DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “towing detector” and “towing lane assist system” in claims 16-20.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-14, and 16-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claims 1, 12 and 16relate to the statutory category of method/process and machine/apparatus. Independent claim 1 recites “providing, by a computing system comprising one or more processors, a smart towing assistant comprising the chatbot, wherein the chatbot is trained, based upon a training dataset, to engage in a conversation with a user in association with towing of a towable object by a vehicle; receiving, by the computing system, and via the chatbot during the conversation, user input comprising natural language input; generating, by the computing system, and via the chatbot, output based at least in part on the user input, wherein the output comprises natural language output that expresses the towing-related information; and presenting, by the computing system, and via the chatbot, the output during the conversation”. Independent claim 12 recites “receive, via the chatbot, and during a conversation associated with towing of a towable object by a vehicle, user input comprising natural language input, wherein the chatbot is trained on a training dataset; generate, via the chatbot, output based at least in part on the user input, wherein the output comprises natural language output that expresses the towing-related information; and present, via the chatbot, the output during the conversation”. Independent claim 16 recites “a chatbot trained, based upon a training dataset, to engage in a conversation with a user in association with towing of a towable object by the vehicle; a towing detector configured to detect, based upon sensor data associated with at least one of the vehicle or the towable object, towing activity associated with the towing of the towable object by the vehicle; and a towing lane assist system configured to: detect, based upon the sensor data, a safety issue associated with the towing of the towable object by the vehicle, and output an alert associated with the safety issue”.
The limitations of claim 1 of “providing…”, “receiving…”, “generating…”, and presenting…” as drafted covers mental activity. More specifically, a human having a conversation whether a vehicle should be towed. A user can look at the condition of the vehicle and determine if it is drivable or not and needs to be towed. The limitations of claim 12 of “receive…”, “generate…” and “present…” as drafted covers mental activity. More specifically, a human having a conversation whether a vehicle should be towed. A user can look at the condition of the vehicle and determine if it is drivable or not and needs to be towed. The limitations of claim 16 of “…engage…”, “…detect…”, “…detect…”, and “output…” as drafted covers mental activity. More specifically, a human can during a conversation, look at sensor data and determine if there is a safety issue. A user can determine if there is an issue with the vehicle and whether it needs to be towed.
This judicial exception is not integrated into a practical application. In particular, claims 1 and 12 recite the additional elements of “processors” and “ memory which are recited generally in the specification. For example “ in paragraphs [0162]-[0168] and Figure 5 of the as filed specification, there is a description of using a general computing system. Accordingly, these additional elements do not integrate the abstract idea int a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claims do not include additional elements that a sufficient to amount to significantly more than the judicial exception. As discussed above, with respect to the integration of the abstract idea int a practical application, the additional element of using a computer as a general computer is noted. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
With respect to claim 2, the claim relates to using a trained a model for the data. The claim relates to a mental activity of learning data. The additional element of using a generative pre-trained transformer (GPT) does not integrate any meaningful limits on the abstract idea.
With respect to claim 3, the claim relates to determining specific information about the vehicle and its insurance coverage. The claim relates to a mental activity of determining what the vehicle’s insurance covers. No additional limitations are present.
With respect to claim 4, the claim relates to identifying the vehicle that needs to be towed and outputting information about the vehicle wherein the output is based on the identity of the vehicle or what is being towed. The claim relates to a mental activity of determining information about the vehicle to be towed by identifying the vehicle or what is being towed. No additional limitations are present.
With respect to claims 5, the claim relates to identifying towing information about the vehicle. The claim relates to a mental activity of determining information about the vehicle to be towed. No additional limitations are present.
With respect to claim 6, the claim relates to gathering information (identification, images, and insurance information) about the vehicle. The claim relates to a mental activity of determining information about the vehicle to be towed. No additional limitations are present.
With respect to claim 7, the claim relates to determining how much knowledge the user has about towing based on the conversation and giving information based on how much knowledge the user has. The claim relates to a mental activity of determining during a conversation, a user’s knowledge and giving the user information based on that knowledge. No additional limitations are present.
With respect to claim 8, the claim relates to determining if the insurance policy covers towing. The claim relates to a mental activity of determining what the actual insurance coverage is.
With respect to claim 9, the claim relates to changing insurance information. The claim relates to a mental activity of updating the insurance coverage to include towing. No additional limitations are present.
