A driving behavior detection method, device, equipment and medium

Abstract

The application discloses a driving behavior detection method, device, equipment and medium. The method comprises the following steps: acquiring a current vehicle speed of a measured vehicle; detecting whether a vehicle state of the measured vehicle is an idle state according to the current vehicle speed; if it is detected that the vehicle state of the measured vehicle is the idle state, acquiring a three-axis acceleration value of the measured vehicle according to a detection period; and detecting whether an empty accelerator pedal stepping behavior occurs in each detection period according to the three-axis acceleration value in each detection period. The embodiment of the application can automatically detect whether an abnormal driving behavior of empty accelerator pedal stepping of a driver when the vehicle is in an idle state occurs according to the vehicle speed and the three-axis acceleration value of the vehicle, does not need to be connected with an ECU of the vehicle, and can accurately judge whether the abnormal driving behavior of empty accelerator pedal stepping of the driver when the vehicle is in the idle state occurs in the case that the connection with the ECU of the vehicle fails.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, apparatus, device, and medium for detecting driving behavior. Background Technology

[0002] Accelerating while the engine is in neutral refers to pressing the accelerator pedal. When a driver accelerates while the vehicle is idling, this not only increases unnecessary fuel consumption but also subjects internal engine components to significant inertial forces, reducing engine life and causing considerable damage to the vehicle. Detecting and warning drivers about this abnormal driving behavior can effectively reduce such actions.

[0003] In related technologies, a common driving behavior detection scheme is to connect an electronic device to the vehicle's electronic control unit (ECU) and detect abnormal driving behavior such as the driver pressing the accelerator pedal while the vehicle is idling.

[0004] The driving behavior detection schemes in related technologies mainly rely on the vehicle's ECU. If the docking with the vehicle's ECU fails, it is impossible to detect abnormal driving behavior such as the driver pressing the accelerator while the vehicle is idling. Summary of the Invention

[0005] This invention provides a driving behavior detection method, device, equipment, and medium to address the problem that driving behavior detection schemes in related technologies mainly rely on the vehicle's ECU, and cannot detect abnormal driving behavior such as the driver pressing the accelerator pedal while the vehicle is idling when the docking with the vehicle's ECU fails.

[0006] According to one aspect of the present invention, a driving behavior detection method is provided, comprising:

[0007] Obtain the current vehicle speed of the vehicle being tested;

[0008] Based on the current vehicle speed, detect whether the vehicle status of the tested vehicle is idling.

[0009] If the vehicle being tested is detected to be in an idling state, the three-axis acceleration value of the vehicle being tested is obtained according to the detection cycle.

[0010] Based on the triaxial acceleration values ​​within each testing cycle, detect whether any uncontrolled acceleration occurs within each testing cycle.

[0011] According to another aspect of the present invention, a driving behavior detection device is provided, comprising:

[0012] The speed acquisition module is used to acquire the current vehicle speed of the vehicle being tested.

[0013] The status detection module is used to detect whether the vehicle status of the tested vehicle is idling based on the current vehicle speed.

[0014] An acceleration value acquisition module is used to acquire the three-axis acceleration values ​​of the vehicle under test according to a detection cycle if the vehicle state of the vehicle under test is detected to be idling.

[0015] The behavior detection module is used to detect whether the accelerator pedal is pressed without braking during each detection cycle based on the triaxial acceleration values ​​within each detection cycle.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] At least one processor;

[0018] and a memory communicatively connected to the at least one processor;

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the driving behavior detection method according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the driving behavior detection method according to any embodiment of the present invention.

