DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Responsive to the communication dated 07/09/2026
Claims 1-20 are presented for examination
Information Disclosure Statement
The IDS dated 07/21/2026 has been reviewed. See attached.
Drawings
The drawings dated 10/13/2021 have been reviewed. They are accepted.
Abstract
The abstract dated 10/13/2021 has been reviewed. It has 131 words, and contains no legal phraseology. It is accepted.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 07/09/2026 has been entered.
Response to Arguments- 35 USC § 101
Applicant’s arguments, see pages 9-15, filed 07/09/2026, with respect to the rejection of claims 1-20 under 35 USC § 101 have been fully considered and are persuasive. The rejection of claims 1-20 under 35 USC § 101 has been withdrawn.
Specifically, the claims describe a very particular user interface system that enables dynamic user interaction with the simulation system that enables a deeper, faster, and more intuitive method for documenting vehicle accidents and filing related insurance claims. Further, see MPEP 2106.05(a)(I)(x) and MPEP 2106.05(a)(I)(xi), as well as USPTO Subject Matter Eligibility Example 37, which all describe how particular, improved user interfaces can integrate an abstract idea into a practical application.
Response to Arguments- 35 USC § 103
Applicant's arguments filed 07/09/2026 have been fully considered but they are not persuasive.
Applicant argues that no prior art teaches “receive, over the one or more networks from the computing device of the claimant, additional information about the vehicle incident provided via the one or more features;
generate, based at least in part on the additional information, a dynamic simulation of the vehicle incident using the physics engine; and
transmit, over the one or more networks, data to the computing device of the claimant to dynamically visualize, on the interactive contextual interface, the dynamic simulation generated based at least in part on the additional information.”
Examiner responds by explaining that these features are taught by the previously cited prior art in combination with new reference Serrao (US 11620862 B1).
In particular:
Farmer teaches provide on the interactive contextual interface, ([Par 8] “ FIG. 5A, FIG. 5B, FIG. 5C, and FIG. 5D are diagrams of a system depicting example interfaces according to some embodiments;”[Par 56-57] “In some embodiments, dynamic diagramming feedback may prompt the user to identify each vehicle (or other object) involved, prompt the user to assign vector input to a graphical representation of a diagrammed vehicle, and/or provide graphical element relocation guidance (e.g., not permit a user to diagram a vehicle off of a travel way (or apply other graphical and/or spatial diagramming constraints). In the case that a user draws/places a graphical representation of a vehicle in a lake, field, and/or conflicting with a building location, for example, the user may be prompted to confirm that the conflicting (or unusual) location is indeed the desired location. In some embodiments, in the case that the input is determined to comply with stored constraints/criteria at 418D, the method 400 may proceed to determine whether additional input is required, at 418E. In the case that additional input is needed, the method 400 may proceed back to provide input guidance at 418A. The method 400 may, for example, loop through capturing of accident inputs at 418 by first guiding a user through acquiring adequate documentary imagery of an accident/event, then acquiring an adequate quantity and content for recorded statements, then through a self-diagramming accident/scene sketching process. In some embodiments, once each of these (or fewer or more desired input actions) is accomplished, the method 400 may proceed. In some embodiments, any or all user input may be automatically uploaded and/or mapped to various respective form fields into one or more third-party websites and/or forms (such as a police FR-10 Form) to automatically order copies of official reports (e.g., police reports) and/or other incident/accident-related data.”)
receive, over the one or more networks from the computing device of the claimant, an indication ([Par 69] “In some embodiments, the submit button 520-13 may, when actuated or selected by the user, for example, initiate a sub-routine that transmits any or all saved, input, and/or captured data (e.g., text details of a user's description of the accident, captured video/images of the accident scene, optically-recognized character information from image data, recorded statement data, scene diagram data, etc.) to a remote server (not shown; e.g., the server 110, 310 of FIG. 1 and/or FIG. 3 herein).”)
receive, over the one or more networks from the computing device of the claimant, additional information about the vehicle incident provided via the one or more features; ([Par 69] “In some embodiments, the submit button 520-13 may, when actuated or selected by the user, for example, initiate a sub-routine that transmits any or all saved, input, and/or captured data (e.g., text details of a user's description of the accident, captured video/images of the accident scene, optically-recognized character information from image data, recorded statement data, scene diagram data, etc.) to a remote server (not shown; e.g., the server 110, 310 of FIG. 1 and/or FIG. 3 herein).” [Par 56-57] “In some embodiments, dynamic diagramming feedback may prompt the user to identify each vehicle (or other object) involved, prompt the user to assign vector input to a graphical representation of a diagrammed vehicle, and/or provide graphical element relocation guidance (e.g., not permit a user to diagram a vehicle off of a travel way (or apply other graphical and/or spatial diagramming constraints). In the case that a user draws/places a graphical representation of a vehicle in a lake, field, and/or conflicting with a building location, for example, the user may be prompted to confirm that the conflicting (or unusual) location is indeed the desired location. In some embodiments, in the case that the input is determined to comply with stored constraints/criteria at 418D, the method 400 may proceed to determine whether additional input is required, at 418E. In the case that additional input is needed, the method 400 may proceed back to provide input guidance at 418A. The method 400 may, for example, loop through capturing of accident inputs at 418 by first guiding a user through acquiring adequate documentary imagery of an accident/event, then acquiring an adequate quantity and content for recorded statements, then through a self-diagramming accident/scene sketching process. In some embodiments, once each of these (or fewer or more desired input actions) is accomplished, the method 400 may proceed. In some embodiments, any or all user input may be automatically uploaded and/or mapped to various respective form fields into one or more third-party websites and/or forms (such as a police FR-10 Form) to automatically order copies of official reports (e.g., police reports) and/or other incident/accident-related data.”)
transmit, over the one or more networks, data to the computing device of the claimant ([Par 17] “In some embodiments, the user device 102a may comprise one or more devices owned and/or operated by one or more users, such as an automobile (and/or other vehicle, liability, personal, and/or corporate insurance customer) insurance customer (e.g., insured) and/or other accident victim and/or witness. According to some embodiments, the user device 102a may communicate with the server 110 via the network 104 to provide evidence and/or other data descriptive of an accident event and/or accident scene (e.g., captured images of damage incurred, recorded statements, and/or scene diagram(s)), as described herein” [Par 33] “According to some embodiments, the mobile electronic device 302 (and/or the display screen 318a thereof) may output a GUI 320 that provides output from and/or accepts input for, a mobile device application executed by the mobile electronic device 302. According to some embodiments, the application may comprise a web-interface application, such as a web browser that provides the GUI 320 based on webpages and/or data served by the server 310.”) ([Par 8] “ FIG. 5A, FIG. 5B, FIG. 5C, and FIG. 5D are diagrams of a system depicting example interfaces according to some embodiments;”)
Farmer teaches the basic UI interactions including dynamic visualizations and the communication between the mobile device and server, but it does not explicitly teach a physics-based simulation nor the accuracy confirmation being in reference to the simulation.
To this end, Cardona teaches ([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.” [Col 8 line 13-18] “The VFA computing device may generate a simulation including a scene model depicting the scene of the collision. The scene model may be based upon, for example, map data and contextual data and enables individuals not present at the scene of the collision (e.g., insurance claims employees) to visualize the scene.” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Col 28 line48-52] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact.”) ([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.” [Col 8 line 13-18] “The VFA computing device may generate a simulation including a scene model depicting the scene of the collision. The scene model may be based upon, for example, map data and contextual data and enables individuals not present at the scene of the collision (e.g., insurance claims employees) to visualize the scene.” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Col 28 line48-52] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact.”)