With respect to claim 10 and 19, the claim relates to determining the cost of the towing. The claim relates to a mental activity of determining how much a user will be billed for towing based on their insurance coverage. No additional limitations are present.
With respect to claim 11 and 20, the claim relates to determining if the vehicle to be towed is in an area that will cause a collision with another object. The claims relates to a mental activity of determining if the vehicle to be towed is in the path of other objects and in danger of colliding with other objects. No additional limitations are present.
With respect to claim 13, the claim relates to the conversation being in either text or vocal via the onboard computing device. The claim relates to a mental activity of determining if you are communicating thru text or speech. The additional elements of whether the output is on a screen or thru a speaker do not integrate any meaningful limits on the abstract idea. These additional elements are directed towards insignificant extra solution activity, specifically, insignificant post solution activity.
With respect to claim 14, the claim relates to using a computer. As discussed above, with respect to the integration of the abstract idea int a practical application, the additional element of using a computer does not integrate any meaningful limits on the abstract idea. No additional limitations are present.
With respect to Claim 17, the claim relates to having a conversation about the vehicle that needs to be towed. The output of the conversation is determined based on whether the conversation includes towing information and the output is presented based on the conversation. The claim relates to a mental activity of having a discussion and determining the response based on the content of the discussion. No additional limitations are present.
With respect to Claim 18, the claim relates to keeping the conversation about the vehicle needs to be towed. The claim relates to a mental activity of keeping the discussion about towing and not veering off topic. No additional limitations are present.
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 1-8 and 12-15 are rejected under 35 U.S.C. 103 as being unpatentable over Pieraccini et al. (US 2024/0304184) in view of Watkins et al. (US 2020/0267503).
Regarding Claim 1, Pieraccini et al teaches a computer-implemented method for providing towing-related information via a chatbot, the method comprising: providing, by a computing system comprising one or more processors (one or more processors for accessing data and executing the software applications) (page 4, paragraph [0030]), wherein the chatbot is trained, based upon a training dataset (In some implementations, the given LLM behavior controller training instance for training the LLM behavior controller can be obtained from one or more databases (e.g., from training instance(s) database 171A). In some versions of these implementations, the training instance(s) database 171A can include training instances that are pre-curated and generated based on prior dialogs between users or users and respective automated assistants) (page 9, paragraph [0056]), to engage in a conversation with a user (Notably, the NL based input 201 can be provided as part of a given turn of an ongoing dialog between the user of the client device 110 and the automated assistant 115. The NL based input 201 can be provided by the user of the client device 110 to initiate the ongoing dialog or in furtherance of the ongoing dialog) (page 9, paragraph [0041]); receiving, by the computing system, and via the chatbot during the conversation, user input comprising natural language input (At block 454, the system receives NL based input from a user of a client device during a given dialog turn of an ongoing dialog between the user of the client device and the automated assistant that is accessible at the client device (e.g., as described with respect to the user input engine 111 of FIG. 1) (pages 10 and 11, paragraph [0067]); generating, by the computing system, and via the chatbot, output based at least in part on the user input, wherein the output comprises natural language output (At block 462, the system determines, based on the LLM output, a NL based response that is in the given NL based response style and that is responsive to the NL based input (e.g., as described with respect to the NL based response engine 185 of FIGS. 1 and 2)) (page 11, paragraph [0070]); and presenting, by the computing system, and via the chatbot, the output during the conversation (At block 464, the system causes the NL based response to be rendered at the client device) (page 11, paragraph [0071]).
Pieraccini et al fails to teach a method comprising: towing of a towable object by a vehicle and outputting information that expresses the towing-related information.
Watkins et al teaches a method comprising: towing of a towable object by a vehicle and outputting information that expresses the towing-related information (FIG. 8 illustrates a second screen 150 of the crash detection, response and reporting application after a request for assistance, depicting updated assistance information 152. This may include the time of dispatch 154 and an estimate time of arrival 156. The update field may also present (not illustrated) the contact information of the tow truck driver) (page 6, paragraph [0065]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by contacting the tow truck driver thru an app on your mobile device
Regarding Claim 2, Pieraccini et al teaches the method, wherein the chatbot is a generative pre-trained transformer (GPT) model trained on the training dataset (The LLM described herein can be any LLM (e.g., LaMDA, BERT, Meena, PaLM, GPT-3, GPT-4, etc.) that is capable of being utilized in processing NL based inputs and generating LLM outputs) (page 8, paragraph [0050]).
