited to engine RPM, gear selection, cruise control use, vehicle speed, and idle time), and to use the RF component to wirelessly convey such data to vehicle owners and/or a third party monitoring service, where such data can be analyzed to determine driver efficiency scores and fuel lost costs due to scores less than 100%, generally as discussed above in connection with FIG. 1.).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Sweany in the teaching of Leoni, in order to determining how often the driver's deviated from an optimal standard (please see Sweany abstract).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leoni (US 2018/0046964) in view of Woodard (US 2016/0202074), Fields (US 10769954), as disclosed in the rejection of claim 8, in further view of Taylor (US 7167796).
As per claim 12, Leoni does not discloses but Taylor discloses wherein the at least one processor is further configured to: determine a current location of the user device based upon the telematics data; and cause, using the application, the user device to display at least one instruction determined based upon the current location of the user device (3:19-31, “(13) The control also receives, preferably continuously, an input from the vehicle-based global positioning system that is indicative of the actual, current geographic position of the vehicle as the vehicle travels along the road, highway or the like. The control is then operable to compare the tagged or coded geographic location (as associated with the respective instructions) with the GPS-derived actual geographic position information. Thus, the control may determine when a particular instruction is appropriate to be displayed and/or communicated to the driver by determining that the GPS-derived actual geographic position of the vehicle is now at or at least close to the geographic location associated with a particular instruction.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Taylor in the teaching of Leoni, in order to provide driving instructions or directions to a driver of a vehicle or which may provide other controls to an accessory or system of the vehicle (please see Taylor 1:35-36).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OMAR ZEROUAL whose telephone number is (571)272-7255. The examiner can normally be reached Flex schedule.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Resha Desai can be reached at (571) 270-7792. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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OMAR . ZEROUAL
Examiner
Art Unit 3628
/OMAR ZEROUAL/Primary Examiner, Art Unit 3628