DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06-09-2026 has been entered.
Response to Amendment
Claims 1 and 15 have been amended.
Claims 9-10 and 19-20 have been canceled.
Claims 23-24 are new.
Claims 1-8, 11-18, and 21-24 are currently pending.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-8, 11-18, and 21-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pal (US 20170053461 A1) in view of Nayak (US 20240144812 A1)in further view of James (US 20050200479 A1).
REGARDING CLAIM 1, Pal discloses, a communication device configured to communicate with at least one vehicle (Pal: [0117] in response to receiving the request, automatically initiating an accident response action of transmitting the accident confidence metric to the third-party service for initiating a third-party accident response action); and at least one processor (Pal: [0172] computer-executable component can be a processor) configured to: receive, from the at least one vehicle, record data of an accident (Pal: [0016] receiving a supplementary dataset configured to supplement the movement dataset S120, determining an accident characteristic associated with the vehicular accident event S160, and/or receiving accident detection feedback), wherein the record data is acquired by an event data recorder (Pal: [0003] Vehicle telematic devices monitor the location, movements, status, and behavior of a vehicle. Such devices commonly use GPS receivers and an electronic device to transmit the collected data; [0021] Vehicular accident events can be detected when the mobile computing device collecting movement data is in a user's pocket, in a user's hand, mounted within the car, in a cup holder, and/or in other suitable locations within the vehicle) of the at least one vehicle related to the accident (Pal: [ABS] A method and system for detecting an accident of a vehicle, the method including: receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle); and transmit an accident response instruction signal via the communication device (Pal: [0022] Accident response actions can include any one or more of notifying emergency services, notifying loved ones, requesting roadside assistance, insurance processing, and/or other suitable accident response actions), wherein the accident severity value (Pal: [0084] determining an accident severity score) is based on: the record data, a quantity of accident vehicles involved in the accident (Pal: [0021] technology can accurately distinguish between collision events (e.g., single-vehicle collisions, multi-vehicle collisions, etc.); [0091] Vehicular accident events can include: collisions (e.g., single-vehicle collisions, multi-vehicle collisions; see [0152] for multi vehicle and vehicle type), a quantity of accident vehicles in which at least one airbag is deployed (Pal: [0055] include recording airbag deployment audio data, and detecting a vehicular accident event and/or determining an vehicular accident characteristic based on the airbag deployment audio data; [0062] vehicle sensor data can provide information on the status of a vehicle before/during/after an accident (e.g., by collecting airbag deployment data, ABS or other braking system data, engine temperature data, etc.); [0136] enable accident services provided by the vehicle (e.g., in-vehicle security services, airbag deployment; [0146] include interpreting vehicle sensor data (e.g., whether airbags deployed or not) as a measure of accident severity), and a quantity of vehicles of which deceleration rates are greater than or equal to a deceleration threshold (Pal: [0021] hard braking, [0033] movement thresholds, [0100] rapid deceleration (e.g., which can indicate an emergency braking situation), [0106] an acceleration threshold (e.g., deceleration must be greater than free-fall deceleration/9.8 ms.sup.−2), and/or any other suitable threshold).
Pal does not explicitly recite the terminology "deceleration threshold". However, in considering the disclosure of a reference, it is proper to take into account not only specific teachings of the reference but also the inferences which one skilled in the art would reasonably be expected to draw therefrom. In this case, Pal discloses establishing a severity level using braking ([0021] hard braking, [0033] movement thresholds, [0100] rapid deceleration (e.g., which can indicate an emergency braking situation), [0106] an acceleration threshold (e.g., deceleration must be greater than free-fall deceleration/9.8 ms.sup.−2), and/or any other suitable threshold), acceleration (deceleration), and turning/steering data (this is also acceleration and deceleration directionally). Which, the examiner respectfully submits, implies or suggests that the braking data breaches a threshold to move a severity rating/score ([0015, 0083-0084, 0149]).
Pal does not explicitly disclose, the accident response instruction signal is for a vehicle that follows an accident vehicle and is based on the record data and based on an accident severity value indicating severity of the accident, and wherein the at least one processor is configured to increase the accident severity value as the quantity of accident vehicles in which at least one airbag is deployed increases and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases.