Regarding Claim 3, Pieraccini et al fails to teach the method, wherein the dataset comprises a training dataset ((In some implementations, the given LLM behavior controller training instance for training the LLM behavior controller can be obtained from one or more databases (e.g., from training instance(s) database 171A). In some versions of these implementations, the training instance(s) database 171A can include training instances that are pre-curated and generated based on prior dialogs between users or users and respective automated assistants) (page 9, paragraph [0056]).
Pieraccini et al fails to teach wherein the dataset comprises at least one of: manufacturer data indicating attributes of vehicles and towable objects, towing safety information approved by an insurance company, or insurance policy information associated with a set of insurance policies provided by the insurance company.
Watkins et al teaches the method, wherein the dataset (Further, the database 21 maintains driver information of driver name, address, insurance company and policy number for a plurality of drivers) (page 5, paragraph [0052]) (It is being interpreted by the examiner that the databases have been curated thru training so as to offer the user access to enormous amounts of data) comprises at least one of: manufacturer data indicating attributes of vehicles and towable objects (The information communicated by the application 14 includes the vehicle identification number, the driver information and contact phone number, and the location, time, and event) (page 6, paragraph [0063]), towing safety information approved by an insurance company, or insurance policy information associated with a set of insurance policies provided by the insurance company (The screen 130 displays the insurance window 122) (page 6, paragraph [0064]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by having access to all of necessary information needed thru an app on your mobile device.
Regarding Claim 4, Pieraccini et al teaches the method, further comprising: a chatbot (Humans may engage in human-to-computer dialogs with interactive software applications referred to herein as “automated assistants” (also referred to as “chatbots,” “interactive personal assistants,” “intelligent personal assistants,” “personal voice assistants,” “conversational agents,” etc.) (page 1, paragraph [0001])
Pieraccini et al fails to teach the method, further comprising: determining, by the computing system, an identity of at least one of the vehicle or the towable object, wherein the chatbot generates the output based at least in part on the identity of the at least one of the vehicle or the towable object.
Watkins et al teaches the method, further comprising: determining, by the computing system, an identity of at least one of the vehicle or the towable object (The information communicated by the application 14 includes the vehicle identification number, the driver information and contact phone number, and the location, time, and event) (page 6, paragraph [0063]), wherein the chatbot (The portable computer can be any of a number and/or combination of devices selected from among personal computers, personal digital assistant devices, portable computing devices, and portable communication devices, but is not so limited) (pages 13-14, paragraph [0107[) generates the output based at least in part on the identity of the at least one of the vehicle or the towable object (The screen 120 includes an insurance window 122 that displays the name and address of the insured; the make, model and vehicle identification number of the insured motor vehicle; and the insurance carrier and policy number) (page 6, paragraph [0062]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by having access to all of necessary information needed thru an app on your mobile device.
Regarding Claim 5, Pieraccini et al fails to teach the method, wherein the output expresses towing-related safety information based at least in part on attributes of the at least one of the vehicle or the towable object indicated by manufacturer data.
Watkins et al teaches the method, wherein the output expresses towing-related safety information based at least in part on attributes of the at least one of the vehicle or the towable object indicated by manufacturer data (The information communicated by the application 14 includes the vehicle identification number, the driver information and contact phone number, and the location, time, and event) (page 6, paragraph [0063]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by having access to all of necessary information needed thru an app on your mobile device.
Regarding Claim 6, Pieraccini et al fails to teach the method, wherein the computing system determines the identity of at least one of the vehicle or the towable object based upon at least one of: a user-provided description, image analysis of a user-provided photograph of the at least one of the vehicle or the towable object, or insurance policy information associated with the at least one of the vehicle or the towable object.
Watkins et al teaches the method, wherein the computing system determines the identity of at least one of the vehicle or the towable object based upon at least one of: a user-provided description, image analysis of a user-provided photograph of the at least one of the vehicle or the towable object, or insurance policy information associated with the at least one of the vehicle or the towable object ((The screen 120 includes an insurance window 122 that displays the name and address of the insured; the make, model and vehicle identification number of the insured motor vehicle; and the insurance carrier and policy number) (page 6, paragraph [0062]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by having access to all of necessary information needed thru an app on your mobile device.
Regarding Claim 7, Pieraccini et al fails to teach the method, further comprising: estimating, by the computing system, a towing experience level of the user based at least in part on the user input received during the conversation, wherein the chatbot generates the output based at least in part on the towing experience level of the user.
