System and method for identifying and predicting cause of sudden acceleration

Abstract

According to an embodiment of the present invention, disclosed are a method and system for identifying and predicting a cause of sudden acceleration. The system comprises: a sensor unit configured to detect driver operation information including brake pedal operation information and accelerator pedal operation information, and vehicle behavior information; an event data recorder (EDR) configured to store, as EDR data, preset information among the driver operation information and the vehicle behavior information detected by the sensor unit; a sudden acceleration monitoring system (SAMS) provided with an embedded sensor configured to detect second vehicle behavior information; and a computing device including a memory and a processor. The memory may be configured to store instructions configured to, when executed by the processor, cause the processor to: process the driver operation information and second vehicle behavior information into SAMS data so as to correspond to the EDR data; determine whether an accident has occurred; in response to determining that the accident has occurred, determine whether the difference between the EDR data and the SAMS data exceeds an error threshold value; and in response to determining that the difference between the EDR data and the SAMS data exceeds the error threshold value, determine that the vehicle is defective.

Description

System and method for identifying and predicting the cause of sudden rash

[0001] The present invention relates to a system and method for identifying and predicting the cause of sudden acceleration, and more particularly, to a system and method for identifying and predicting the cause of sudden acceleration, which records sudden acceleration monitoring system (SAMS) data separately from event data recorder (EDR) data, behavioral data, and on-board diagnosis (OBD) data, identifies the cause of sudden acceleration using the EDR data and SAMS data, and predicts the occurrence of sudden acceleration by analyzing trends in the behavioral data, OBD data, and SAMS data.

[0002] Accidents in which a vehicle accelerates unexpectedly, contrary to the driver's intent, occur occasionally both domestically and internationally. Most accidents suspected of being caused by sudden acceleration are often ruled as the result of driver error rather than vehicle defect, or the evidence is often insufficient to prove vehicle defect. In particular, in countries without product liability laws, it is extremely difficult for an ordinary driver to prove vehicle defect.

[0003] Domestic automakers have built-in Event Data Recorders (EDRs) to record some accidents. However, they do not disclose the details of these records, making it difficult to reliably determine the cause of the accident. In particular, in cases where sudden acceleration is suspected and the cause is a malfunction of the vehicle's Electronic Control Unit (ECU), the accuracy of EDR records can be uncertain. In particular, it is crucial to determine how the driver operated the brake and accelerator pedals in accidents suspected of sudden acceleration. However, the evidence the driver can provide is often circumstantial, making it very difficult to prove sudden acceleration.

[0004] The information contained in this background section is intended to enhance understanding of the background of the invention and may include matters that are not prior art and are already known to those of ordinary skill in the art.

[0005] An embodiment of the present invention provides a system and method for identifying and predicting the cause of sudden acceleration, which records sudden acceleration monitoring system (SAMS) data separately from event data recorder (EDR), behavioral data, and on-board diagnosis (OBD) data, identifies the cause of sudden acceleration using EDR data and SAMS data, and predicts the occurrence of sudden acceleration by analyzing trends in behavioral data, OBD data, and SAMS data.

[0006] A method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention may include the steps of: detecting, by a sensor unit, preset information among driver operation information including brake pedal operation information and accelerator pedal operation information and vehicle behavior information as Event Data Recorder (EDR) data; detecting, by a built-in sensor of a Sudden Acceleration Monitoring System (SAMS), second vehicle behavior information; processing, by a computing device including a memory and a processor, the driver operation information and the second vehicle behavior information into SAMS data corresponding to the EDR data; determining, by the computing device, whether an accident has occurred; in response to determining that an accident has occurred, in response to determining that a difference between the EDR data and the SAMS data exceeds an error threshold value; and in response to determining that the difference between the EDR data and the SAMS data exceeds the error threshold value, in response to determining that the vehicle has a defect, in response to determining that the difference between the EDR data and the SAMS data exceeds the error threshold value, in response to determining that the vehicle has a defect, in response to determining that the vehicle has a defect.

[0007] The method may further include a step of analyzing the EDR data and the SAMS data by the computing device in response to a determination that the difference between the EDR data and the SAMS data is less than or equal to an error threshold.

[0008] The step of determining whether a difference between EDR data and SAMS data exceeds an error threshold may include at least one of the following steps: determining whether a difference between a speed in the EDR data and a speed in the SAMS data exceeds a speed error threshold; determining whether a difference between a brake pedal operation degree in the EDR data and a brake pedal operation degree in the SAMS data exceeds a brake pedal operation error threshold; determining whether a difference between an accelerator pedal operation degree in the EDR data and an accelerator pedal operation degree in the SAMS data exceeds an accelerator pedal operation error threshold; determining whether a difference between a cumulative change in speed for a set time before an accident in the EDR data and a cumulative change in speed for a set time before an accident in the SAMS data exceeds a cumulative error threshold for speed change; determining whether a difference between a maximum acceleration in the direction of travel in the EDR data and a maximum acceleration in the direction of travel in the SAMS data exceeds a maximum acceleration error threshold; or determining whether a difference between a point in time of maximum acceleration occurrence in the direction of travel in the EDR data and a point in time of maximum acceleration occurrence in the direction of travel in the SAMS data exceeds a point in time of maximum acceleration occurrence error threshold.

[0009] If the difference between the speed in the EDR data and the speed in the SAMS data exceeds the speed error threshold, or the difference between the brake pedal operation degree in the EDR data and the brake pedal operation degree in the SAMS data exceeds the brake pedal operation error threshold, or the difference between the accelerator pedal operation degree in the EDR data and the accelerator pedal operation degree in the SAMS data exceeds the accelerator pedal operation error threshold, or the difference between the cumulative change in speed for a set time before an accident in the EDR data and the cumulative change in speed for a set time before an accident in the SAMS data exceeds the cumulative speed change error threshold, or the difference between the maximum acceleration in the forward direction in the EDR data and the maximum acceleration in the forward direction in the SAMS data exceeds the maximum acceleration error threshold, or the difference between the point in time of maximum acceleration in the forward direction in the EDR data and the point in time of maximum acceleration in the forward direction in the SAMS data exceeds the point in time of maximum acceleration occurrence error threshold, the vehicle may be determined to have a defect.