However, in the same field of endeavor, Nayak discloses, the accident response instruction signal is for a vehicle that follows an accident vehicle (Nayak: [0002]) and is based on the record data (Nayak: [0100]) and based on an accident severity value indicating severity of the accident (Nayak: [0100]), and wherein the at least one processor is configured to increase the accident severity value as the quantity of accident vehicles in which at least one airbag is deployed increases (Nayak: [0068]) and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases (Nayak: [0067]), for the benefit of rerouting one or more vehicles.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by Pal to include sharing severity score based on received data taught by Nayak. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to reroute one or more vehicles.
The examiner respectfully submits, Pal, as modified discloses the accident response instruction signal is for a vehicle that follows an accident vehicle and is based on the record data and based on an accident severity value indicating severity of the accident, and wherein the at least one processor is configured to increase the accident severity value as the quantity of accident vehicles in which at least one airbag is deployed increases and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases.
However, in the alternative, and in the same field of endeavor, James discloses, the accident response instruction signal is for a vehicle that follows an accident vehicle (James: [0016] Additionally or alternatively, the method 100 can include receiving a supplementary dataset configured to supplement the movement dataset S120, determining an accident characteristic associated with the vehicular accident event S160, and/or receiving accident detection feedback S170; [0035] In a variation, Block S110 can include collecting movement data at multiple devices associated with a user and/or vehicle. For example, Block S110 can include collecting a first movement dataset at least at one of a location sensor and a motion sensor of mobile computing device positioned within a moving vehicle, and receiving a second movement dataset collected at least at one of a location sensor and a motion sensor of the moving vehicle. Multiple sources of movement data can be used to reduce noise, fill gaps of movement data during a time period, and/or increase confidence levels associated with detecting vehicular accident events and/or determining vehicular accident characteristics. For example, the method 100 can include reducing noise by combining (e.g., averaging) multiple sources of movement data. Movement datasets from multiple sources can be collected at the same type of device (e.g., a first and a second smart phone positioned within the vehicle), or different types of devices (e.g., a smart phone and a vehicle). Additionally or alternatively, collecting movement data at multiple devices can be performed in any suitable fashion) and is based on the record data (James: [0015] As shown in FIGS. 1-3, an embodiment of a method 100 for detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle S110; extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period S130; detecting a vehicular accident event from processing the set of movement features with an accident detection model S140; and in response to detecting the vehicular accident event, automatically initiating an accident response action) and based on an accident severity value indicating severity of the accident (James: [0015] As shown in FIGS. 1-3, an embodiment of a method 100 for detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle S110; extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period S130; detecting a vehicular accident event from processing the set of movement features with an accident detection model S140; and in response to detecting the vehicular accident event, automatically initiating an accident response action), and wherein the at least one processor is configured to increase the accident severity value as the quantity of accident vehicles in which at least one airbag is deployed increases (James: [0015] As shown in FIGS. 1-3, an embodiment of a method 100 for detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle S110; extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period S130; detecting a vehicular accident event from processing the set of movement features with an accident detection model S140; and in response to detecting the vehicular accident event, automatically initiating an accident response action) and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases (James: [0035] In a variation, Block S110 can include collecting movement data at multiple devices associated with a user and/or vehicle. For example, Block S110 can include collecting a first movement dataset at least at one of a location sensor and a motion sensor of mobile computing device positioned within a moving vehicle, and receiving a second movement dataset collected at least at one of a location sensor and a motion sensor of the moving vehicle. Multiple sources of movement data can be used to reduce noise, fill gaps of movement data during a time period, and/or increase confidence levels associated with detecting vehicular accident events and/or determining vehicular accident characteristics. For example, the method 100 can include reducing noise by combining (e.g., averaging) multiple sources of movement data. Movement datasets from multiple sources can be collected at the same type of device (e.g., a first and a second smart phone positioned within the vehicle), or different types of devices (e.g., a smart phone and a vehicle). Additionally or alternatively, collecting movement data at multiple devices can be performed in any suitable fashion), for the benefit of getting help.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by a modified Pal to include broadcasting a severe event based upon severity based upon braking and airbag information taught by James. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to get help.
REGARDING CLAIM 2, Pal, as modified, remains as applied above to claim 1, and further, Pal also discloses, the at least one vehicle comprises the accident vehicle (Pal: [0015]); and the at least one processor is configured to: receive location information of the accident vehicle (Pal: [0059]), and determine, based on the location information of the accident vehicle, an accident location in which the accident occurs (Pal: [0059]).