([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.” [Col 8 line 13-18] “The VFA computing device may generate a simulation including a scene model depicting the scene of the collision. The scene model may be based upon, for example, map data and contextual data and enables individuals not present at the scene of the collision (e.g., insurance claims employees) to visualize the scene.” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Col 28 line48-52] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact.”)
Further, Cardona does not merely “discard” its claimant input, as argued; instead this claimant input is an integral part of generating the simulation, as in the present claims ([Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Abstract] “(3) receive speech data, the speech data corresponding to a statement given by a witness of the traffic collision; (4) parse the speech data for phrases describing the traffic collision; (5) determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time; and (7) display the simulation to reconstruct the collision.”) Rather than “discarding” the claimant data in favor of the physics data, the simulation data produced by Cardona is a combination of both.
While Cardona teaches generating dynamic simulations using a physics engine based on the provided data, it does not explicitly teach showing a first visualization, checking with a user to confirm accuracy, and then presenting a second visualization based on the user’s response (e.g. if the user says the visualization is inaccurate, changing aspects of the visualization)
To this end, new reference Serrao teaches provide, with the dynamic visualization, features that allow enable the user to confirm an accuracy of the visualization, and provide additional information; processing an indication as to whether the visualization is accurate; generate, based at least in part on the additional information, a dynamic visualization of the vehicle incident; process data to dynamically visualize the dynamic visualization generated based at least in part on the additional information. ([Col 5 line 61 – Col 6 line 31] “Next, in step 410, accident reconstruction system 190 may generate an animated video of the accident using the accident data. This process is described in further detail below and shown in FIG. 5. In some cases, accident reconstruction system 190 may also generate a 3D model as part of, or in parallel with, generating the animated video. For example, in some embodiments a system first generates a dynamic 3D model of an accident, including the vehicles or other objects involved in the accident, and then uses that model as the basis for rendering an animated video to represent the sequence of events. In step 412, system 110 may present the animated video to a user. The user in this context could be a driver of the vehicle or another occupant. The animated video could be displayed on a display of the vehicle, or could be sent to the user's mobile device for viewing. … Next, in step 414, system 110 may have the user confirm that the animated video is sufficiently accurate. If the user does not feel the animation is accurate, the system may modify the video in step 416 and then return to step 412 to present the modified video to the user. To improve the accuracy of the video, the system may also change the accident data used by the model by adding additional data sources and/or removing others… In step 418, after the accuracy of the animated video is confirmed by the user, system 110 may send the accident data to remote server 350.” [Col 7 line 41- line 54] “As part of constructing an animated video, and/or in parallel, accident reconstruction system 190 may also build a 3D model of the accident. This model could be static or dynamic. As seen in FIG. 5, in some cases, animation and model engine 504 may output both an animated video of the accident 540 and a 3D model of the accident 542. Whereas the animated video may be especially useful for drivers, occupants and other parties to review the accident, the 3D model could be used by other software or systems to record information and/or take action in response to an accident, as discussed in further detail below. In some cases, a 3D model could be interactive, allowing the user to adjust parameters and/or move parts of the model to better understand the accident.”)
Serrao is analogous art because it is within the field of vehicle accident visualization and recreation. It would have been obvious to one of ordinary skill in the art to combine it with Farmer and Cardona before the effective filing date. One of ordinary skill in the art would have been motivated to make this combination in order to more accurately produce accident recreations, as well as prevent further damage to a vehicle between the time of the accident and the time rescuers or insurance personnel can arrive. Firstly, Serrao notes how, frequently, insurance carriers are not the first people contacted following an accident, and consequently, between the trauma of an accident occurring and normal forgetting of memories over time the information eventually relayed to an insurance representative may be misremembered or inaccurate. ([Col 1 Line 22 – Line 35] “Following an accident, a driver may or may not call their insurance carrier to provide details about the accident. If an accident is reported, it is a very time consuming process. In addition, the driver may forget or misremember details about the accident. The driver may also be in a physical or mental state that prevents them from providing accurate details about incidents before, during or after the accident. The representative of the insurance carrier may therefore obtain an inaccurate understanding of how the accident occurred and what damage has occurred to the vehicle. This inaccuracy can lead to delays in claim processing, inaccurate damage estimates, multiple inspections, as well as additional costs to both the insurance provider and the driver in some cases.”) To this end, Serrao introduces a system for generating an accident recreation from sensor data and allowing a user to review the recreation of the accident to confirm the recreation’s accuracy or otherwise adjust data sources until the recreation matches reality. ([Col 5 line 61 – Col 6 line 31] “Next, in step 410, accident reconstruction system 190 may generate an animated video of the accident using the accident data. This process is described in further detail below and shown in FIG. 5. In some cases, accident reconstruction system 190 may also generate a 3D model as part of, or in parallel with, generating the animated video. For example, in some embodiments a system first generates a dynamic 3D model of an accident, including the vehicles or other objects involved in the accident, and then uses that model as the basis for rendering an animated video to represent the sequence of events. In step 412, system 110 may present the animated video to a user. The user in this context could be a driver of the vehicle or another occupant. The animated video could be displayed on a display of the vehicle, or could be sent to the user's mobile device for viewing. … Next, in step 414, system 110 may have the user confirm that the animated video is sufficiently accurate. If the user does not feel the animation is accurate, the system may modify the video in step 416 and then return to step 412 to present the modified video to the user. To improve the accuracy of the video, the system may also change the accident data used by the model by adding additional data sources and/or removing others… In step 418, after the accuracy of the animated video is confirmed by the user, system 110 may send the accident data to remote server 350.” [Col 6 line 42 – Line 67] “Once the accident data is received at remote server 350 in step 420, remote server 350 may reconstruct the animated video of the accident in step 422. … Next, in step 424, the animated video may be presented to a representative to facilitate review of the accident. Specifically, in some cases, the representative could be a representative of an insurance company that provides coverage for the vehicle. In some cases, upon receiving the animated video of the accident, the representative could call the user of vehicle 100 to review the accident and gather any relevant information in step 426. Finally, the animated video and/or underlying raw accident data could be sent to other parties in step 428. As one example, an animated video of a collision could be sent to a repair facility to provide a visual image of the type of damage expected for the vehicle prior to its arrival at the repair facility. This process of reviewing a reconstructed video of an accident based on sensed data may provide increased accuracy for reporting accidents over alternative methods that rely on user's to manually recall events from memory. Moreover, once the user confirms that the video is sufficiently accurate, the video can serve as a more reliable store of accident information than the user's long-term memory.”) This combination of sensor-derived data with user input and review ultimately results in an accident recreation that is more accurate than either a purely sensor-derived or purely testimony-derived recreation would be on its own. Further, Serrao notes how certain types of damage may cause vehicles to continue to damage themselves following an accident, which could lead to additional costs and maintenance; to this end, Serrao presents a control system that uses the recreation to determine if the vehicle has damage that would cause it to be an immediate risk to itself and takes action to prevent that risk. ([Col 9 line 37 – line 62] “An accident reconstruction system can include provisions for mitigating further damage after an accident has occurred. … In step 1206, the system assesses the damage vehicle components and systems based on the model (or animation). The system then determines if there is a risk of further damage to any components (or system) in step 1208. If there is no further risk of damage, the system may take no further actions as in step 1209. If there is a risk of further damage, the system may modify the control of one or more vehicle systems to mitigate further damage in step 1210… As one example of damage mitigation, an accident reconstruction system could assess the state of an engine following an accident. By analyzing a 3D model of the accident and/or images from an animated video, the accident reconstruction system could determine that the engine is severely damaged and there is further risk of damage if the engine keeps running in an idle mode. In this case, the accident reconstruction system could actively control one or more engine control systems, such as the fuel injection system, to stop fuel from being injected into the cylinders.”) Overall, one of ordinary skill in the art would have recognized that combining Serrao with Farmer and Cardona would result in more accurate accident recreations as well as prevent any additional post-accident damage that could complicate later analysis or repair.