[0010] According to another embodiment of the present invention, a method for identifying and predicting the cause of sudden acceleration may include the steps of: detecting, by a sensor unit, preset information among driver operation information including brake pedal operation information and accelerator pedal operation information and vehicle behavior information as vehicle behavior data; detecting, by a built-in sensor of a Sudden Acceleration Monitoring System (SAMS), second vehicle behavior information; processing, by a computing device including a memory and a processor, the driver operation information and the second vehicle behavior information into SAMS data so as to correspond to the vehicle behavior data; calculating, by the computing device, a deterioration function defined as a value obtained by subtracting the SAMS data from the vehicle behavior data; determining, by the computing device, whether the deterioration function is greater than or equal to a deterioration function threshold value; and calculating, by the computing device, a residual time until occurrence of sudden acceleration in response to determining that the deterioration function is greater than or equal to a deterioration function threshold value.

[0011] The method further includes a step of detecting, by an on-board diagnosis (OBD) device in response to a determination that the vehicle behavior information does not correspond to the driver operation information, the step of detecting the corresponding vehicle behavior information and the driver operation information as OBD data; and a step of establishing, by a computing device, a database of vehicle behavior data, OBD data, and a deterioration function by associating the vehicle behavior data and the OBD data related to the value of the deterioration function with each other, wherein the step of determining whether the deterioration function is greater than or equal to a deterioration function threshold value can be performed when the number of the vehicle behavior data, the OBD data, and the deterioration function that are associated with each other is greater than or equal to a set number.

[0012] The method may further include a step of analyzing, by a computing device, vehicle behavior data, OBD data, and a deterioration function after calculating a residual time until sudden acceleration occurs or in response to determining that the deterioration function is below a deterioration function threshold.

[0013] The method may further include a step of providing maintenance / repair information via a user interface by the computing device.

[0014] According to another embodiment of the present invention, a system for identifying and predicting the cause of sudden acceleration includes: a sensor unit configured to detect driver operation information including brake pedal operation information and accelerator pedal operation information and vehicle behavior information; an EDR configured to store preset information among the driver operation information and vehicle behavior information detected by the sensor unit as event data recorder (EDR) data; a sudden acceleration monitoring system (SAMS) provided with a built-in sensor configured to detect second vehicle behavior information; and a computing device including a memory and a processor, wherein the memory may be configured to store a command configured to, when executed by the processor, cause the processor to process the driver operation information and the second vehicle behavior information into SAMS data corresponding to the EDR data, determine whether an accident has occurred, and in response to determining that an accident has occurred, determine whether a difference between the EDR data and the SAMS data exceeds an error threshold value, and in response to determining that the difference between the EDR data and the SAMS data exceeds the error threshold value, determine that there is a defect in the vehicle.

[0015] The above instructions, when executed by the processor, may be further configured to cause the processor to analyze the EDR data and the SAMS data in response to a determination that the difference between the EDR data and the SAMS data is less than or equal to an error threshold.

[0016] The processor may be configured to determine, when determining whether a difference between EDR data and SAMS data exceeds an error threshold, whether a difference between a speed in the EDR data and a speed in the SAMS data exceeds a speed error threshold; whether a difference between a brake pedal operation degree in the EDR data and a brake pedal operation degree in the SAMS data exceeds a brake pedal operation error threshold; whether a difference between an accelerator pedal operation degree in the EDR data and an accelerator pedal operation degree in the SAMS data exceeds an accelerator pedal operation error threshold; whether a difference between a cumulative change in speed for a set time before an accident in the EDR data and a cumulative change in speed for a set time before an accident in the SAMS data exceeds a cumulative error threshold of speed change; whether a difference between a maximum acceleration in the forward direction in the EDR data and a maximum acceleration in the forward direction in the SAMS data exceeds a maximum acceleration error threshold; or whether a difference between a point in time when a maximum acceleration occurs in the forward direction in the EDR data and a point in time when a maximum acceleration occurs in the forward direction in the SAMS data exceeds a maximum acceleration occurrence point error threshold.

[0017] If the difference between the speed in the EDR data and the speed in the SAMS data exceeds the speed error threshold, or the difference between the brake pedal operation degree in the EDR data and the brake pedal operation degree in the SAMS data exceeds the brake pedal operation error threshold, or the difference between the accelerator pedal operation degree in the EDR data and the accelerator pedal operation degree in the SAMS data exceeds the accelerator pedal operation error threshold, or the difference between the cumulative change in speed for a set time before an accident in the EDR data and the cumulative change in speed for a set time before an accident in the SAMS data exceeds the cumulative speed change error threshold, or the difference between the maximum acceleration in the forward direction in the EDR data and the maximum acceleration in the forward direction in the SAMS data exceeds the maximum acceleration error threshold, or the difference between the point in time of maximum acceleration in the forward direction in the EDR data and the point in time of maximum acceleration in the forward direction in the SAMS data exceeds the point in time of maximum acceleration occurrence error threshold, the vehicle may be determined to have a defect.

[0018] A system for identifying and predicting the cause of sudden acceleration according to another embodiment of the present invention comprises: a sensor unit configured to detect driver operation information including brake pedal operation information and accelerator pedal operation information and vehicle behavior information; a Sudden Acceleration Monitoring System (SAMS) provided with a built-in sensor configured to detect second vehicle behavior information; and a computing device including a memory and a processor, wherein the memory may be configured to store a command configured to cause the processor to process the driver operation information and the second vehicle behavior information into SAMS data corresponding to the vehicle behavior data, calculate a deterioration function defined as a value obtained by subtracting the SAMS data from the vehicle behavior data, determine whether the deterioration function is greater than or equal to a deterioration function threshold value, and in response to determining that the deterioration function is greater than or equal to a deterioration function threshold value, calculate a remaining time until occurrence of sudden acceleration.

[0019] The system further includes an On-Board Diagnosis (OBD) configured to detect corresponding vehicle behavior information and driver operation information as OBD data in response to a determination that the vehicle behavior information does not correspond to driver operation information, and the memory is further configured to cause the processor, when executed by the processor, to build a database of vehicle behavior data, OBD data, and deterioration functions by associating the vehicle behavior data and OBD data related to values ​​of the deterioration functions, and the processor may be configured to determine whether the deterioration function is greater than or equal to a deterioration function threshold when the number of the vehicle behavior data, the OBD data, and the deterioration functions associated with each other is greater than or equal to a set number.