REGARDING CLAIM 3, Pal, as modified, remains as applied above to claim 1, and further, Pal also discloses, transmit, to the at least one vehicle, a request for accident information via the communication device (Pal: [0117]), and receive, based on the request for accident information, the record data of the accident vehicle in response to the request (Pal: [0117]).
REGARDING CLAIM 4, Pal, as modified, remains as applied above to claim 1, and further, Pal also discloses, transmit, to the at least one vehicle, a request for accident information via the communication device (Pal: [0117]), and receive, based on the request for accident information, image data associated with at least one image of the accident acquired by a video recording device of the at least one vehicle (Pal: [0063]; [0059]).
Pal does not explicitly recite the terminology "requesting image data". However, Pal discloses obtaining vehicle exterior and interior images before, during, and after an event, and upon request, transmitting vehicle data. Thus, implying an image data request and transmission (coded instructions or otherwise). In considering the disclosure of a reference, it is proper to take into account not only specific teachings of the reference but also the inferences which one skilled in the art would reasonably be expected to draw therefrom.
REGARDING CLAIM 5, Pal, as modified, remains as applied above to claim 4, and further, Pal also discloses, the at least one processor is configured to transmit a request for the record data (Pal: [0063]; [0059]) and the image data to the accident vehicle (Pal: [0063]; [0059]).
REGARDING CLAIM 6, Pal, as modified, remains as applied above to claim 2, and further, Pal also discloses, transmit, to the at least one vehicle, a request for image data (Pal: [0063]; [0059]) within a certain time range associated with an accident time at which the accident occurs (Pal: [0015]; [0023]; [0094]; [0117]).
Pal does not explicitly disclose, wherein the at least one vehicle comprises a nearby vehicle located in the accident location, and receive, based on the request for image data, image data acquired by a video recording device of the nearby vehicle.
However, in the same field of endeavor, Nayak discloses, wherein the at least one vehicle comprises a nearby vehicle located in the accident location (Nayak: [0093]; [0108-0110]), and receive, based on the request for image data, image data acquired by a video recording device of the nearby vehicle (Nayak: [0093]; [0108-0110]), for the benefit of rerouting one or more vehicles.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by Pal to include confirmation taught by Nayak. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to reroute one or more vehicles.
REGARDING CLAIM 7, Pal, as modified, remains as applied above to claim 6, and further, Pal also discloses, including data associated with EDR data provided from the accident vehicle within the certain time range (Pal: [0015]; [0023]; [0094]; [0117]).
Pal does not explicitly disclose, the nearby vehicle is a vehicle that transmits event data recorder (EDR) data.
However, in the same field of endeavor, Nayak discloses, the nearby vehicle is a vehicle that transmits event data recorder (EDR) data (Nayak: [0093]), for the benefit of rerouting one or more vehicles.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by Pal to include confirmation of event data taught by Nayak. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to reroute one or more vehicles.
REGARDING CLAIM 8, Pal, as modified, remains as applied above to claim 6, and further, Pal also discloses, specific data associated with the accident within the certain time range (Pal: [0015]; [0023]; [0094]; [0117]).
Pal does not explicitly disclose, the nearby vehicle is a vehicle that transmits event data recorder (EDR) data.
However, in the same field of endeavor, Nayak discloses, the nearby vehicle is a vehicle that transmits event data recorder (EDR) data (Nayak: [0093]), for the benefit of rerouting one or more vehicles.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by Pal to include confirmation of event data taught by Nayak. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to reroute one or more vehicles.
REGARDING CLAIM 11, Pal, as modified, remains as applied above to claim 1, and further, Pal also discloses, transmit, to the vehicle that follows the accident vehicle, accident section information indicating an accident location (Pal: [0122]) and accident image data for the accident via the communication device (Pal: [0122]).
REGARDING CLAIM 12, Pal, as modified, remains as applied above to claim 11, and further, Pal also discloses, search for a detour route that bypasses the accident location (Pal: [0122]), and transmit, to the vehicle that follows the accident vehicle, the detour route via the communication device (Pal: [0122]).
REGARDING CLAIM 13, Pal, as modified, remains as applied above to claim 1, and further, Pal also discloses, based on the accident severity value (Pal: [0024]; [0084]; [0120]) being less than a certain critical value (Pal: [0094]), the at least one processor transmits accident section information indicating an accident location (Pal: [0059]) and an accident occurrence notification, to the vehicle that follows the accident vehicle, via the communication device (Pal: [0122]).