[0021] The technical solution of this invention obtains the current vehicle speed of the vehicle under test; then, based on the current vehicle speed, detects whether the vehicle is in an idling state; if the vehicle is detected to be in an idling state, the three-axis acceleration value of the vehicle is obtained according to the detection cycle; based on the three-axis acceleration value in each detection cycle, it detects whether the driver has engaged in idling acceleration behavior. This solves the problem that related technologies mainly rely on the vehicle's ECU for driving behavior detection, which cannot detect abnormal driving behavior such as idling acceleration when the vehicle is idling if the docking with the vehicle's ECU fails. The invention achieves the beneficial effect of automatically detecting whether abnormal driving behavior such as idling acceleration occurs based on the vehicle speed and three-axis acceleration value, without needing to dock with the vehicle's ECU, ensuring accurate determination of whether abnormal driving behavior such as idling acceleration occurs even if the docking with the vehicle's ECU fails.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of a driving behavior detection method provided in Embodiment 1 of the present invention.

[0025] Figure 2 This is a flowchart of a driving behavior detection method provided in Embodiment 2 of the present invention.

[0026] Figure 3 This is a schematic diagram of a driving behavior detection device provided in Embodiment 3 of the present invention.

[0027] Figure 4 A schematic diagram of the structure of an electronic device for implementing the driving behavior detection method of this invention. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "target," "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising," "including," and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] Example 1

[0031] Figure 1 This is a flowchart of a driving behavior detection method provided in Embodiment 1 of the present invention. This embodiment is applicable to detecting whether an abnormal driving behavior occurs, such as a driver pressing the accelerator while the vehicle is idling. The method can be executed by a driving behavior detection device, which can be implemented in hardware and / or software and can be configured in an electronic device.

[0032] like Figure 1 As shown, the method includes:

[0033] Step 101: Obtain the current vehicle speed of the vehicle being tested.

[0034] Optionally, the vehicle being tested is one where it is necessary to detect whether the driver is engaging in abnormal driving behavior such as pressing the accelerator while the vehicle is idling. The current vehicle speed is the speed of the vehicle being tested at the current moment.

[0035] Optionally, the Global Positioning System (GPS) module installed on the vehicle under test includes a vehicle speed sensor. The vehicle speed sensor is used to collect the vehicle speed of the vehicle under test at a preset sampling frequency. For example, the preset sampling frequency is 1 kHz. The electronic device establishes a communication connection with the GPS module and can obtain the vehicle speed collected by the vehicle speed sensor. The electronic device obtains the vehicle speed of the vehicle under test collected by the vehicle speed sensor at the current moment as the current vehicle speed of the vehicle under test.

[0036] Optionally, obtaining the current vehicle speed of the vehicle under test includes: obtaining the current vehicle speed of the vehicle under test at preset time intervals. The preset time interval can be set according to business needs. For example, the preset time interval is 1 minute. The electronic device obtains the current vehicle speed of the vehicle under test every 1 minute.

[0037] Step 102: Based on the current vehicle speed, detect whether the vehicle status of the tested vehicle is idling.

[0038] Optionally, vehicle states include, but are not limited to: idling, parked, driving, and vehicle malfunction. Idling refers to a vehicle being stationary while the engine is running. All other vehicle states besides idling are considered non-idling states.

[0039] Optionally, the step of detecting whether the vehicle state of the tested vehicle is idling based on the current vehicle speed includes: determining whether the current vehicle speed is less than a preset speed threshold; if the current vehicle speed is less than the preset speed threshold, then determining that the vehicle state of the tested vehicle is idling; if the current vehicle speed is greater than or equal to the preset speed threshold, then determining that the vehicle state of the tested vehicle is not idling.

[0040] Optionally, typically, when the vehicle under test is in an idling state, its speed will be less than a preset speed threshold; when the vehicle under test is not in an idling state, its speed will be greater than or equal to the preset speed threshold. Therefore, based on the current speed of the vehicle under test, it can be determined whether the vehicle is in an idling state: if the current speed is less than the preset speed threshold, the vehicle is determined to be in an idling state; if the current speed is greater than or equal to the preset speed threshold, the vehicle is determined to be in a non-idling state. For example, the preset speed threshold is 3 km / h. The preset speed threshold can be set based on the vehicle test data.

[0041] Step 103: If the vehicle status of the tested vehicle is detected to be idling, then the three-axis acceleration value of the tested vehicle is obtained according to the detection cycle.