[0020] The above memory may be further configured to cause the processor, when executed by the processor, to analyze the vehicle behavior data, the OBD data, and the deterioration function after calculating the remaining time until the sudden acceleration occurs or in response to determining that the deterioration function is below a deterioration function threshold.

[0021] The above memory may be further configured to, when executed by the processor, cause the processor to provide maintenance / repair information through a user interface.

[0022] According to the present invention, SAMS data can be recorded separately from EDR data, behavior data, and OBD data, and the cause of a vehicle defect or sudden acceleration can be identified by comparing these data.

[0023] Additionally, by analyzing trends in behavioral data and OBD data along with SAMS data, it is possible to predict sudden acceleration and provide maintenance / repair information.

[0024] In addition, the effects that can be obtained or expected from embodiments of the present invention will be disclosed directly or implicitly in the detailed description of the embodiments of the present invention. That is, the various effects expected according to embodiments of the present invention will be disclosed in the detailed description that follows.

[0025] Embodiments of the present disclosure may be better understood by reference to the following description taken in conjunction with the accompanying drawings in which like reference numerals designate identical or functionally similar elements.

[0026] Figure 1 is a block diagram of a system for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention.

[0027] Figure 2 is a schematic diagram showing an example of a pedal device provided in a vehicle and sensors provided in the pedal device.

[0028] Figure 3 is a flowchart of a method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention.

[0029] Figure 4 is a flowchart of a method for identifying and predicting the cause of sudden acceleration according to another embodiment of the present invention.

[0030] The drawings referenced above are not necessarily drawn to scale, but should be understood to present rather simplified representations of various preferred features that illustrate the fundamental principles of the present disclosure. For example, specific design features of the present disclosure, including specific dimensions, orientations, positions, and shapes, will be determined in part by the specific intended application and usage environment.

[0031] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present invention. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It will also be understood that the terms "comprises" and / or "comprising," when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term "and / or" includes any one or all combinations of the associated listed items.

[0032] As used herein, the terms "vehicle" or "vehicle of" or other similar terms include general land vehicles, including passenger cars, buses, trucks, various commercial vehicles, and the like, including sport utility vehicles (SUVs). Furthermore, as used herein, the terms "vehicle" or "vehicle of" or other similar terms are understood to include hybrid vehicles, electric vehicles, plug-in hybrid vehicles, hydrogen-powered vehicles, and other alternative fuel (e.g., fuels derived from sources other than petroleum) vehicles. Hybrid vehicles include vehicles with two or more power sources, such as gasoline-powered and electric-powered vehicles. Vehicles according to embodiments of the present invention include both manually driven vehicles as well as vehicles that are somewhat autonomous and / or automatically driven.

[0033] Additionally, it is understood that one or more of the methods or aspects thereof below may be implemented by at least one controller. The term "controller" may refer to a hardware device comprising a memory and a processor. The memory is configured to store program instructions, and the processor is specifically programmed to execute the program instructions to perform one or more processes described in more detail below. The controller may control the operation of units, modules, components, devices, or the like, as described herein. It is also understood that the methods below may be implemented by a device comprising the controller in conjunction with one or more other components, as will be appreciated by those skilled in the art.

[0034] Additionally, the controller of the present disclosure may be implemented as a non-transitory computer-readable recording medium containing executable program instructions executed by a processor. Examples of computer-readable recording media include, but are not limited to, read-only memory (ROM), random-access memory (RAM), compact disc (CD) ROM, magnetic tapes, floppy disks, flash drives, smart cards, and optical data storage devices. The computer-readable recording medium may also be distributed across a computer network so that the program instructions are stored and executed in a distributed manner, such as on a telematics server or a Controller Area Network (CAN).

[0035]

[0036] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings.

[0037] Figure 1 is a block diagram of a system for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention.

[0038] As illustrated in FIG. 1, the sudden acceleration cause identification and prediction system (10) according to an embodiment of the present invention is configured to identify the cause of sudden acceleration of a vehicle and predict the occurrence of sudden acceleration by using driver operation information (30) and vehicle behavior information (40). For this purpose, the sudden acceleration cause identification and prediction system (10) according to an embodiment of the present invention may include a sensor unit, a main electronic control unit (ECU) (50), an event data recorder (EDR) (52), an on-board diagnosis (OBD) (54), a sudden acceleration monitoring system (SAMS) (60), an image / audio recording device (80), a navigation device (82), and a control server (90).

[0039] The sensor unit is configured to detect various physical values ​​representing driver operation and vehicle behavior. More specifically, the sensor unit is configured to detect driver operation information (30) including brake pedal operation information (32), accelerator pedal operation information (34), and steering wheel operation information (36), and is configured to detect whether a brake lamp (42) is blinking and vehicle behavior information (44) such as vehicle speed, steering angle, acceleration, vehicle attitude, and / or gear. To this end, the sensor unit may include, but is not limited to, a brake pedal sensor (20), a first foot image sensor (22), an accelerator pedal sensor (24), a second foot image sensor (26), and a current or voltage sensor (28).

[0040] The brake pedal sensor (20) is configured to detect brake pedal operation information (32). For example, the brake pedal sensor (20) is configured to detect brake pedal operation information (32) by detecting the rotation angle of the brake pedal, the torsion of the brake pedal, the displacement of the return spring for the brake pedal, the load, or the displacement of the brake pedal.

[0041] The first foot image sensor (22) is configured to detect an image of the brake pedal and thereby detect brake pedal operation information (32). That is, the first foot image sensor (22) can detect the displacement of the brake pedal by acquiring an image of the brake pedal, and is configured to detect brake pedal operation information (32) through the displacement of the brake pedal.

[0042] The accelerator pedal sensor (24) is configured to detect accelerator pedal operation information (34). For example, the accelerator pedal sensor (24) is configured to detect accelerator pedal operation information (34) by detecting the rotation angle of the accelerator pedal, the torsion of the accelerator pedal, the displacement of the return spring for the accelerator pedal, the load, or the displacement of the accelerator pedal.