Claim Objections
Claims 1-20 objected to because of the following informalities:
Claims 1, 9, and 17 recite “dynamically visualize the simulation” to refer to the first simulation, not based on the additional data, and the later recite “a dynamic simulation of the vehicle incident” to refer to the second simulation based on the additional data. Although not technically an issue with antecedent basis as different terms are used (i.e. the “simulation” vs the “dynamic simulation”) the fact that both simulations are referred to as being “dynamically visualize[d]” hinders readability. It is recommended to amend the claims to more clearly distinguish the pre- and post- additional information simulations, for example referring to the pre- additional information simulation as an “initial simulation” and the post- additional information simulation as a “modified simulation” or referring to the pre- and post- additional information simulations as a “first simulation” and “second simulation,” respectively. Care should be taken to ensure these changes are properly propagated to the dependent claims as well.
Appropriate correction is required.
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.
Claims 1-5, 8-13, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Farmer (US 20210004909 A1) in view of Cardona (US 11308741 B1) in further view of Serrao (US 11620862 B1)
Claim 1. Farmer makes obvious A computing system comprising: a network communication interface; one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: ([Par 19] “The network 104 may, according to some embodiments, comprise a Local Area Network (LAN; wireless and/or wired), cellular telephone, Bluetooth® and/or Bluetooth Low Energy (BLE), Near Field Communication (NFC), and/or Radio Frequency (RF) network with communication links between the server 110, the user device 102a, the vehicle 102b, the third-party device 106, the sensors 116a-b, and/or the memory 140.”) generate an interactive contextual interface on a computing device of a claimant claiming an injury from a vehicle incident, the interactive contextual interface enabling the claimant (i) to provide incident information, including to physically draw a trajectory on an input interface of the computing device, and (ii) to indicate a location and severity of one or more injuries of the claimant; ([Fig. 5D] [Par 71-72] “ The fourth version of the interface 520d may comprise and/or represent, for example, a map-based diagram tool and/or a GUI vector drawing tool. According to some embodiments, the fourth version of the interface 520d may be generated by GUI diagram program code that pre-loads a geo-referenced map image, e.g., as depicted in FIG. 5D. In some embodiments, the map image may comprise the map-based diagram that permits the user to provide input defining one or more points, areas, and/or objects on the generated map image/layer… In some embodiments, the GUI vector drawing tool may be utilized by the user to provide (e.g., via the user device 502 and/or the fourth version of the interface 520d) first vector input that defines a first location on the map and/or a first direction (and/or speed; e.g., a vector). According to some embodiments, the first vector input may be provided in conjunction with and/or utilizing a common GUI object selection tool or library. As depicted in FIG. 5D, for example, the fourth version of the interface 520d may comprise a common GUI object selection area 524 that stores and displays a plurality of common GUI objects, such as those representing various vehicles and objects that may be desired for placement on the map image” [Par 55] ” According to some embodiments, audio input may be interrupted to prompt the user to answer a specific question or even to answer a question posed by the user to the system. In some embodiments, recorded statement prompts and/or questions may direct the user to provide any or all of the following data items (either personally or by interviewing a witness): (i) informed consent to the recording; (ii) driver identification information (name, license number, date of birth, address); (iii) whether the driver owns the vehicle or had permission to use the vehicle; (iv) where the vehicle is garaged; (v) if the driver has possession of a set of keys for the vehicle; (vi) whether the driver regularly uses the vehicle; (vii) whether the driver/user was injured; (viii) identifying information of others that were injured; (ix) injury details (parts of body, extent); (x) how injury occurred (injury mechanics as related to the vehicle); (xi) details on initial treatment; (xii) details of any diagnostic injury testing done; (xiii) resulting medication information; (xiv) scheduled follow-up treatment details; (xv) details of prior accidents and/or injuries”)
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receive, over one or more networks from the computing device of the claimant, input data indicating (i) a drawn path representing a trajectory of at least one vehicle, (ii) a speed of the at least one vehicle along the trajectory, and (iii) an incident location following the trajectory; and ([Fig. 5D] [Par 72] “] In some embodiments, the GUI vector drawing tool may be utilized by the user to provide (e.g., via the user device 502 and/or the fourth version of the interface 520d) first vector input that defines a first location on the map and/or a first direction (and/or speed; e.g., a vector).” [Par 51] “In some embodiments, the user input may comprise one or more images and/or videos, one or more audio recordings (e.g., recorded statement(s)), and/or one or more graphical diagramming inputs (e.g., self-diagramming inputs, such as lines, points, vectors, object locations, speeds, etc.).” [Par 47] “ In some embodiments, the method 400 may comprise receiving (e.g., by the webserver and/or via the electronic communications network and/or from the user device) data verification, at 416. Input received via the GUI input elements of the data verification webpage/GUI may, for example, be received by the webserver.”) ([Fig. 5D] [Par 72] “] In some embodiments, the GUI vector drawing tool may be utilized by the user to provide (e.g., via the user device 502 and/or the fourth version of the interface 520d) first vector input that defines a first location on the map and/or a first direction (and/or speed; e.g., a vector).” [Par 51] “In some embodiments, the user input may comprise one or more images and/or videos, one or more audio recordings (e.g., recorded statement(s)), and/or one or more graphical diagramming inputs (e.g., self-diagramming inputs, such as lines, points, vectors, object locations, speeds, etc.).” [Par 47] “ In some embodiments, the method 400 may comprise receiving (e.g., by the webserver and/or via the electronic communications network and/or from the user device) data verification, at 416. Input received via the GUI input elements of the data verification webpage/GUI may, for example, be received by the webserver.” [Par 55] ” According to some embodiments, audio input may be interrupted to prompt the user to answer a specific question or even to answer a question posed by the user to the system. In some embodiments, recorded statement prompts and/or questions may direct the user to provide any or all of the following data items (either personally or by interviewing a witness): (i) informed consent to the recording; (ii) driver identification information (name, license number, date of birth, address); (iii) whether the driver owns the vehicle or had permission to use the vehicle; (iv) where the vehicle is garaged; (v) if the driver has possession of a set of keys for the vehicle; (vi) whether the driver regularly uses the vehicle; (vii) whether the driver/user was injured; (viii) identifying information of others that were injured; (ix) injury details (parts of body, extent); (x) how injury occurred (injury mechanics as related to the vehicle); (xi) details on initial treatment; (xii) details of any diagnostic injury testing done; (xiii) resulting medication information; (xiv) scheduled follow-up treatment details; (xv) details of prior accidents and/or injuries”) ([Fig. 5D] [Par 72] “] In some embodiments, the GUI vector drawing tool may be utilized by the user to provide (e.g., via the user device 502 and/or the fourth version of the interface 520d) first vector input that defines a first location on the map and/or a first direction (and/or speed; e.g., a vector).” [Par 51] “In some embodiments, the user input may comprise one or more images and/or videos, one or more audio recordings (e.g., recorded statement(s)), and/or one or more graphical diagramming inputs (e.g., self-diagramming inputs, such as lines, points, vectors, object locations, speeds, etc.).”) transmit, over the one or more networks, data to the computing device of the claimant ([Par 17] “In some embodiments, the user device 102a may comprise one or more devices owned and/or operated by one