Watkins et al teaches the method, further comprising: estimating, by the computing system, a towing experience level of the user based at least in part on the user input received during the conversation, wherein the chatbot generates the output based at least in part on the towing experience level of the user (The communications network of the comprehensive crash event and claims servicing system provides communications facilities and protocols on a bidirectional basis, to obtain data and claim status from all persons and entities involved in the crash/tow/claim solution) (page 13, paragraph [0103]) (It is being interpreted by the examiner that during the bidirectional communication, the knowledge that the user has about the towing experience can be gathered.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by communicating all of necessary information that is known about the towing of the vehicle thru an app on your mobile device.
Regarding Claim 8, Pieraccini et al fails to teach the method, wherein the output expresses towing insurance coverage information indicating whether an insurance policy covers the towing of the towable object by the vehicle.
Watkins et al teaches the method, wherein the output expresses towing insurance coverage information indicating whether an insurance policy covers the towing of the towable object by the vehicle (The disclosed communications hub 186 coordinates the processing of the insurance claim and vehicle disposition information, which information is derived by integrations to the data base, from the fleet bub or by other electronic means via appropriate APIs … as well as towing services (which companies may be independent or networked within the disclosed comprehensive crash event and claims servicing system) (page 13, paragraph [0102]) (It is being interpreted by the examiner that if the insurance policy covers the towing, then the networked companies will address the towing because they are within network for towing, just like within network for health insurance.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by communicating all of necessary insurance information thru an app on your mobile device.
Regarding Claim 12, Pieraccini et al teaches a computing system configured to provide towing-related information via a chatbot, the computing system comprising: one or more processors (one or more processors for accessing data and executing the software applications) (page 4, paragraph [0030]), and memory storing computer-executable instructions (one or more memories for storage of data and/or software applications) (page 4, paragraph [0030]) that, when executed by the one or more processors, cause the one or more processors to: receive, via the chatbot, and during a conversation associated with user input comprising natural language input (At block 454, the system receives NL based input from a user of a client device during a given dialog turn of an ongoing dialog between the user of the client device and the automated assistant that is accessible at the client device (e.g., as described with respect to the user input engine 111 of FIG. 1) (pages 10 and 11, paragraph [0067]) , wherein the chatbot is trained on a training dataset (In some implementations, the given LLM behavior controller training instance for training the LLM behavior controller can be obtained from one or more databases (e.g., from training instance(s) database 171A). In some versions of these implementations, the training instance(s) database 171A can include training instances that are pre-curated and generated based on prior dialogs between users or users and respective automated assistants) (page 9, paragraph [0056]); generate, via the chatbot, output based at least in part on the user input, wherein the output comprises natural language output (At block 462, the system determines, based on the LLM output, a NL based response that is in the given NL based response style and that is responsive to the NL based input (e.g., as described with respect to the NL based response engine 185 of FIGS. 1 and 2)) (page 11, paragraph [0070]); and present, via the chatbot, the output during the conversation (At block 464, the system causes the NL based response to be rendered at the client device) (page 11, paragraph [0071]).
Pieraccini et al fails to teach a computing system comprising: towing of a towable object by a vehicle and outputting information that expresses the towing-related information.
Watkins et al teaches a computing system comprising: towing of a towable object by a vehicle and outputting information that expresses the towing-related information (FIG. 8 illustrates a second screen 150 of the crash detection, response and reporting application after a request for assistance, depicting updated assistance information 152. This may include the time of dispatch 154 and an estimate time of arrival 156. The update field may also present (not illustrated) the contact information of the tow truck driver) (page 6, paragraph [0065]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Watkins to improve insurance claim resolution during a traffic accident by contacting the tow truck driver thru an app on your mobile device.
Regarding Claim 13, Pieraccini et al teaches the system, wherein: the computing system is an on-board computing system of the vehicle (a computing device of a vehicle (e.g., an in-vehicle communications system, an in-vehicle entertainment system, an in-vehicle navigation system)) (page 4, paragraph [0025]), the chatbot (The client device 110 can execute an automated assistant client 114) (page 4, paragraph [0026]) receives the user input as at least one of text input or audio input via one or more input devices (For example, the client device 110 may be equipped with one or more microphones that capture audio data, such as audio data corresponding to spoken utterances of the user or other sounds in an environment of the client device 110) of the vehicle (a computing device of a vehicle (e.g., an in-vehicle communications system, an in-vehicle entertainment system, an in-vehicle navigation system)) (page 4, paragraph [0025]), and the chatbot presents the output as at least one of text output or audio output via at least one of a dashboard screen, speakers, or other output devices (For example, the client device 110 may be equipped with one or more speakers that enable content to be provided for audible presentation to the user via the client device 110) (page 4, paragraph [0028]) of the vehicle (a computing device of a vehicle (e.g., an in-vehicle communications system, an in-vehicle entertainment system, an in-vehicle navigation system)) (page 4, paragraph [0025]).