REGARDING CLAIM 14, Pal, as modified, remains as applied above to claim 1, and further, Pal also discloses, the communication device receives a portion of the record data from an audio video navigation telematics (AVNT) device of the accident vehicle (Pal: [FIG. 4-8]; [0119]).
REGARDING CLAIM 15, Pal discloses, receiving an accident occurrence signal from a first accident vehicle (Pal: [ABS] receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle, extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period, detecting a vehicular accident event) indicating a first accident section (Pal: [0015] detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor; [0037] collect location-related data for use in detecting one or more vehicular accident events) in which an accident of the first accident vehicle occurs (Pal: [0015] detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor; [0037] collect location-related data for use in detecting one or more vehicular accident events); receiving an accident occurrence signal from a second accident vehicle (Pal: [0144] calculating an accident confidence metric indicating a degree of confidence in occurrence of the vehicular accident event, based on at least one of the second location dataset and the second motion dataset; selecting a personalized accident response action from a set of accident response actions, based on the accident confidence metric) indicating a second accident section in which an accident of the second accident vehicle occurs (Pal: [0144] calculating an accident confidence metric indicating a degree of confidence in occurrence of the vehicular accident event, based on at least one of the second location dataset and the second motion dataset; selecting a personalized accident response action from a set of accident response actions, based on the accident confidence metric); receiving accident record acquired by an accident recording device of at least one of the first accident vehicle or the second accident vehicle (Pal: [ABS]); wherein the accident severity value (Pal: [0084] determining an accident severity score) is based on: the accident record, a quantity of vehicles involved in at least one of the accident of the first accident vehicle or the accident of the second accident vehicle (Pal: [0021] technology can accurately distinguish between collision events (e.g., single-vehicle collisions, multi-vehicle collisions, etc.); [0091] Vehicular accident events can include: collisions (e.g., single-vehicle collisions, multi-vehicle collisions; see [0152] for multi vehicle and vehicle type), a quantity of vehicles in which at least one airbag is deployed (Pal: [0055] include recording airbag deployment audio data, and detecting a vehicular accident event and/or determining an vehicular accident characteristic based on the airbag deployment audio data; [0062] vehicle sensor data can provide information on the status of a vehicle before/during/after an accident (e.g., by collecting airbag deployment data, ABS or other braking system data, engine temperature data, etc.); [0136] enable accident services provided by the vehicle (e.g., in-vehicle security services, airbag deployment; [0146] include interpreting vehicle sensor data (e.g., whether airbags deployed or not) as a measure of accident severity), and a quantity of vehicles of which deceleration rates are greater than or equal to a deceleration threshold (Pal: [0021] hard braking, [0033] movement thresholds, [0100] rapid deceleration (e.g., which can indicate an emergency braking situation), [0106] an acceleration threshold (e.g., deceleration must be greater than free-fall deceleration/9.8 ms.sup.−2), and/or any other suitable threshold).
Pal does not explicitly recite the terminology "deceleration threshold". However, in considering the disclosure of a reference, it is proper to take into account not only specific teachings of the reference but also the inferences which one skilled in the art would reasonably be expected to draw therefrom. In this case, Pal discloses establishing a severity level using braking ([0021] hard braking, [0033] movement thresholds, [0100] rapid deceleration (e.g., which can indicate an emergency braking situation), [0106] an acceleration threshold (e.g., deceleration must be greater than free-fall deceleration/9.8 ms.sup.−2), and/or any other suitable threshold), acceleration (deceleration), and turning/steering data (this is also acceleration and deceleration directionally). Which, the examiner respectfully submits, implies or suggests that the braking data breaches a threshold to move a severity rating/score ([0015, 0083-0084, 0149]).
Pal does not explicitly disclose, transmitting, to the first accident vehicle and the second accident vehicle, a request for accident information; and transmitting an accident response instruction signal for at least one vehicle that follows at least one of the first accident vehicle or the second accident vehicle, wherein the accident response instruction signal is based on the accident record and based on an accident severity value indicating severity of the accident of the first accident vehicle, and wherein the accident severity value is configured to be increased as the quantity of accident vehicles in which at least one airbag is deployed increases and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases.