or more users, such as an automobile (and/or other vehicle, liability, personal, and/or corporate insurance customer) insurance customer (e.g., insured) and/or other accident victim and/or witness. According to some embodiments, the user device 102a may communicate with the server 110 via the network 104 to provide evidence and/or other data descriptive of an accident event and/or accident scene (e.g., captured images of damage incurred, recorded statements, and/or scene diagram(s)), as described herein” [Par 33] “According to some embodiments, the mobile electronic device 302 (and/or the display screen 318a thereof) may output a GUI 320 that provides output from and/or accepts input for, a mobile device application executed by the mobile electronic device 302. According to some embodiments, the application may comprise a web-interface application, such as a web browser that provides the GUI 320 based on webpages and/or data served by the server 310.”) to dynamically visualize([Fig. 5D] [Par 71-72] “ The fourth version of the interface 520d may comprise and/or represent, for example, a map-based diagram tool and/or a GUI vector drawing tool. According to some embodiments, the fourth version of the interface 520d may be generated by GUI diagram program code that pre-loads a geo-referenced map image, e.g., as depicted in FIG. 5D. In some embodiments, the map image may comprise the map-based diagram that permits the user to provide input defining one or more points, areas, and/or objects on the generated map image/layer… In some embodiments, the GUI vector drawing tool may be utilized by the user to provide (e.g., via the user device 502 and/or the fourth version of the interface 520d) first vector input that defines a first location on the map and/or a first direction (and/or speed; e.g., a vector). According to some embodiments, the first vector input may be provided in conjunction with and/or utilizing a common GUI object selection tool or library. As depicted in FIG. 5D, for example, the fourth version of the interface 520d may comprise a common GUI object selection area 524 that stores and displays a plurality of common GUI objects, such as those representing various vehicles and objects that may be desired for placement on the map image.”) provide on the interactive contextual interface, ([Par 8] “ FIG. 5A, FIG. 5B, FIG. 5C, and FIG. 5D are diagrams of a system depicting example interfaces according to some embodiments;”[Par 56-57] “In some embodiments, dynamic diagramming feedback may prompt the user to identify each vehicle (or other object) involved, prompt the user to assign vector input to a graphical representation of a diagrammed vehicle, and/or provide graphical element relocation guidance (e.g., not permit a user to diagram a vehicle off of a travel way (or apply other graphical and/or spatial diagramming constraints). In the case that a user draws/places a graphical representation of a vehicle in a lake, field, and/or conflicting with a building location, for example, the user may be prompted to confirm that the conflicting (or unusual) location is indeed the desired location. In some embodiments, in the case that the input is determined to comply with stored constraints/criteria at 418D, the method 400 may proceed to determine whether additional input is required, at 418E. In the case that additional input is needed, the method 400 may proceed back to provide input guidance at 418A. The method 400 may, for example, loop through capturing of accident inputs at 418 by first guiding a user through acquiring adequate documentary imagery of an accident/event, then acquiring an adequate quantity and content for recorded statements, then through a self-diagramming accident/scene sketching process. In some embodiments, once each of these (or fewer or more desired input actions) is accomplished, the method 400 may proceed. In some embodiments, any or all user input may be automatically uploaded and/or mapped to various respective form fields into one or more third-party websites and/or forms (such as a police FR-10 Form) to automatically order copies of official reports (e.g., police reports) and/or other incident/accident-related data.”) receive, over the one or more networks from the computing device of the claimant, an indication ([Par 69] “In some embodiments, the submit button 520-13 may, when actuated or selected by the user, for example, initiate a sub-routine that transmits any or all saved, input, and/or captured data (e.g., text details of a user's description of the accident, captured video/images of the accident scene, optically-recognized character information from image data, recorded statement data, scene diagram data, etc.) to a remote server (not shown; e.g., the server 110, 310 of FIG. 1 and/or FIG. 3 herein).”) ([Par 69] “In some embodiments, the submit button 520-13 may, when actuated or selected by the user, for example, initiate a sub-routine that transmits any or all saved, input, and/or captured data (e.g., text details of a user's description of the accident, captured video/images of the accident scene, optically-recognized character information from image data, recorded statement data, scene diagram data, etc.) to a remote server (not shown; e.g., the server 110, 310 of FIG. 1 and/or FIG. 3 herein).” [Par 56-57] “In some embodiments, dynamic diagramming feedback may prompt the user to identify each vehicle (or other object) involved, prompt the user to assign vector input to a graphical representation of a diagrammed vehicle, and/or provide graphical element relocation guidance (e.g., not permit a user to diagram a vehicle off of a travel way (or apply other graphical and/or spatial diagramming constraints). In the case that a user draws/places a graphical representation of a vehicle in a lake, field, and/or conflicting with a building location, for example, the user may be prompted to confirm that the conflicting (or unusual) location is indeed the desired location. In some embodiments, in the case that the input is determined to comply with stored constraints/criteria at 418D, the method 400 may proceed to determine whether additional input is required, at 418E. In the case that additional input is needed, the method 400 may proceed back to provide input guidance at 418A. The method 400 may, for example, loop through capturing of accident inputs at 418 by first guiding a user through acquiring adequate documentary imagery of an accident/event, then acquiring an adequate quantity and content for recorded statements, then through a self-diagramming accident/scene sketching process. In some embodiments, once each of these (or fewer or more desired input actions) is accomplished, the method 400 may proceed. In some embodiments, any or all user input may be automatically uploaded and/or mapped to various respective form fields into one or more third-party websites and/or forms (such as a police FR-10 Form) to automatically order copies of official reports (e.g., police reports) and/or other incident/accident-related data.”)([Par 17] “In some embodiments, the user device 102a may comprise one or more devices owned and/or operated by one or more users, such as an automobile (and/or other vehicle, liability, personal, and/or corporate insurance customer) insurance customer (e.g., insured) and/or other accident victim and/or witness. According to some embodiments, the user device 102a may communicate with the server 110 via the network 104 to provide evidence and/or other data descriptive of an accident event and/or accident scene (e.g., captured images of damage incurred, recorded statements, and/or scene diagram(s)), as described herein” [Par 33] “According to some embodiments, the mobile electronic device 302 (and/or the display screen 318a thereof) may output a GUI 320 that provides output from and/or accepts input for, a mobile device application executed by the mobile electronic device 302. According to some embodiments, the application may comprise a web-interface application, such as a web browser that provides the GUI 320 based on webpages and/or data served by the server 310.”) ([Par 8] “ FIG. 5A, FIG. 5B, FIG. 5C, and FIG. 5D are diagrams of a system depicting example interfaces according to some embodiments;”)
Farmer does not explicitly teach generate a simulation of the vehicle incident using a physics engine, the simulation taking into account information about the incident; dynamically visualize the simulation; provide, with the dynamically visualized simulation, features that allow enable the user to confirm an accuracy of the simulation, and provide additional information; processing an indication as to whether the simulation is accurate; generate, based at least in part on the additional information, a dynamic simulation of the vehicle incident using the physics engine; and process data to dynamically visualize the dynamic simulation generated based at least in part on the additional information.