Regarding Claim 14, Pieraccini et al teaches the system, wherein the computing system is a user device (The client device 110) (page 4, paragraph [0025]).
Regarding Claim 15, Pieraccini et al teaches the system, wherein: the user device connects to a dashboard system of the vehicle (a computing device of a vehicle (e.g., an in-vehicle communications system, an in-vehicle entertainment system, an in-vehicle navigation system)) (page 4, paragraph [0025]), and the chatbot interacts with a user via input devices and output devices of the vehicle (For the sake of brevity and simplicity, the automated assistant 115 as used herein will refer to the automated assistant client 114 executing locally on the client device 110 and/or executing remotely at one or more remote servers that may implement the response style system 120) (page 4, paragraph [0026]).
Claims 16 are rejected under 35 U.S.C. 103 as being unpatentable over Pieraccini et al. (US 2024/0304184) in view of Burtch et al. (US 2023/0278493)
Regarding Claim 16, Pieraccini et al teaches a computer-implemented smart towing assistant configured to provide towing assistance associated with a vehicle, comprising: a chatbot trained, based upon a training dataset (In some implementations, the given LLM behavior controller training instance for training the LLM behavior controller can be obtained from one or more databases (e.g., from training instance(s) database 171A). In some versions of these implementations, the training instance(s) database 171A can include training instances that are pre-curated and generated based on prior dialogs between users or users and respective automated assistants) (page 9, paragraph [0056]), to engage in a conversation with a user (Notably, the NL based input 201 can be provided as part of a given turn of an ongoing dialog between the user of the client device 110 and the automated assistant 115. The NL based input 201 can be provided by the user of the client device 110 to initiate the ongoing dialog or in furtherance of the ongoing dialog) (page 9, paragraph [0041]).
Pieraccini et al fails to teach a smart towing assistant in association with towing of a towable object by the vehicle; a towing detector configured to detect, based upon sensor data associated with at least one of the vehicle or the towable object, towing activity associated with the towing of the towable object by the vehicle; and a towing lane assist system configured to: detect, based upon the sensor data, a safety issue associated with the towing of the towable object by the vehicle, and output an alert associated with the safety issue.
Burtch et al teaches a smart towing assistant in association with towing of a towable object by the vehicle (a vehicle control system 20 for assisting a vehicle operator in maneuvering a trailer 24) (page 2, paragraph [0033]); a towing detector configured to detect, based upon sensor data associated with at least one of the vehicle or the towable object, towing activity associated with the towing of the towable object by the vehicle (A disclosed example embodiment of the control system 20 operates by predicting a path 54 of the trailer based on vehicle and trailer odometry and detecting an obstacle 56 within the predicted path 54 with at least one trailer sensor system mounted on the trailer 24) (page 2, paragraph [003419]); and a towing lane assist system (The sensor system further provides information that is used to determine an orientation between the vehicle 22 and the trailer 24 that is utilized to predict the path 54) (page 2, paragraph [0040])configured to: detect, based upon the sensor data, a safety issue associated with the towing of the towable object by the vehicle (A disclosed example embodiment of the control system 20 operates by predicting a path 54 of the trailer based on vehicle and trailer odometry and detecting an obstacle 56 within the predicted path 54 with at least one trailer sensor system mounted on the trailer 24) (page 2, paragraph [0034]), and output an alert associated with the safety issue (at least one alert device in communication with the controller and configured to communicate possible contact to a tow vehicle operator responsive to detecting the obstacle within the predicted path) (page 2, paragraph [0034]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini with the teachings of Burtch to improve driving safety and reduce the chance of an accident by communicating the driving conditions of the trailer while you are driving.
Claims 9 are rejected under 35 U.S.C. 103 as being unpatentable over Pieraccini et al. and Watkins et al as applied to claim 1 above, and further in view of Anagnoson (US 8,650,052).
Regarding Claim 9, Pieraccini et al. and Watkins et al fail to teach a method, further comprising: determining, by the computing system, that the user input requests a change to an insurance policy to adjust towing insurance coverage; and initiating, by the computing system, the change to the insurance policy based upon the user input.