[0043] The second foot image sensor (26) is configured to detect an image of the accelerator pedal and thereby detect accelerator pedal operation information (34). That is, the second foot image sensor (26) can detect displacement of the accelerator pedal by acquiring an image of the accelerator pedal, and is configured to detect accelerator pedal operation information (34) through the displacement of the accelerator pedal.

[0044] Fig. 2 is a schematic diagram illustrating an example of a pedal device provided in a vehicle and sensors provided in the pedal device. The pedal device (100) of Fig. 2 may be a brake pedal or an accelerator pedal.

[0045] A pedal device (100) is provided at a predetermined distance from the floor (102) of the vehicle and is mounted to be rotatable about a pedal rotation axis with respect to the vehicle body. A push rod (108) is connected to the pedal device (100), and the push rod (108) moves by the rotation of the pedal device (100) to operate a target device. A push rod adjuster (110) is provided between the pedal device (100) and the push rod (108) and is configured to adjust the movement of the push rod (108) according to the pedal device (100). A rotation angle sensor (114) configured to detect a rotation angle of the pedal device (100) or to detect a torsion applied to the pedal device (100) may be arranged on the rotation axis.

[0046] A return spring (104) is provided between the pedal device (100) and the vehicle body to provide a restoring force to move the pedal device (100) to its initial position. A displacement sensor (112) is installed between the pedal device (100) and the vehicle body on which the return spring (104) is mounted to detect the displacement of the pedal device (100) or the load applied to the pedal device (100). In addition, an image sensor (116) is provided on the vehicle body near the pedal device (100) to detect an image of the pedal device (100). When the pedal device (100) is a brake pedal, a pedal light switch (106) is provided close to the pedal device (100). When the brake pedal is operated, the pedal light switch (106) is configured to turn on the brake lamp (42).

[0047] Accordingly, the brake pedal sensor (20) and the accelerator pedal sensor (24) may be displacement sensors (112) or rotation angle sensors (114), and the first and second foot image sensors (22, 26) may be image sensors (116).

[0048] The current or voltage sensor (28) is configured to detect the current or voltage applied to the brake lamp (42). For example, when the pedal light switch (106) is operated, current or voltage is applied to the brake lamp (42), and the current or voltage sensor (28) can detect brake pedal operation information (32) by detecting the current or voltage.

[0049] The main ECU (50) receives driver operation information (30) detected by the sensor unit, and is configured to accelerate, brake, or steer the vehicle according to the driver operation information (30). The main ECU (50) transmits the driver operation information (30) detected by the sensor unit to a corresponding target device, receives vehicle behavior information (40) of the target device detected by the sensor unit, and determines whether the vehicle behavior information (40) corresponds to the driver operation information (30). If the vehicle behavior information (40) does not correspond to the driver operation information (30), it is determined that there is a problem in the vehicle behavior information (40) or a device corresponding to the driver operation information (30), and the information can be transmitted to the OBD (54) and stored as OBD data. In addition, the main ECU (50) can transmit the vehicle behavior information (40) corresponding to the driver operation information (30) to the EDR (52) and store it as EDR data. The driver operation information (30) and vehicle behavior information (40) stored as the above EDR data can be set by the designer.

[0050] The EDR (52) stores driver operation information (30) and corresponding vehicle behavior information (40) as EDR data. If necessary or requested, the EDR (52) can transmit the EDR data to the SAMS (60), the control server (90), or a separate accident cause analysis device (not shown). The EDR data can be recorded on an hourly basis.

[0051] OBD (54) stores vehicle behavior information (40) and driver operation information (30) as OBD data. OBD (54) can transmit the OBD data to SAMS (60) via internal communication. For example, the internal communication may be CAN communication, but is not limited thereto. The OBD data can also be recorded by time.

[0052] SAMS (60) is configured to receive driver operation information including brake pedal operation information and accelerator pedal operation information and vehicle behavior information from the sensor unit, receive video / audio information and GPS information from the video / audio recording device (80) and the navigation device (82), and detect vehicle behavior information such as speed and / or acceleration using built-in sensors. In order to distinguish it from the vehicle behavior information detected by the sensor unit, the vehicle behavior information detected by the sensor unit is referred to as 'vehicle behavior data' below, and the vehicle behavior information detected by the built-in sensor of SAMS (60) is referred to as 'second vehicle behavior information'. The vehicle behavior data may further include pedal operation information in addition to the vehicle behavior information.

[0053] In addition, SAMS (60) processes the driver operation information, second vehicle behavior information, video / audio information, and / or GPS information and records them as SAMS data, receives OBD data from OBD (54), and analyzes the vehicle behavior data, SAMS data, and OBD data to calculate the possibility of sudden acceleration and the remaining time until sudden acceleration occurs. The SAMS data can also be recorded by time.

[0054] For this purpose, the SAMS (60) may include an image processing module (62), an analog digital converter (ADC) module (64), a built-in acceleration sensor (66), an internal communication module (68), an external communication module (70), a built-in GPS (72), a data management device (74), and a data storage device (76).

[0055] The image processing module (62) receives an image of the brake pedal from the first foot image sensor (22), processes the image of the brake pedal through image processing logic, and can detect displacement of the brake pedal (i.e., operation information of the brake pedal). In addition, the image processing module (62) receives an image of the accelerator pedal from the second foot image sensor (26), and processes the image of the accelerator pedal through the image processing logic, and can detect displacement of the accelerator pedal (i.e., operation information of the accelerator pedal). The image processing logic may be a known image processing logic that can detect operation information of the pedal device (100) from an image of the pedal device (100).

[0056] The ADC module (64) is configured to convert driver operation information including brake pedal operation information and accelerator pedal operation information detected by the sensor unit or processed by the image processing module (62), and second vehicle behavior information including multi-axis acceleration information of the vehicle detected by the built-in acceleration sensor (66) into digital signals. For example, the ADC module may receive second vehicle behavior information including brake pedal operation information, accelerator pedal operation information, and / or multi-axis acceleration information of the vehicle from the brake pedal sensor (20), the accelerator pedal sensor (24), the current or voltage sensor (28), the imaging processing module (62), and / or the built-in acceleration sensor (66), and may convert the second vehicle behavior information including the brake pedal operation information, the accelerator pedal operation information, and / or multi-axis acceleration information of the vehicle into digital signals.