Cardona makes obvious generate a simulation of the vehicle incident using a physics engine, the simulation taking into account information about the incident; ([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.”) dynamically visualize the simulation; ([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.” [Col 8 line 13-18] “The VFA computing device may generate a simulation including a scene model depicting the scene of the collision. The scene model may be based upon, for example, map data and contextual data and enables individuals not present at the scene of the collision (e.g., insurance claims employees) to visualize the scene.” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Col 28 line48-52] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact.”) ([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.” [Col 8 line 13-18] “The VFA computing device may generate a simulation including a scene model depicting the scene of the collision. The scene model may be based upon, for example, map data and contextual data and enables individuals not present at the scene of the collision (e.g., insurance claims employees) to visualize the scene.” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Col 28 line48-52] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact.”) , a dynamic simulation of the vehicle incident using the physics engine; and process data to dynamically visualize the dynamic simulation ([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.” [Col 8 line 13-18] “The VFA computing device may generate a simulation including a scene model depicting the scene of the collision. The scene model may be based upon, for example, map data and contextual data and enables individuals not present at the scene of the collision (e.g., insurance claims employees) to visualize the scene.” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Col 28 line48-52] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact.”)
Cardona is analogous art because it is within the field of accident simulation for insurance purposes. It would have been obvious to one of ordinary skill in the art to combine it with Farmer before the effective filing date. One of ordinary skill in the art would have been motivated to make this combination in order to verify and validate information provided by individuals involved in a crash or accident. Vehicle accidents can happen rapidly, and leave those involved in shock. This can lead to an inaccurate recollection of events, making proper determination of liability difficult. As suggested by Cardona, this can lead to inaccurate, costly, and time consuming process ([Col 1 line 39-53] “Further, the process may include insurance claims employees receiving statements from drivers involved in the collision. Claims employees may often interpret and paraphrase such driver statements for a particular claims file. These statements given by drivers are based upon the driver's recollection of the accident, and may or may not be totally accurate. Further, paraphrasing the driver's statement by a claims employee may add additional error to the driver's account of the accident. Claims employees use this information to attempt to determine the events leading to the collision. For example, in some cases, claims employees will actually use toy cars to reconstruct accidents and points of contact for insurances claims processing. This process may be highly manual, costly, and prone to human error.”) To this end, Cardona introduces a system capable of automating the validation of reports given by witnesses, ([Col 4 line 26-32] “As described below, the systems and methods described herein generate a simulation of a vehicle collision. By so doing, the systems and methods enable a determination of the events leading to the vehicle collision. Further, the systems and methods may verify eyewitness accounts of the vehicle collision, and may enable a determination of the cause of the vehicle collision.”) cross-referencing statements with each other to find contractions as well as employing a physics-based collision simulations to determine if the reported series of events are physically possible ([Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision. For example, VFA computing device 102 may apply information regarding the coefficient of friction of the road surface and the mass of a vehicle to determine a maximum capability of the vehicle to decelerate. If, for example, speech data indicates that the vehicle decelerated at a faster rate than is physically possible, VFA computing device 102 may disregard the conflicting speech data when simulating the collision. The simulation thus may more accurately reflect the actual behavior of the vehicle in the collision.” [Col 14 line 62-67] “ VFA computing device 102 may disregard speech data that VFA computing device 102 determines to be conflicting. Thus, the simulation may conform as close as possible to an eyewitness statement while maintaining a physically accurate depiction of the collision.”) Overall, one of ordinary skill in the art would have recognized that combining Farmer with Cardona would produce a system capable of not only collecting comprehensive reports from witnesses of a crash using intuitive interfaces, but also validating those reports against simulations of the crash to give insurance workers the most accurate information possible for determining fault and liability in an accident.
The combination of Farmer and Cardona does not explicitly teach provide, with the dynamic visualization, features that allow enable the user to confirm an accuracy of the visualization, and provide additional information; processing an indication as to whether the visualization is accurate; generate, based at least in part on the additional information, a dynamic visualization of the vehicle incident; process data to dynamically visualize the dynamic visualization generated based at least in part on the additional information.
Serrao makes obvious provide, with the dynamic visualization, features that allow enable the user to confirm an accuracy of the visualization, and provide additional information; processing an indication as to whether the visualization is accurate; generate, based at least in part on the additional information, a dynamic visualization of the vehicle incident; process data to dynamically visualize the dynamic visualization generated based at least in part on the additional information. ([Col 5 line 61 – Col 6 line 31] “Next, in step 410, accident reconstruction system 190 may generate an animated video of the accident using the accident data. This process is described in further detail below and shown in FIG. 5. In some cases, accident reconstruction system 190 may also generate a 3D model as part of, or in parallel with, generating the animated video. For example, in some embodiments a system first generates a dynamic 3D model of an accident, including the vehicles or other objects involved in the accident, and then uses that model as the basis for rendering an animated video to represent the sequence of events. In step 412, system 110 may present the animated video to a user. The user in this context could be a driver of the vehicle or another occupant. The animated video could be displayed on a display of the vehicle, or could be sent to the user's mobile device for viewing. … Next, in step 414, system 110 may have the user confirm that the animated video is sufficiently accurate. If the user does not feel the animation is accurate, the system may modify the video in step 416 and then return to step 412 to present the modified video to the user. To improve the accuracy of the video, the system may also change the accident data used by the model by adding additional data sources and/or removing others… In step 418, after the accuracy of the animated video is confirmed by the user, system 110 may send the accident data to remote server 350.”)
Serrao is analogous art because it is within the field of vehicle accident visualization and recreation. It would have been obvious to one of ordinary skill in the art to combine it with Farmer and Cardona before the effective filing date. One of ordinary skill in the art would have been motivated to make this combination in order to more accurately produce accident recreations, as well as prevent further damage to a vehicle between the time of the accident and the time rescuers or insurance personnel can arrive. Firstly, Serrao notes how, frequently, insurance carriers are not the first people contacted following an accident, and consequently, between the trauma of an accident occurring and normal forgetting of memories over time the information eventually relayed to an insurance representative may be misremembered or inaccurate. ([Col 1 Line 22 – Line 35] “Following an accident, a driver may or may not call their insurance carrier to provide details about the accident. If an accident is reported, it is a very time consuming process. In addition, the driver may forget or misremember details about the accident. The driver may also be in a physical or mental state that prevents them from providing accurate details about incidents before, during or after the accident. The representative of the insurance carrier may therefore obtain an inaccurate understanding of how the accident occurred and what damage has occurred to the vehicle. This inaccuracy can lead to delays in claim processing, inaccurate damage estimates, multiple inspections, as well as additional costs to both the insurance provider and the driver in some cases.”) To this end, Serrao introduces a system for generating an accident recreation from sensor data and allowing a user to review the recreation of the accident to confirm the recreation’s accuracy or otherwise adjust data sources until the recreation matches reality. ([Col 5 line 61 – Col 6 line 31] “Next, in step 410, accident reconstruction system 190 may generate an animated video of the accident using the accident data. This process is described in further detail below and shown in FIG. 5. In some cases, accident reconstruction system 190 may also generate a 3D model as part of, or in parallel with, generating the animated video. For example, in some embodiments