Anagnoson et al teaches further comprising: determining, by the computing system, that the user input requests a change to an insurance policy to adjust towing insurance coverage (Among the configurable elements under Personal Auto Line 602, Basics & Coverages tab 604 is selected. Then, among the coverages presented in area 616, Towing and Labor coverage 606 is selected to be added as a configured insurance product definition of product model 610) (col. 12, lines 44-54); and initiating, by the computing system, the change to the insurance policy based upon the user input (As a result of the selections made at the user interfaces of FIGS. 6A, 6B, and 6C, insurance product definition templates of a Towing and Labor coverage with a coverage limit of 50 was added to product model 610.) (col. 13, lines 10-15).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini, Watkins, and Anagnoson to insurance claim resolution by adding towing coverage while on the app during a traffic accident.
Claims 17 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Pieraccini et al. and Burtch et al. as applied to claim 16 above, and further in view of Watkins et al (US 2020/0267503).
Regarding Claim 17, Pieraccini et al. teaches the smart towing assistant, wherein the chatbot is configured to engage in the conversation by: receiving user input comprising natural language input (At block 454, the system receives NL based input from a user of a client device during a given dialog turn of an ongoing dialog between the user of the client device and the automated assistant that is accessible at the client device (e.g., as described with respect to the user input engine 111 of FIG. 1) (pages 10 and 11, paragraph [0067])); generating output based at least in part on the user input (At block 462, the system determines, based on the LLM output, a NL based response that is in the given NL based response style and that is responsive to the NL based input (e.g., as described with respect to the NL based response engine 185 of FIGS. 1 and 2)) (page 11, paragraph [0070]); and presenting the output during the conversation (At block 464, the system causes the NL based response to be rendered at the client device) (page 11, paragraph [0071]).
Pieraccini et al. and Burtch et al. fail to teach the smart towing assistant, wherein the output comprises natural language output that expresses towing-related information.
Watkins et al teaches wherein the output comprises natural language output that expresses towing-related information (FIG. 8 illustrates a second screen 150 of the crash detection, response and reporting application after a request for assistance, depicting updated assistance information 152. This may include the time of dispatch 154 and an estimate time of arrival 156. The update field may also present (not illustrated) the contact information of the tow truck driver) (page 6, paragraph [0065]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini and Burtch with the teachings of Watkins to improve insurance claim resolution during a traffic accident by contacting the tow truck driver thru an app on your mobile device.
Regarding Claim 18, Pieraccini et al. and Burtch et al. fail to teach the smart towing assistant, wherein the chatbot is configured to proactively steer the conversation to one or more towing-related topics.
Watkins et al teaches he smart towing assistant, wherein the chatbot (The portable computer can be any of a number and/or combination of devices selected from among personal computers, personal digital assistant devices, portable computing devices, and portable communication devices, but is not so limited) (pages 13 and 14, paragraph [0107]) is configured to proactively steer the conversation to one or more towing-related topics ( FIG. 8 illustrates a second screen 150 of the crash detection, response and reporting application after a request for assistance, depicting updated assistance information 152. This may include the time of dispatch 154 and an estimate time of arrival 156. The update field may also present (not illustrated) the contact information of the tow truck driver. A call button 157 initiates telephonic communication with the operator of the tow truck. Optionally, a confirm arrival button enables the driver to communicate status information to the tracking/dispatch center 18) (page 6, paragraph [0065]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the teachings of Pieraccini and Burtch with the teachings of Watkins to improve insurance claim resolution during a traffic accident by contacting the tow truck driver thru an app on your mobile device.
Allowable Subject Matter
Claims 10, 11, 19 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and if the 35 US 101 rejections above are overcome..
Cited Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Niewiadomski et al. (US 2022/0230544) discloses active HMI coaching to assist in the retreat from a pending trailer flank contact.
Enno (US 2023/0331151) discloses collision avoidance assembly.
Watkins et al. (US 2024/0163419) discloses remote verification of image collection equipment for crash event detection, response, and reporting.
Aharoni et al. (US 2024/0185734) discloses unstructured description based chatbot development techniques.
Goldshtein et al. (US 2024/0194180) discloses structured description based chatbot development techniques.
Gainer et a. (US 11,017,476) discloses telematics for accident detection and notification.
Conclusion
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/SATWANT K SINGH/Primary Examiner, Art Unit 2653
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