However, in the same field of endeavor, Nayak discloses, transmitting, to the first accident vehicle and the second accident vehicle, a request for accident information (Nayak: see [0108-0110] for routing nearby vehicles to record the traffic event); and transmitting an accident response instruction signal for at least one vehicle that follows at least one of the first accident vehicle or the second accident vehicle (Nayak: [0061]; [0124]), the accident response instruction signal is for a vehicle that follows an accident vehicle (Nayak: [0002]) and is based on the record data (Nayak: [0100]) and based on an accident severity value indicating severity of the accident (Nayak: [0100]), and wherein the at least one processor is configured to increase the accident severity value as the quantity of accident vehicles in which at least one airbag is deployed increases (Nayak: [0068]) and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases (Nayak: [0067]), for the benefit of rerouting one or more vehicles.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by Pal to include confirmation and data sharing taught by Nayak. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to reroute one or more vehicles.
The examiner respectfully submits, Pal, as modified discloses the accident response instruction signal is for a vehicle that follows an accident vehicle and is based on the record data and based on an accident severity value indicating severity of the accident, and wherein the at least one processor is configured to increase the accident severity value as the quantity of accident vehicles in which at least one airbag is deployed increases and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases.
However, in the alternative, and in the same field of endeavor, James discloses, the accident response instruction signal is for a vehicle that follows an accident vehicle (James: [0016] Additionally or alternatively, the method 100 can include receiving a supplementary dataset configured to supplement the movement dataset S120, determining an accident characteristic associated with the vehicular accident event S160, and/or receiving accident detection feedback S170; [0035] In a variation, Block S110 can include collecting movement data at multiple devices associated with a user and/or vehicle. For example, Block S110 can include collecting a first movement dataset at least at one of a location sensor and a motion sensor of mobile computing device positioned within a moving vehicle, and receiving a second movement dataset collected at least at one of a location sensor and a motion sensor of the moving vehicle. Multiple sources of movement data can be used to reduce noise, fill gaps of movement data during a time period, and/or increase confidence levels associated with detecting vehicular accident events and/or determining vehicular accident characteristics. For example, the method 100 can include reducing noise by combining (e.g., averaging) multiple sources of movement data. Movement datasets from multiple sources can be collected at the same type of device (e.g., a first and a second smart phone positioned within the vehicle), or different types of devices (e.g., a smart phone and a vehicle). Additionally or alternatively, collecting movement data at multiple devices can be performed in any suitable fashion) and is based on the record data (James: [0015] As shown in FIGS. 1-3, an embodiment of a method 100 for detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle S110; extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period S130; detecting a vehicular accident event from processing the set of movement features with an accident detection model S140; and in response to detecting the vehicular accident event, automatically initiating an accident response action) and based on an accident severity value indicating severity of the accident (James: [0015] As shown in FIGS. 1-3, an embodiment of a method 100 for detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle S110; extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period S130; detecting a vehicular accident event from processing the set of movement features with an accident detection model S140; and in response to detecting the vehicular accident event, automatically initiating an accident response action), and wherein the at least one processor is configured to increase the accident severity value as the quantity of accident vehicles in which at least one airbag is deployed increases (James: [0015] As shown in FIGS. 1-3, an embodiment of a method 100 for detecting an accident of a vehicle includes receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle S110; extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period S130; detecting a vehicular accident event from processing the set of movement features with an accident detection model S140; and in response to detecting the vehicular accident event, automatically initiating an accident response action) and as the quantity of vehicles of which deceleration rates are greater than or equal to the deceleration threshold increases (James: [0035] In a variation, Block S110 can include collecting movement data at multiple devices associated with a user and/or vehicle. For example, Block S110 can include collecting a first movement dataset at least at one of a location sensor and a motion sensor of mobile computing device positioned within a moving vehicle, and receiving a second movement dataset collected at least at one of a location sensor and a motion sensor of the moving vehicle. Multiple sources of movement data can be used to reduce noise, fill gaps of movement data during a time period, and/or increase confidence levels associated with detecting vehicular accident events and/or determining vehicular accident characteristics. For example, the method 100 can include reducing noise by combining (e.g., averaging) multiple sources of movement data. Movement datasets from multiple sources can be collected at the same type of device (e.g., a first and a second smart phone positioned within the vehicle), or different types of devices (e.g., a smart phone and a vehicle). Additionally or alternatively, collecting movement data at multiple devices can be performed in any suitable fashion), for the benefit of getting help.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by a modified Pal to include broadcasting a severe event based upon severity based upon braking and airbag information taught by James. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to get help.