[0057] An acceleration sensor (66) is configured to detect second vehicle behavior information including multi-axis acceleration information of a vehicle and transmit the second vehicle behavior information including the multi-axis acceleration information to an ADC module (64). The acceleration sensor may be, but is not limited to, a multi-axis acceleration sensor, a gyro sensor, etc.

[0058] The internal communication module (68) is configured to receive OBD data from the OBD (54) and vehicle behavior data from the sensor unit. The internal communication module (68) may be, but is not limited to, a CAN communication module.

[0059] The external communication module (70) is configured to communicate with the video / audio recording device (80) and the navigation device (82) to receive video / audio information and / or GPS information, and is configured to communicate with the control server (90) to transmit SAMS data, OBD data, vehicle behavior data, etc. to the control server (90).

[0060] The built-in GPS (72) receives GPS information. Time synchronization of SAMS data, OBD data, vehicle behavior data, etc. can be performed using the GPS information detected by the built-in GPS (72).

[0061] The data management device (74) may be configured to perform a method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention. More specifically, the data management device (74) is configured to identify the cause of sudden acceleration using SAMS data and EDR data, calculate a deterioration function using vehicle behavior data and SAMS data, and build a database of vehicle behavior data, OBD data, and deterioration function. In addition, the data management device (74) may be further configured to, but is not limited to, determine whether the deterioration function is greater than or equal to a deterioration function threshold value, calculate the remaining time until sudden acceleration occurs in response to the deterioration function being greater than or equal to the deterioration function threshold value, and analyze the vehicle behavior data, OBD data, and deterioration function to provide vehicle maintenance / repair information. To this end, the data management device (74) may be implemented as a type of processor.

[0062] The data storage device (76) is configured to store a database of vehicle behavior data, OBD data, SAMS data, and / or deterioration functions. Furthermore, the data storage device (76) is further configured to store various program commands, algorithms, logic circuits, and / or operating systems for performing a method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention. For this purpose, the data storage device (76) may be implemented as a type of memory.

[0063] The video / audio recording device (80) is configured to record video outside the vehicle (e.g., video of the external environment in front and / or behind the vehicle) and / or audio inside the vehicle, and transmit video / audio information about the video outside the vehicle and / or audio inside the vehicle to the SAMS (60) through the internal communication module (68).

[0064] The navigation device (82) is configured to detect GPS information of the vehicle and transmit the GPS information of the vehicle to SAMS (60) through an internal communication module (68).

[0065] The control server (90) may be configured to receive EDR data from the EDR (52), and SAMS data, OBD data, vehicle behavior data, etc. from the SAMS (60) through the external communication module (70), identify the cause of sudden acceleration using the EDR data and the SAMS data, calculate a deterioration function using the vehicle behavior data and the SAMS data, and build a database of the vehicle behavior data, OBD data, and deterioration function. In addition, the control server (90) may be further configured to transmit the deterioration function or the database of the deterioration function to the SAMS (60) so that the SAMS (60) may calculate the remaining time until sudden acceleration occurs or provide maintenance / repair information. To this end, the control server (90) may include a user interface (UI) (96), a server data analysis device (94), and a server data storage device (92).

[0066] The UI (96) may include an input interface configured to receive user input and an output interface configured to display output to the user. The input interface may include at least one of various input devices such as a keyboard, a mouse, a touch screen, a laser pointer, and a microphone, and the output interface may include at least one of various output devices such as a touch screen, a display, a speaker, and a warning light. However, the types of the input interface and the output interface are not limited to those exemplified.

[0067] The server data analysis device (94) may also be configured to perform the method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention together with or independently of the data management device (74). More specifically, the server data analysis device (94) is configured to receive EDR data from the EDR (52), receive SAMS data, vehicle behavior data, and OBD data from the SAMS (60) via the external communication module (70), identify the cause of sudden acceleration using the SAMS data and the EDR data, calculate a deterioration function using the vehicle behavior data and the SAMS data, and build a database of the vehicle behavior data, OBD data, and deterioration function. In addition, the server data analysis device (94) may be further configured to, but is not limited to, determine whether the deterioration function is greater than or equal to a deterioration function threshold value, calculate the remaining time until sudden acceleration occurs in response to the deterioration function being greater than or equal to the deterioration function threshold value, and analyze the vehicle behavior data, OBD data, and deterioration function to provide maintenance / repair information for the vehicle. For this purpose, the server data analysis device (94) can be implemented as a type of processor.

[0068] The server data storage device (92) is configured to store a database of vehicle behavior data, OBD data, SAMS data, and / or deterioration functions. Furthermore, the server data storage device (92) is further configured to store various program commands, algorithms, logic circuits, and / or operating systems for performing a method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention. For this purpose, the server data storage device (92) may be implemented as a type of memory.

[0069] In this specification, the SAMS (60) or the control server (90) is described as performing the method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention. However, the method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention may also be performed by a separate accident cause analysis device (not shown). In this case, the accident cause analysis device includes at least the components of the control server (90) described in this specification, and the components of the accident cause analysis device may perform the same or extremely similar functions as the corresponding components of the control server (90) or operate the same or extremely similarly. Accordingly, the SAMS (60), the control server (90), or the accident cause analysis device includes a computing device including a memory and a processor, and the memory is configured to store instructions for performing the method according to an embodiment of the present invention, and the instructions may be configured to cause the processor to perform each step of the method according to an embodiment of the present invention when executed by the processor.

[0070] Figure 3 is a flowchart of a method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention.

[0071] As illustrated in FIG. 3, a method for identifying and predicting the cause of sudden acceleration according to an embodiment of the present invention is intended to identify the cause of sudden acceleration in the event of an accident. While the method is illustrated as starting from step S100 and sequentially performing steps S110 and S120, the execution order of steps S100 to S120 is not limited thereto. The method may begin at at least one step among steps S100 to S120.

[0072] At step S100, the sensor unit detects driver operation information (30) and vehicle behavior information (44), and detects set information among the driver operation information (30) and vehicle behavior information (44) as EDR data (S100). For example, the EDR data may be at least one of speed, brake pedal operation degree, accelerator pedal operation information, cumulative change in speed during a set time before an accident, maximum acceleration in the direction of travel, and point in time when maximum acceleration occurs in the direction of travel. The EDR data may be stored in the EDR (52).