[0042] Optionally, a triaxial accelerometer installed on the vehicle under test is used to collect the triaxial acceleration values ​​of the vehicle under test at a preset sampling frequency. For example, the preset sampling frequency is 1kHz.

[0043] Optionally, the triaxial acceleration values ​​of the vehicle under test are the acceleration values ​​of the vehicle under test on the mutually perpendicular X-axis, Y-axis, and Z-axis. The X-axis is aligned with the vehicle's forward direction, the Y-axis is aligned with the vehicle's left-right direction, and the Z-axis is aligned with the vehicle's vertical direction. An electronic device establishes a communication connection with the triaxial acceleration sensor installed on the vehicle under test, and can acquire the triaxial acceleration values ​​collected by the sensor. The triaxial acceleration values ​​of the vehicle under test include the X-axis acceleration value, Y-axis acceleration value, and Z-axis acceleration value. The X-axis acceleration value is the acceleration value of the vehicle under test along the X-axis. The Y-axis acceleration value is the acceleration value of the vehicle under test along the Y-axis. The Z-axis acceleration value is the acceleration value of the vehicle under test along the Z-axis.

[0044] Optionally, the detection cycle can be set according to business needs. For example, the detection cycle is 10 seconds. After detecting that the vehicle under test is in an idling state, each 10 seconds constitutes a detection cycle. For each detection cycle, the triaxial acceleration value collected by the triaxial accelerometer within the 10 seconds of the detection cycle is the triaxial acceleration value within that cycle. When the electronic device detects that the vehicle under test is in an idling state, it acquires the triaxial acceleration value of the vehicle under test according to the detection cycle, obtaining the triaxial acceleration value within each detection cycle. That is, the electronic device acquires the triaxial acceleration value collected by the triaxial accelerometer within 10 seconds every 10 seconds, obtaining the triaxial acceleration value within each 10-second interval.

[0045] Optionally, when the vehicle under test is in an idling state, the three-axis acceleration value of the vehicle under test is acquired according to the detection cycle. Based on the three-axis acceleration value in each detection cycle, it is detected whether abnormal driving behavior such as the driver stepping on the accelerator while the vehicle is idling occurs in each monitoring cycle, until the vehicle under test is updated from an idling state to a non-idling state.

[0046] Step 104: Based on the triaxial acceleration values ​​in each detection cycle, detect whether the accelerator pedal was pressed without braking during each detection cycle.

[0047] Optionally, the triaxial acceleration values ​​include X-axis acceleration, Y-axis acceleration, and Z-axis acceleration. The step of detecting whether a "free-throttle" behavior occurs within each detection cycle based on the triaxial acceleration values ​​within each detection cycle includes: performing the following operations on the triaxial acceleration values ​​within each detection cycle: filtering the X-axis, Y-axis, and Z-axis acceleration values ​​within each time interval of the detection cycle to obtain filtered X-axis, Y-axis, and Z-axis acceleration values ​​within each time interval; calculating the filtered X-axis, Y-axis, and Z-axis acceleration values ​​within each time interval. The standard deviation of the acceleration values; based on the standard deviations of the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​within each time interval, the standard deviation statistics of the detection period are determined; wherein, the standard deviation statistics of the detection period include the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values, the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values, and the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​within each time interval; based on the standard deviation statistics, it is determined whether any uncontrolled acceleration behavior occurred within the detection period.

[0048] Optionally, when the vehicle under test is idling, the vibration of the engine is relatively constant. If the driver accelerates while the vehicle is idling, the engine will spin rapidly, generating high-amplitude, high-frequency vibrations. These high-amplitude, high-frequency vibrations will cause significant variations in the amplitude of the triaxial acceleration values ​​collected by the triaxial acceleration sensor installed on the vehicle. Therefore, the amplitude variation of the triaxial acceleration values ​​can be used to determine whether the driver accelerated while the vehicle was idling.