a system first generates a dynamic 3D model of an accident, including the vehicles or other objects involved in the accident, and then uses that model as the basis for rendering an animated video to represent the sequence of events. In step 412, system 110 may present the animated video to a user. The user in this context could be a driver of the vehicle or another occupant. The animated video could be displayed on a display of the vehicle, or could be sent to the user's mobile device for viewing. … Next, in step 414, system 110 may have the user confirm that the animated video is sufficiently accurate. If the user does not feel the animation is accurate, the system may modify the video in step 416 and then return to step 412 to present the modified video to the user. To improve the accuracy of the video, the system may also change the accident data used by the model by adding additional data sources and/or removing others… In step 418, after the accuracy of the animated video is confirmed by the user, system 110 may send the accident data to remote server 350.” [Col 6 line 42 – Line 67] “Once the accident data is received at remote server 350 in step 420, remote server 350 may reconstruct the animated video of the accident in step 422. … Next, in step 424, the animated video may be presented to a representative to facilitate review of the accident. Specifically, in some cases, the representative could be a representative of an insurance company that provides coverage for the vehicle. In some cases, upon receiving the animated video of the accident, the representative could call the user of vehicle 100 to review the accident and gather any relevant information in step 426. Finally, the animated video and/or underlying raw accident data could be sent to other parties in step 428. As one example, an animated video of a collision could be sent to a repair facility to provide a visual image of the type of damage expected for the vehicle prior to its arrival at the repair facility. This process of reviewing a reconstructed video of an accident based on sensed data may provide increased accuracy for reporting accidents over alternative methods that rely on user's to manually recall events from memory. Moreover, once the user confirms that the video is sufficiently accurate, the video can serve as a more reliable store of accident information than the user's long-term memory.”) This combination of sensor-derived data with user input and review ultimately results in an accident recreation that is more accurate than either a purely sensor-derived or purely testimony-derived recreation would be on its own. Further, Serrao notes how certain types of damage may cause vehicles to continue to damage themselves following an accident, which could lead to additional costs and maintenance; to this end, Serrao presents a control system that uses the recreation to determine if the vehicle has damage that would cause it to be an immediate risk to itself and takes action to prevent that risk. ([Col 9 line 37 – line 62] “An accident reconstruction system can include provisions for mitigating further damage after an accident has occurred. … In step 1206, the system assesses the damage vehicle components and systems based on the model (or animation). The system then determines if there is a risk of further damage to any components (or system) in step 1208. If there is no further risk of damage, the system may take no further actions as in step 1209. If there is a risk of further damage, the system may modify the control of one or more vehicle systems to mitigate further damage in step 1210… As one example of damage mitigation, an accident reconstruction system could assess the state of an engine following an accident. By analyzing a 3D model of the accident and/or images from an animated video, the accident reconstruction system could determine that the engine is severely damaged and there is further risk of damage if the engine keeps running in an idle mode. In this case, the accident reconstruction system could actively control one or more engine control systems, such as the fuel injection system, to stop fuel from being injected into the cylinders.”) Overall, one of ordinary skill in the art would have recognized that combining Serrao with Farmer and Cardona would result both in more accurate accident recreations as well as prevent any additional post-accident damage that could complicate later analysis or repair.
Claim 2. Farmer makes obvious generate the interactive contextual interface by generating a map interface of an incident location of the vehicle incident on which the claimant indicates the path of the at least one vehicle involved in the vehicle incident. ([Fig. 5D]) ([Par 71] “ In some embodiments, the fourth version (or page or instance) of the interface 520d may comprise an accident diagram webpage and/or GUI that permits, instructs, and/or guides a user/insured through constructing a diagram of an incident and/or accident scene. The fourth version of the interface 520d may comprise and/or represent, for example, a map-based diagram tool and/or a GUI vector drawing tool” [Par 71-72] “ The fourth version of the interface 520d may comprise and/or represent, for example, a map-based diagram tool and/or a GUI vector drawing tool. According to some embodiments, the fourth version of the interface 520d may be generated by GUI diagram program code that pre-loads a geo-referenced map image, e.g., as depicted in FIG. 5D. In some embodiments, the map image may comprise the map-based diagram that permits the user to provide input defining one or more points, areas, and/or objects on the generated map image/layer… In some embodiments, the GUI vector drawing tool may be utilized by the user to provide (e.g., via the user device 502 and/or the fourth version of the interface 520d) first vector input that defines a first location on the map and/or a first direction (and/or speed; e.g., a vector). According to some embodiments, the first vector input may be provided in conjunction with and/or utilizing a common GUI object selection tool or library. As depicted in FIG. 5D, for example, the fourth version of the interface 520d may comprise a common GUI object selection area 524 that stores and displays a plurality of common GUI objects, such as those representing various vehicles and objects that may be desired for placement on the map image”)
Claim 3. Farmer makes obvious determine one or more individuals, other than the claimant, that have been involved in the vehicle incident based on a claim initiated by a claimant. ([Par 36] “Further, the user/insured may utilize a second drop-down menu element 344-2b to view a listing of drivers (or other individuals) associated with the policy number 344a in the database 340 and/or to select (and/or enter additional) one or more appropriate drivers/individuals, e.g., involved in an accident. In such a manner, for example, in the case that the information captured and identified from the insurance card 332 is accurate, a claim reporting application of the electronic mobile device 302 (and/or a web-based GUI 320 served by the server 310) may be pre-loaded with appropriate policy-related data (e.g., from the database 340)” [Par 41] “According to some embodiments, the login webpage may comprise instructions requesting login credentials and/or data from a user/user device. The login webpage may, for example, be output via the user device and/or GUI thereof and may prompt the user to activate a camera of the user's device and capture an image of an insurance and/or other identification card.”[Par 44] “The insurance policy (and/or other identification data) derived from the image data received from the user device may, for example, be utilized to authorize access to accident and/or claim submission functionality offered by or via the webserver (and/or associated application).” [Par 54] “According to some embodiments, image, video, audio, and/or diagramming evidence may be analyzed to calculate estimated distances between objects at the accident scene and/or orientations and/or positions of objects at or near the scene. Image analysis may include object, facial, pattern, and/or spatial recognition analysis routines that, e.g., identify individuals at the scene, identify vehicles at the scene, identify roadway features, obstacles, weather conditions, etc”)
Claim 4. Farmer makes obvious generate a contextual flow comprising a set of user interface features that enable the claimant to provide contextual information corresponding to the vehicle incident, the set of user interface features being presented on a computing device of the claimant as part of the interactive contextual interface. ([Fig. 5C] Shows a user interface enabling a claimant to provide contextual information. Note that the bottom options are a sequential checklist [Par 70] “In some embodiments, one or more options of the accident checklist 520-11 may generate additional interface versions, screens, and/or GUI elements (not shown) defined by stored data input guidance rules. The “Take pictures of your damage” option 520-15 and/or the “Take pictures of other damage” option 520-16 may, upon a triggering and/or receipt of input from the user (e.g., a properly-positioned click of a mouse or other pointer) with respect to the “Take pictures of your damage” option 520-15 and/or the “Take pictures of other damage” option 520-16, respectively, initiate a sub-routine that may trigger a call to and/or otherwise cause a provision, generation, and/or outputting of image capture guidance rules (not shown). Such rules may, in some embodiments, actively guide a user through capturing each required item of image data.. According to some embodiments, the “Record Statement(s)” option 520-17 may, upon a triggering and/or receipt of input from the user (e.g., a properly-positioned click of a mouse or other pointer) with respect to the “Record Statement(s)” option 520-17, initiate a sub-routine that may trigger a call to and/or otherwise cause a provision, generation, and/or outputting of guidance that steps the user through recording audio statements of one or more accident witnesses by prompting the user to ask the witness certain questions.”)