[0073] In addition, the sensor unit detects driver operation information including brake pedal operation information and accelerator pedal operation information, and the built-in sensor of SAMS (60) (e.g., acceleration sensor (66) or built-in GPS (72)) detects second vehicle behavior information, thereby detecting SAMS data (S110). The SAMS data can be processed to correspond to EDR data. The SAMS data can be transmitted to a computing device at set intervals by being stored in a data storage device (76) or transmitted to a control server (90) via external communication.

[0074] Additionally, the main ECU (50) determines whether an accident has occurred (S120). The main ECU (50) can determine whether an accident has occurred based on detection values ​​from airbag sensors, impact sensors, video / audio recording devices (80), etc. Alternatively, a computing device can determine whether an accident has occurred instead of the main ECU (50).

[0075] If no accident occurs, the method returns to step S100 and continues to detect EDR data and SAMS data.

[0076] If an accident occurs, the main ECU (50) transmits accident information to the computing device, or the computing device directly determines that an accident has occurred. In this case, the computing device receives EDR data from the EDR (52). In addition, the computing device receives SAMS data at set intervals.

[0077] When EDR data and SAMS data are acquired, the computing device determines whether a difference between the EDR data and the SAMS data exceeds an error threshold value (S130). For example, the EDR data may include at least one of a speed among the EDR data, a brake pedal operation degree among the EDR data, an accelerator pedal operation degree among the EDR data, a cumulative change in speed for a set time before an accident among the EDR data, a maximum acceleration in the direction of travel among the EDR data, and a point in time when the maximum acceleration occurs in the direction of travel among the EDR data, and the corresponding SAMS data may include at least one of a speed among the SAMS data, a brake pedal operation degree among the SAMS data, an accelerator pedal operation degree among the SAMS data, a cumulative change in speed for a set time before an accident among the SAMS data, a maximum acceleration in the direction of travel among the SAMS data, and a point in time when the maximum acceleration occurs in the direction of travel among the SAMS data, and the corresponding error threshold value may include at least one of a speed error threshold value, a brake pedal operation error threshold value, an accelerator pedal operation error threshold value, a cumulative change in speed error threshold value, a maximum acceleration error threshold value, and a point in time when the maximum acceleration occurs error threshold value.

[0078] If the difference between the EDR data and the SAMS data exceeds the error threshold, the vehicle may be determined to have a defect (S140). For example, if the difference between the EDR data and the SAMS data is large, the vehicle may be determined to have a defect, such as the sensor unit incorrectly detecting a sensor value, the main ECU (50) issuing an incorrect command, or a component receiving a command from the main ECU (50) is malfunctioning.

[0079] If the difference between the EDR data and the SAMS data does not exceed the error threshold, the computing device can analyze the EDR data and the SAMS data (S150) to determine the cause of the accident.

[0080] Figure 4 is a flowchart of a method for identifying and predicting the cause of sudden acceleration according to another embodiment of the present invention.

[0081] As illustrated in FIG. 4, a method for identifying and predicting the cause of sudden acceleration according to another embodiment of the present invention is intended to predict the occurrence of sudden acceleration. While the method is illustrated as starting at step S200 and sequentially performing steps S210 and S220, the execution order of steps S200 to S220 is not limited thereto. The method may start at at least one step among steps S200 to S220.

[0082] In step S200, the sensor unit detects vehicle behavior data including vehicle behavior information and pedal operation information (S200). For example, the vehicle behavior data may be at least one of speed, brake pedal operation degree, accelerator pedal operation information, cumulative change in speed for a set period of time, maximum acceleration in the direction of travel, and point in time when maximum acceleration occurs in the direction of travel. The vehicle behavior data is identical to or extremely similar to the EDR data, but the EDR data is stored in the EDR (52) and is not transmitted to the computing device before an accident occurs, whereas the vehicle behavior data may be transmitted to the computing device at set intervals by being transmitted to the SAMS (60) via internal communication or to the control server (90) via external communication.

[0083] In addition, the sensor unit detects driver operation information including brake pedal operation information and accelerator pedal operation information, and the built-in sensor of the SAMS (60) (e.g., acceleration sensor (66) or built-in GPS (72)) detects second vehicle behavior information, thereby detecting SAMS data (S210). The SAMS data can be processed to correspond to the vehicle behavior data. The SAMS data can be transmitted to a computing device at set intervals by being stored in a data storage device (76) or transmitted to a control server (90) via external communication.

[0084] In addition, when the vehicle behavior information (40) does not correspond to the driver operation information (30), the corresponding vehicle behavior information (40) and driver operation information (30) are detected as OBD data (S220), and the OBD data can be transmitted to the computing device at set intervals by being transmitted to the SAMS (60) through internal communication or to the control server (90) through external communication.

[0085] When the computing device acquires vehicle behavior data, SAMS data, and OBD data, the computing device calculates a deterioration function (S230). The deterioration function is defined as the value obtained by subtracting SAMS data from the vehicle behavior data. In other words, the deterioration function is defined by the following equation.

[0086] Deterioration function = vehicle behavior data - SAMS data

[0087] For example, the degradation function includes at least one of a velocity degradation function, a brake pedal operation degradation function, an accelerator pedal operation degradation function, a velocity change cumulative degradation function, a maximum acceleration degradation function, and a maximum acceleration occurrence point degradation function. The speed degradation function is defined as the value obtained by subtracting the speed in the SAMS data from the speed in the vehicle behavior data, the brake pedal operation degradation function is defined as the value obtained by subtracting the brake pedal operation degree in the SAMS data from the brake pedal operation degree in the vehicle behavior data, the accelerator pedal operation degradation function is defined as the value obtained by subtracting the accelerator pedal operation degree in the SAMS data from the accelerator pedal operation degree in the vehicle behavior data, the speed change cumulative degradation function is defined as the value obtained by subtracting the cumulative change in speed in the SAMS data for the same set time from the cumulative change in speed in the vehicle behavior data, the maximum acceleration degradation function is defined as the value obtained by subtracting the maximum acceleration in the forward direction in the SAMS data from the maximum acceleration in the forward direction in the vehicle behavior data, and the maximum acceleration occurrence point degradation function can be defined as the value obtained by subtracting the maximum acceleration occurrence point in the forward direction in the SAMS data from the maximum acceleration occurrence point in the forward direction in the vehicle behavior data.