REGARDING CLAIM 16, Pal, as modified, remains as applied above to claim 15, and further, Pal also discloses, receiving, based on the request for accident information, accident image data (Pal: [0059]) acquired by a video recording device of at least one of the first accident vehicle or the second accident vehicle (Pal: [0059]).
REGARDING CLAIM 17, Pal, as modified, remains as applied above to claim 15, and further, Pal also discloses, based on the first accident section and the second accident section being the same (Pal: [0021]; [0156]; [0157]) and based on an accident time at which the accident of the first accident vehicle occurs (Pal: [0034]; [0082]; [0157]) and an accident time at which the accident of the second accident vehicle occurs (Pal: [0034]; [0082]; [0157]) being within a certain time period (Pal: [0034]; [0082]; [0157]), determining that the accident of the first accident vehicle is associated with the accident of the second accident vehicle (Pal: [0034]; [0082]; [0157]).
REGARDING CLAIM 18, Pal, as modified, remains as applied above to claim 17, and further, Pal also discloses, based on a determination that it is necessary to additionally collect accident-related information for the accident of the first accident vehicle and the accident of the second accident vehicle (Pal: [0039]; [0146]; [0163]).
Pal does not explicitly disclose, transmitting, to a nearby vehicle located in the first accident section, a request for image data within a certain time range associated with an accident time at which the accident of the first accident vehicle occurs; and receiving, based on the request for image data, image data acquired by a video recording device of the nearby vehicle.
However, in the same field of endeavor, Nayak discloses, transmitting, to a nearby vehicle located in the first accident section, a request for image data within a certain time range associated with an accident time at which the accident of the first accident vehicle occurs (Nayak: see [0108-0110] for routing nearby vehicles to record the traffic event); and receiving, based on the request for image data, image data acquired by a video recording device of the nearby vehicle (Nayak: [ABS]), for the benefit of rerouting one or more vehicles.
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the process disclosed by Pal to include confirmation taught by Nayak. One of ordinary skill in the art would have been motivated to make this modification, with a reasonable expectation of success, in order to reroute one or more vehicles.
REGARDING CLAIM 21, Pal, as modified, remains as applied above to claim 15, and further, Pal also discloses, accident section information indicating at least one of the first accident section or the second accident section (Pal: [0055]); and accident image data for the accident (Pal: [0059]); and the transmitting the accident response instruction signal comprises transmitting, to the at least one vehicle that follows at least one of the first accident vehicle or the second accident vehicle, the accident response instruction signal based on the accident severity value being greater than or equal to a certain critical value (Pal: [0023]; [0116]; [0120]; see [0125-0140] for detailed section on contacting emergency services).
REGARDING CLAIM 22, Pal, as modified, remains as applied above to claim 21, and further, Pal also discloses, searching for a detour route that bypasses at least one of the first accident section or the second accident section (Pal: [0122]); and transmitting, to the at least one vehicle that follows at least one of the first accident vehicle or the second accident vehicle (Pal: [0122]), the detour route via a communication device, based on the accident severity value being greater than or equal to the certain critical value (Pal: [0122]).
The examiner respectfully submits, that the action of rerouting suggests a threshold has been achieved to initiate rerouting. In considering the disclosure of a reference, it is proper to take into account not only specific teachings of the reference but also the inferences which one skilled in the art would reasonably be expected to draw therefrom.