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Claim 5. Farmer makes obvious receive contextual information from the computing device of the claimant based on input data corresponding to the claimant interacting with the set of user interface features. ([Fig. 5C] Shows a user interface enabling a claimant to provide contextual information. [Par 31] “The app may include, comprise, and/or cause the generation of the GUI 220, which may be utilized, for example, for transmitting and/or exchanging data through and/or via a network (not shown in FIG. 2; e.g., the Internet). In some embodiments, once the app receives captured data from an input device 216a-b, the app in turn transmits the captured data through a first interface for exchanging data (not separately depicted in FIG. 2) and through the network.” [Par 70] “In some embodiments, one or more options of the accident checklist 520-11 may generate additional interface versions, screens, and/or GUI elements (not shown) defined by stored data input guidance rules. The “Take pictures of your damage” option 520-15 and/or the “Take pictures of other damage” option 520-16 may, upon a triggering and/or receipt of input from the user (e.g., a properly-positioned click of a mouse or other pointer) with respect to the “Take pictures of your damage” option 520-15 and/or the “Take pictures of other damage” option 520-16, respectively, initiate a sub-routine that may trigger a call to and/or otherwise cause a provision, generation, and/or outputting of image capture guidance rules (not shown). Such rules may, in some embodiments, actively guide a user through capturing each required item of image data ... According to some embodiments, the “Record Statement(s)” option 520-17 may, upon a triggering and/or receipt of input from the user (e.g., a properly-positioned click of a mouse or other pointer) with respect to the “Record Statement(s)” option 520-17, initiate a sub-routine that may trigger a call to and/or otherwise cause a provision, generation, and/or outputting of guidance that steps the user through recording audio statements of one or more accident witnesses by prompting the user to ask the witness certain questions.”)
Claim 8. Farmer makes obvious wherein the one or more individuals other than the claimant comprise at least one of a witness to the vehicle incident, a party to the vehicle incident, or a driver of another vehicle involved in the vehicle incident. ([Par 58]”Image analysis may include object, facial, pattern, and/or spatial recognition analysis routines that, e.g., identify individuals at the scene, identify vehicles at the scene, identify roadway features, obstacles, weather conditions, etc” [Par 36] “In some embodiments, the GUI 320 may comprise one or more drop-down menu elements 344-2a, 344-2b that permit the user/insured to provide input indicating a selection of one of a plurality of available data options. In the case of the vehicle 344b and the driver 344c, for example, the user/insured may utilize a first drop-down menu element 344-2a to view a listing of vehicles (and/or other objects; e.g., insured objects) associated with the policy number 344a in the database 340 and/or to select (and/or enter additional) one or more appropriate vehicles (and/or other objects), e.g., involved in an accident. Further, the user/insured may utilize a second drop-down menu element 344-2b to view a listing of drivers (or other individuals) associated with the policy number 344a in the database 340 and/or to select (and/or enter additional) one or more appropriate drivers/individuals, e.g., involved in an accident.” [Par 70] “According to some embodiments, the “Record Statement(s)” option 520-17 may, upon a triggering and/or receipt of input from the user (e.g., a properly-positioned click of a mouse or other pointer) with respect to the “Record Statement(s)” option 520-17, initiate a sub-routine that may trigger a call to and/or otherwise cause a provision, generation, and/or outputting of guidance that steps the user through recording audio statements of one or more accident witnesses by prompting the user to ask the witness certain questions.”)
Claims 9-13 and 16. The elements of claims 9-13 and 16 are substantially the same as those of claims 1-5 and 8. Therefore, the elements of claim 9-13 and 16 are rejected due to the same reasons as outlined above for claims 1-5 and 8. Further, Farmer makes obvious the additional elements of “A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:” ([Par 39] “Any of the processes and methods described herein may be performed and/or facilitated by hardware, software (including microcode), firmware, or any combination thereof. For example, a storage medium… may store thereon instructions that when executed by a machine (such as a computerized processor) result in performance according to any one or more of the embodiments described herein”)
Claims 17-20. The elements of claims 17-20 are substantially the same as those of claims 1-4. Therefore, the elements of claim 17-20 are rejected due to the same reasons as outlined above for claims 1-4.
(2) Claims 6-7 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Farmer (US 20210004909 A1) in view of Cardona (US 11308741 B1) in further view of Serrao (US 11620862 B1) as well as Lopez (US 12374035 B1)
Claim 6. Farmer teaches the instructions, when executed by the one or more processors, cause the computing system to further: ([Par 19] “The network 104 may, according to some embodiments, comprise a Local Area Network (LAN; wireless and/or wired), cellular telephone, Bluetooth® and/or Bluetooth Low Energy (BLE), Near Field Communication (NFC), and/or Radio Frequency (RF) network with communication links between the server 110, the user device 102a, the vehicle 102b, the third-party device 106, the sensors 116a-b, and/or the memory 140.”) ([Fig. 5D])
Cardona makes obvious ([Col 2 line 6-14] “determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time;” [Col 16 line 1-16] “VFA computing device 102 may apply physics data to other data, (e.g., map data, contextual data, and vehicle specification data) to determine physical constraints for the simulation corresponding to realistic physics of the collision.” [Col 8 line 44-52] “To simulate the collision, the VFA computing device may determine the position and orientation of one or more vehicles involved in the collision for a plurality of moments in time during the collision. The VFA computing device may simulate the collision based upon, for example, speech data and/or vehicle telematics data. The VFA computing device may further use additional data to simulate the collision (e.g., vehicle specification data, photographic data, text data, and/or physics data).” [Col 9 line 13-35] “Additionally or alternatively, the VFA computing device may determine the position and orientation of the vehicle based upon vehicle telematics data. Vehicle telematics data includes data retrieved from a sensor-equipped vehicle involved in the collision (e.g., an AV) or a device onboard a vehicle involved in the collision (e.g., a mobile phone device or a telematics device installed by an insurance company). Vehicle telematics data may include data derived from, for example, an accelerometer, gyroscope, or GPS device, and indicate the position, yaw, speed, acceleration, deceleration, braking, cornering, and other characteristics of the vehicle's motion and orientation. Such vehicle telematics data may be used by the VFA computing device to determine the behavior of the vehicle from which it is derived during the collision. To generate the simulation, the VFA computing device may generate a representation of the vehicle from which the vehicle telematics data was received that behaves in accordance with the telematics data (e.g., the simulated vehicle appears to move and change orientation in accordance with the telematics data). The simulation thus reflects the actual behavior of the vehicle in the collision and enables analysis of the collision even in cases where no eyewitnesses are available or present at the scene of the collision.” )
The combination of Farmer, Cardona, and Serrao does not explicitly teach render multiple different views of the simulation
Lopez makes obvious render multiple different views of the simulation ([Col 11 line 29 – Col 12 line 8] “ Thus, in some embodiments, the system can automatically arrange the elements in space based on keyword analysis, thereby rendering a schematic scene of the accident according to the testimony. In one embodiment, the generative engine can also include damage done to the vehicle(s) following the collision. In some cases, the scene generated could be animated and/or otherwise dynamic. For purposes of illustration and clarity, the drawing depicts an accident simulation as viewed from above. However, in other embodiments, the accident could be rendered from any other viewpoint, such as the driver's viewpoint, an external viewpoint or any other viewpoint. In some cases, a model is generated first, and then the model may be rendered from a particular view to create the simulation. in different embodiments, the system can be configured to further generate data representing injuries to the claimant or others involved in the accident based on key word analysis. FIGS. 6 and 7 present an additional example in which other types of accident-related details may be characterized by the system. ... In some embodiments, the accident may also be shown in a different perspective 750 to better illustrate how such an injury might have occurred or is described as occurring. [Fig. 7] Shows an example simulation. As can be seen, the accident is rendered in multiple views)