[0088] Once the deterioration function is calculated, the computing device builds a database of vehicle behavior data, OBD data, and deterioration functions (S240). That is, a database of vehicle behavior data, OBD data, and deterioration functions is built by correlating vehicle behavior data and OBD data related to the values ​​of the calculated deterioration function.

[0089] When the number of interrelated vehicle behavior data, OBD data, and deterioration functions exceeds a set number and a sufficient database is built for analysis of the deterioration functions, the computing device determines whether the deterioration function is greater than the deterioration function threshold value (S250).

[0090] If the degradation function is determined to be greater than the degradation function threshold, the computing device calculates the remaining time until sudden acceleration occurs. For example, as a vehicle ages, the ECU, sensors, or components within the vehicle may age or become defective, causing the degradation function value to increase. If the degradation function value increases to a warning value, the likelihood of sudden acceleration increases, requiring maintenance or replacement of the ECU, sensor, or component within the vehicle. Therefore, the remaining time until sudden acceleration occurs is calculated based on the difference between the current value of the degradation function and the warning value.

[0091] Thereafter, the computing device analyzes vehicle behavior data, OBD data, and deterioration functions (S270). For example, by analyzing the values ​​of a specific deterioration function and the related behavior data and OBD data, ECUs, sensors, or components within the vehicle requiring maintenance / repair can be identified, and maintenance / repair information can be provided to the user through a UI (96) or the like (S280).

[0092] Meanwhile, even if the deterioration function is determined to be greater than the deterioration function threshold at step S250, the computing device can analyze vehicle behavior data, OBD data, and the deterioration function (S270) and provide maintenance / repair information to the user (S280).

[0093] Then, users, mechanics, etc. can maintain / repair the identified ECU, sensor, or component based on the provided maintenance / repair information.

[0094]

[0095] Although the preferred embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, and includes all changes that can be easily modified and deemed equivalent by a person having ordinary skill in the art to which the invention pertains from the embodiments of the present invention.

Claims

1. In the method of identifying and predicting the cause of sudden rash, A step of detecting preset information among driver operation information and vehicle behavior information, including brake pedal operation information and accelerator pedal operation information, as event data recorder (EDR) data by a sensor unit; A step of detecting second vehicle behavior information by a built-in sensor of a Sudden Acceleration Monitoring System (SAMS); A step of processing driver operation information and second vehicle behavior information into SAMS data corresponding to EDR data by a computing device including a memory and a processor; A step of determining whether an accident has occurred by a computing device; In response to determining that an accident has occurred, a step of determining whether the difference between EDR data and SAMS data exceeds an error threshold by the computing device; and A step of determining that there is a defect in the vehicle by the computing device in response to a determination that the difference between the EDR data and the SAMS data exceeds an error threshold; A method for identifying and predicting the cause of a rash, including:

2. In paragraph 1, A method for identifying and predicting the cause of a sudden rash, further comprising a step of analyzing EDR data and SAMS data by a computing device in response to a determination that the difference between EDR data and SAMS data is below an error threshold.

3. In paragraph 1, The step to determine whether the difference between EDR data and SAMS data exceeds the error threshold is A step of determining whether the difference between the speed in the EDR data and the speed in the SAMS data exceeds the speed error threshold; A step of determining whether the difference between the brake pedal operation degree among EDR data and the brake pedal operation degree among SAMS data exceeds the brake pedal operation error threshold; A step of determining whether the difference between the degree of accelerator pedal operation in EDR data and the degree of accelerator pedal operation in SAMS data exceeds the accelerator pedal operation error threshold; A step of determining whether the difference between the cumulative change in speed during a set time period before an accident among EDR data and the cumulative change in speed during a set time period before an accident among SAMS data exceeds a cumulative error threshold of speed change; A step of determining whether the difference between the maximum acceleration in the forward direction among EDR data and the maximum acceleration in the forward direction among SAMS data exceeds the maximum acceleration error threshold; or A step of determining whether the difference between the point of maximum acceleration in the forward direction among EDR data and the point of maximum acceleration in the forward direction among SAMS data exceeds the maximum acceleration point error threshold; A method for identifying and predicting the cause of a rash, comprising at least one of:

4. In paragraph 3, If the difference between the speed in the EDR data and the speed in the SAMS data exceeds the speed error threshold, If the difference between the brake pedal operation degree in the EDR data and the brake pedal operation degree in the SAMS data exceeds the brake pedal operation error threshold, If the difference between the accelerator pedal operation degree in the EDR data and the accelerator pedal operation degree in the SAMS data exceeds the accelerator pedal operation error threshold, If the difference between the cumulative change in speed during the set time before the accident among the EDR data and the cumulative change in speed during the set time before the accident among the SAMS data exceeds the cumulative error threshold of the speed change, If the difference between the maximum acceleration in the forward direction among EDR data and the maximum acceleration in the forward direction among SAMS data exceeds the maximum acceleration error threshold, A method for identifying and predicting the cause of sudden acceleration, in which the vehicle is judged to have a defect if the difference between the point of maximum acceleration in the forward direction in EDR data and the point of maximum acceleration in the forward direction in SAMS data exceeds the maximum acceleration point error threshold.

5. In the method of identifying and predicting the cause of sudden rash, A step of detecting preset information among driver operation information including brake pedal operation information and accelerator pedal operation information and vehicle behavior information as vehicle behavior data by a sensor unit; A step of detecting second vehicle behavior information by a built-in sensor of a Sudden Acceleration Monitoring System (SAMS); A step of processing driver operation information and second vehicle behavior information into SAMS data corresponding to vehicle behavior data by a computing device including a memory and a processor; A step of calculating a degradation function defined by subtracting SAMS data from vehicle behavior data by a computing device; A step of determining, by a computing device, whether the degradation function is greater than or equal to a degradation function threshold; and A step of calculating the remaining time until the occurrence of a sudden acceleration in response to a determination by a computing device that the degradation function is greater than or equal to a degradation function threshold; A method for identifying and predicting the cause of a rash, including:

6. In paragraph 5, A step of detecting the corresponding vehicle behavior information and driver operation information as OBD data in response to a determination that the vehicle behavior information does not correspond to the driver operation information by an on-board diagnosis device (OBD); and A step of constructing a database of vehicle behavior data, OBD data, and deterioration function by correlating vehicle behavior data and OBD data related to values ​​of deterioration functions by a computing device; Including more, The step of determining whether the deterioration function is greater than the deterioration function threshold is a method for identifying and predicting the cause of sudden acceleration performed when the number of related vehicle behavior data, OBD data, and deterioration functions is greater than a set number.