REGARDING CLAIM 23, Pal, as modified, remains as applied above to claim 1. Further, Pal also discloses, determine whether a vehicle body posture control device of the at least one vehicle was triggered (Pal: [0104] Block S142 preferably includes extracting a vehicle motion characteristic (e.g., to compare against motion characteristic threshold). Vehicle motion characteristics and motion characteristic thresholds can typify motion characteristic types including any one or more of: speed characteristics (e.g., average speed, instantaneous speed, speed variability, change in speed, etc.), acceleration (e.g., average acceleration, instantaneous acceleration, acceleration variability, change in acceleration, etc.), position (e.g., altitude, GPS coordinates, direction, location, etc.), turning characteristics (e.g., turn speed, turn radius, steering angles, wheel velocities, tire slip velocities, etc.), movement features, and/or any other suitable vehicle motion characteristics. For example, Block S142 can include extracting a vehicle motion characteristic, where the vehicle motion characteristic is a vehicular speed value, and where the threshold motion characteristic (e.g., to which the vehicle motion characteristic can be compared) is a vehicular speed threshold. In another example, Block S142 can include extracting a vehicle motion characteristic from a movement dataset (e.g., a location dataset and/or motion dataset), where the vehicle motion characteristic describes the movement of the vehicle within a time window of the first time period (examiner: no mention of braking, implying all data is pre-brakage)) before a sudden stop based on the record data (Pal: [0021] Second, the technology can detect vehicular accident events with high accuracy. In examples, the technology can accurately distinguish between collision events (e.g., single-vehicle collisions, multi-vehicle collisions, etc.) and non-collision events (e.g., hard braking, rapid acceleration, etc.); [0055] In a variation, Block S120 can optionally include Block S121, which recites: collecting audio data. Block S121 preferably includes collecting audio data that can be used to detect that an accident has occurred and/or the severity of an accident (e.g., by analyzing recorded audio for sounds related to or resulting from impacts). For example, audio data can provide information on the status of a vehicle before/during/after an accident (e.g., by recording engine noise), the nature, location, and/or severity of an accident (e.g., by recording impact noise), and the effect of the accident on the vehicle's occupants (e.g., by recording voice data for a vehicle's occupants). In another example, Block S121 can include recording airbag deployment audio data, and detecting a vehicular accident event and/or determining an vehicular accident characteristic based on the airbag deployment audio data, any other suitable audio data, and/or movement data).
REGARDING CLAIM 24, Pal, as modified, remains as applied above to claim 1. Further, Pal also discloses, automatically transmit the accident response instruction signal, via wireless communication (Pal: [ABS] in response to detecting the vehicular accident event, automatically initiating an accident response action), based on the accident severity value indicating severity of the accident (Pal: [0022] Third, the technology can automatically initiate accident response actions in response to detection of a vehicular accident. Accident response actions can include any one or more of notifying emergency services, notifying loved ones, requesting roadside assistance, insurance processing, and/or other suitable accident response actions. Further, in examples, the type of initiated accident response action can be tailored to the particular accident based on movement data and/or supplemental data. In examples, the technology can include a software development kit for third-parties to integrate the accident detection features, thereby enabling third-parties to leverage accident detection for purposes of driving education, ride sharing, valet services, navigation, roadside assistance, insurance processing, emergency services, and/or other services. [0023] Fourth, the technology can detect vehicular accident events in real-time. Prompt transmission of time-sensitive information (e.g., GPS coordinates, vehicular accident characteristics, etc.) to the appropriate entities (e.g., emergency services) can be the differentiator between life and death in serious vehicular accidents. [0024] Fifth, the technology can improve the technical fields of at least vehicle telematics, computational modeling of vehicular accident detection, and vehicular accident detection with mobile computing device data. The technology can continuously collect and utilize non-generic sensor data (e.g., location sensor data, motion sensor data, etc.) to provide real-time accident detection and/or determination of accident characteristics (e.g., severity, accident type, etc.) Further, the technology can take advantage of the non-generic sensor data and/or supplemental data (e.g., vehicle sensor data, weather data, traffic data, biosignal sensor data, etc.) to better improve the understanding of correlations between such data and vehicular accident events, leading to an increased understanding of vehicular-related and driver-related variables affecting vehicular accidents; [0116] include automatically contacting emergency services (e.g., rather than only notifying selected user contacts) in response to a vehicular speed movement feature exceeding a threshold vehicular speed. In another example, Block S150 can include prompting a user to signify that he/she is okay if a low-severity accident score accident is detected, but can include automatically notifying emergency services if a severe accident is detected; 3.2.E Supplementary Data—Collecting Biosignal Data).
Response to Arguments
Applicant’s arguments, beginning on page 11, received 06-09-2026, with respect to 35 USC §101, ineligible subject matter rejection of record have been fully considered and are persuasive. The 35 USC §101, ineligible subject matter rejection of record has been withdrawn.
Applicant’s arguments with respect to the rejection of the independent claim(s) under 35 USC §103, obviousness, have been considered but are moot because the new ground of rejection does not rely on the reference combination applied in the prior rejection of record for matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Nepomuceno (US 20170292848 A1)
Brandmaier (US 10460534 B1)
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/A.S./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663