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Lopez is analogous art because it is within the field of vehicle accident simulation for insurance purposes. It would have been obvious to one of ordinary skill in the art to combine it with Farmer, Cardona, and Serrao before the effective filing date. One of ordinary skill in the art would have been motivated to make this combination in order to better determine the reliability of the claimant, and therefore produce a more accurate insurance assessment. Lopez notes how individuals involved in accidents can be in shock or misremember events, causing them to relay inaccurate information about the accident there leading to inaccurate insurance assessments ([Col 1 line 14-34] “ Following an accident, a driver may or may not call their insurance carrier immediately to provide details about the accident. When an accident is reported to the insurance carrier, it is typically a very time-consuming process. In addition, the driver may forget or misremember details about the accident, leading to an inaccurate assessment of damage. The driver may also be in a physical or mental state that prevents them from providing accurate details about incidents before, during or after the accident, and inconsistencies in the report may delay the processing of the claim. In some cases, claimants may provide details that are inconsistent to the damage or injuries reported, but these details may be overlooked by an investigator when reviewing the case. In addition, the insurer may not necessarily be able to distinguish all of the significant details about the accident from the driver's report. The representative of the insurance carrier may therefore obtain an inaccurate understanding of how the accident occurred and what damage has occurred to the vehicle. This inaccuracy can lead to inaccurate damage estimates, multiple inspections, as well as additional costs to both the insurance provider and the driver in some cases.”) To this end, Lopez presents a method for detecting inconsistencies in insurance reports and giving insurance agents more tools and addition information for determining fault ([Col 3 line 18-39] “The embodiments provide a system and method for generating a static or animated video and/or a three-dimensional model (i.e., “3D model”) of an accident involving one or more vehicles. The virtual representations can be constructed from data retrieved from claimant testimony as well as eyewitness testimony and police reports, vehicle telemetry, images, and other data obtained from or about the site of the accident. For example, in some embodiments, the disclosed systems can apply one or more machine-learning models to analyze claimant testimony about an accident and then automatically generate 2D or 3D images of key words as graphic elements, such as vehicles, drivers, passengers, and the surrounding environment. In some cases, the embodiments of the proposed systems can be configured to arrange the elements in space based on key word analysis, thereby rendering a schematic scene of the accident according to the testimony. The model can also demonstrate damage done to the vehicle(s) following the collision. In addition, in some embodiments, the system can be configured to detect inconsistencies between witness reports of the accident and vehicle telemetry and/or images taken of the accident.” [Col 3 line 54- Col 4 line 2] “This generated information can be used by interested parties to better understand the location of impact and the damage to the vehicles, as well as about how the crash occurred. For example, by identifying the various points of damage on the automobile, an investigator can work backward to determine how the accident may have happened. In some cases, the damage depiction can significantly affect the results of an insurance or civil claim, underscoring the need for accurate representation of the damage. In other cases, the vehicle damage can allow the investigator to rule out ways that the accident could not have occurred. This type of visual representation of the accident report details can offer insights and clarity regarding the incident that are far greater than what conventional case reviews can provide.” [Col 11 line 55- Col 12 line 8] “In this case, the example keywords 630 or phrases that have been detected include “Teenage daughter”, “arm broken”, and “concussion”. In FIG. 7, these keywords 630 as well as other data can then be fed to generative engine 510 that can automatically produce additional 2D or 3D images of elements in the context of the previous information, in this case providing a new simulation element 740 that depicts a woman 720 with a broken arm 730. In some embodiments, the accident may also be shown in a different perspective 750 to better illustrate how such an injury might have occurred or is described as occurring. In some other examples, the injury data can be compared to the predictive model data to see if the injuries are consistent with the damage done to the vehicle. In one example, the system could simulate an occupant in the vehicle during the collision, based on the model, and determine likely injuries that may occur. If the claimant's purported injuries do not match any injuries on this list, the system could recommend further investigation by a human investigator (e.g., see FIG. 9).”) Overall, one of ordinary skill in the art would have recognized that combining Lopez with Farmer, Cardona, and Serrao would allow for even deeper investigation and analysis of accidents along with additional consistency checks, ultimately enabling more accurate insurance assessments to be made.
Claim 7. Farmer makes obvious wherein the executed instructions further cause the computing system to: ([Par 70] “In some embodiments, one or more options of the accident checklist 520-11 may generate additional interface versions, screens, and/or GUI elements (not shown) defined by stored data input guidance rules. The “Take pictures of your damage” option 520-15 and/or the “Take pictures of other damage” option 520-16 may, upon a triggering and/or receipt of input from the user (e.g., a properly-positioned click of a mouse or other pointer) with respect to the “Take pictures of your damage” option 520-15 and/or the “Take pictures of other damage” option 520-16, respectively, initiate a sub-routine that may trigger a call to and/or otherwise cause a provision, generation, and/or outputting of image capture guidance rules (not shown). Such rules may, in some embodiments, actively guide a user through capturing each required item of image data… According to some embodiments, the “Record Statement(s)” option 520-17 may, upon a triggering and/or receipt of input from the user (e.g., a properly-positioned click of a mouse or other pointer) with respect to the “Record Statement(s)” option 520-17, initiate a sub-routine that may trigger a call to and/or otherwise cause a provision, generation, and/or outputting of guidance that steps the user through recording audio statements of one or more accident witnesses by prompting the user to ask the witness certain questions.” [Par 44] “The insurance policy (and/or other identification data) derived from the image data received from the user device may, for example, be utilized to authorize access to accident and/or claim submission functionality offered by or via the webserver (and/or associated application).”)
Cardona makes obvious validate or invalidate accident information ([Col 4 line 26-32] “As described below, the systems and methods described herein generate a simulation of a vehicle collision. By so doing, the systems and methods enable a determination of the events leading to the vehicle collision. Further, the systems and methods may verify eyewitness accounts of the vehicle collision, and may enable a determination of the cause of the vehicle collision.”) using the visualized simulation of the vehicle incident. ([Col 28 line 48-60] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact. Based upon the vehicle details in the file, the application may be configured to use real world and validated vehicle physical and engineering specifications related to gross weight, acceleration, deceleration, crump zones, etc.” [Col 8 line 13-18] “The VFA computing device may generate a simulation including a scene model depicting the scene of the collision. The scene model may be based upon, for example, map data and contextual data and enables individuals not present at the scene of the collision (e.g., insurance claims employees) to visualize the scene.” [Col 9 line 1-7] “Based upon the speech data, the VFA computing device may generate visual representations of vehicles involved in the accident based upon the determined positions and orientations of the vehicles over the course of the collision. For example, the visual representations may appear to move and come into contact in a manner as described in the speech data.” [Col 28 line48-52] “The present embodiments may also provide a collision physics simulator. The application would upload in real time the details of the accident into the collision simulator to recreate a video of the path of the vehicles and point of contact.”)
Claims 14-15. The elements of claims 14-15 are substantially the same as those of claims 6-7. Therefore, the elements of claim 14-15 are rejected due to the same reasons as outlined above for claims 6-7. Further, Farmer makes obvious the additional elements of claim 9 as inherited by claims 14-15, particularly: “A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:” ([Par 39] “Any of the processes and methods described herein may be performed and/or facilitated by hardware, software (including microcode), firmware, or any combination thereof. For example, a storage medium… may store thereon instructions that when executed by a machine (such as a computerized processor) result in performance according to any one or more of the embodiments described herein”)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael P Mirabito whose telephone number is (703)756-1494. The examiner can normally be reached M-F 10:30 am - 6:30 pm.
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/M.P.M./ Examiner, Art Unit 2187
/EMERSON C PUENTE/ Supervisory Patent Examiner, Art Unit 2187
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