7. In paragraph 6, A method for identifying and predicting the cause of sudden acceleration, further comprising a step of analyzing vehicle behavior data, OBD data, and a deterioration function by a computing device after calculating the residual time until sudden acceleration occurs or in response to determining that the deterioration function is below a deterioration function threshold.

8. In paragraph 7, A method for identifying and predicting the cause of a sudden surge, further comprising the step of providing maintenance / repair information through a user interface by a computing device.

9. In the system for identifying and predicting the cause of sudden rash, A sensor unit configured to detect driver operation information and vehicle behavior information including brake pedal operation information and accelerator pedal operation information; EDR configured to store preset information among driver operation information and vehicle behavior information detected by the sensor unit as event data recorder (EDR) data; A Sudden Acceleration Monitoring System (SAMS) provided with a built-in sensor configured to detect second vehicle behavior information; and A computing device including memory and a processor; Includes, The above memory, when executed by the processor, causes the processor to: Process driver operation information and second vehicle behavior information into SAMS data corresponding to the EDR data, Determine whether an accident has occurred, In response to the judgment that an accident has occurred, determine whether the difference between EDR data and SAMS data exceeds the error threshold, A system for identifying and predicting the cause of sudden acceleration, configured to store a command configured to determine that the vehicle is defective in response to a determination that the difference between EDR data and SAMS data exceeds an error threshold.

10. In paragraph 9, A method for identifying and predicting the cause of a sudden acceleration, wherein the above command, when executed by the processor, causes the processor to analyze the EDR data and the SAMS data in response to a determination that the difference between the EDR data and the SAMS data is less than or equal to an error threshold.

11. In paragraph 9, When the above processor determines whether the difference between EDR data and SAMS data exceeds the error threshold, Determine whether the difference between the speed in the EDR data and the speed in the SAMS data exceeds the speed error threshold; or Determine whether the difference between the brake pedal operation degree in the EDR data and the brake pedal operation degree in the SAMS data exceeds the brake pedal operation error threshold; or Determine whether the difference between the accelerator pedal operation degree in the EDR data and the accelerator pedal operation degree in the SAMS data exceeds the accelerator pedal operation error threshold; or Determine whether the difference between the cumulative change in speed during a set time period before an accident among EDR data and the cumulative change in speed during a set time period before an accident among SAMS data exceeds the cumulative error threshold of speed change; or Determine whether the difference between the maximum acceleration in the forward direction among EDR data and the maximum acceleration in the forward direction among SAMS data exceeds the maximum acceleration error threshold; or A system for identifying and predicting the cause of sudden acceleration configured to determine whether the difference between the point of maximum acceleration in the forward direction among EDR data and the point of maximum acceleration in the forward direction among SAMS data exceeds the maximum acceleration point error threshold.

12. In paragraph 11, If the difference between the speed in the EDR data and the speed in the SAMS data exceeds the speed error threshold, If the difference between the brake pedal operation degree in the EDR data and the brake pedal operation degree in the SAMS data exceeds the brake pedal operation error threshold, If the difference between the accelerator pedal operation degree in the EDR data and the accelerator pedal operation degree in the SAMS data exceeds the accelerator pedal operation error threshold, If the difference between the cumulative change in speed during the set time before the accident among the EDR data and the cumulative change in speed during the set time before the accident among the SAMS data exceeds the cumulative error threshold of the speed change, If the difference between the maximum acceleration in the forward direction among EDR data and the maximum acceleration in the forward direction among SAMS data exceeds the maximum acceleration error threshold, A system for identifying and predicting the cause of sudden acceleration, which determines that there is a defect in the vehicle if the difference between the point of maximum acceleration in the forward direction in EDR data and the point of maximum acceleration in the forward direction in SAMS data exceeds the maximum acceleration point error threshold.

13. In the system for identifying and predicting the cause of sudden rash, A sensor unit configured to detect driver operation information and vehicle behavior information including brake pedal operation information and accelerator pedal operation information; A Sudden Acceleration Monitoring System (SAMS) provided with a built-in sensor configured to detect second vehicle behavior information; and A computing device including memory and a processor; Includes, The above memory, when executed by the processor, causes the processor to: Driver operation information and second vehicle behavior information are processed into SAMS data corresponding to vehicle behavior data, Computes a degradation function defined as the value obtained by subtracting SAMS data from vehicle behavior data, Determine whether the degradation function is greater than or equal to the degradation function threshold, A system for identifying and predicting the cause of a sudden acceleration, the system comprising: a command configured to calculate a residual time until a sudden acceleration occurs in response to a determination that the deterioration function is greater than a deterioration function threshold.

14. In paragraph 13, In response to a determination that the vehicle behavior information does not correspond to the driver operation information, the vehicle further includes an On-Board Diagnosis (OBD) configured to detect the corresponding vehicle behavior information and driver operation information as OBD data. The above memory is further configured to cause the processor, when executed by the processor, to build a database of vehicle behavior data, OBD data, and deterioration function by associating the vehicle behavior data and OBD data with values ​​of the deterioration function, The above processor is a system for identifying and predicting the cause of sudden acceleration, wherein the processor is configured to determine whether the deterioration function is greater than the deterioration function threshold value when the number of interrelated vehicle behavior data, OBD data, and deterioration functions is greater than or equal to a set number.

15. In paragraph 14, A system for identifying and predicting the cause of sudden acceleration, wherein the memory is further configured to cause the processor to analyze vehicle behavior data, OBD data, and a deterioration function when executed by the processor, after calculating the remaining time until sudden acceleration occurs or in response to determining that the deterioration function is below a deterioration function threshold.

16. In paragraph 15, A system for identifying and predicting the cause of a sudden surge, wherein the memory is further configured to cause the processor to provide maintenance / repair information through a user interface when executed by the processor.

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