[0049] Optionally, if the amplitude of the X-axis acceleration value, Y-axis acceleration value, or Z-axis acceleration value of the tested vehicle collected by the triaxial acceleration sensor changes significantly during the detection period, it indicates that the driver pressed the accelerator without a load during the detection period. That is, the driver pressed the accelerator without a load while the tested vehicle was idling, causing the engine of the tested vehicle to rotate rapidly and generate high-amplitude, high-frequency vibrations. This confirms that the driver pressed the accelerator without a load during the detection period.

[0050] Optionally, if the amplitude changes of the X-axis acceleration value, Y-axis acceleration value, or Z-axis acceleration value of the tested vehicle collected by the triaxial acceleration sensor are small during the detection period, it indicates that the driver did not press the accelerator pedal without braking during the detection period, and it can be determined that no uncontrolled acceleration behavior occurred during the detection period.

[0051] Optionally, each detection cycle consists of multiple time intervals. For example, the detection cycle is 10 seconds, and the time interval is 1 second. Each detection cycle consists of 10 time intervals.

[0052] Optionally, the X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​within each time interval of the detection period are filtered to obtain filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​for each time interval. This includes performing the following operations for each time interval of the detection period: using a preset high-pass filter to filter the X-axis acceleration values ​​within the time interval to obtain filtered X-axis acceleration values; using a preset high-pass filter to filter the Y-axis acceleration values ​​within the time interval to obtain filtered Y-axis acceleration values; and using a preset high-pass filter to filter the Z-axis acceleration values ​​within the time interval to obtain filtered Z-axis acceleration values. For example, the preset high-pass filter can be a Gaussian high-pass filter.

[0053] Optionally, the standard deviations of the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​within each time interval are calculated, including: performing the following operations for each time interval within the detection period: calculating the standard deviation of the filtered X-axis acceleration values ​​within the time interval; calculating the standard deviation of the filtered Y-axis acceleration values ​​within the time interval; and calculating the standard deviation of the filtered Z-axis acceleration values ​​within the time interval.

[0054] Optionally, the standard deviation of the filtered X-axis acceleration values ​​within the time interval is calculated, including: using the following formula to calculate the standard deviation of the filtered X-axis acceleration values ​​within the time interval:

[0055]

[0056] Where, σ x Let be the standard deviation of the filtered X-axis acceleration values ​​within the time interval, and n be the total number of filtered X-axis acceleration values ​​within the time interval. i Let be the i-th filtered X-axis acceleration value within the time interval, where i = 1, 2, ..., n, and μ is the average value of the filtered X-axis acceleration values ​​within the time interval.

[0057] Optionally, each detection cycle consists of multiple time intervals. For each detection cycle, the standard deviation statistics include the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values, the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values, and the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​within each time interval. The standard deviations of the filtered X-axis, Y-axis, and Z-axis acceleration values ​​within each time interval are statistically analyzed to determine the standard deviation statistics for the detection cycle.

[0058] Optionally, determining whether a "free-throttle" behavior occurred within the detection period based on the standard deviation statistics includes: calculating a first difference between the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values ​​in each time interval; calculating a second difference between the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values ​​in each time interval; calculating a third difference between the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​in each time interval; determining whether the first difference, the second difference, and the third difference are greater than a preset difference threshold; if the first difference, the second difference, or the third difference is greater than the preset difference threshold, then it is determined that a "free-throttle" behavior occurred within the detection period.

[0059] Optionally, if the first difference, the second difference, and the third difference are all less than or equal to a preset difference threshold, it is determined that no accelerator pedal movement occurred during the detection period.

[0060] Optionally, the first difference is the difference between the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values ​​within each time interval. The second difference is the difference between the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values ​​within each time interval. The third difference is the difference between the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​within each time interval.

[0061] Optionally, if the first difference, the second difference, or the third difference is greater than a preset difference threshold, it indicates that the amplitude of the X-axis acceleration value, Y-axis acceleration value, or Z-axis acceleration value of the tested vehicle collected by the triaxial acceleration sensor changes significantly within the detection period. This indicates that the driver accelerated without a load during the detection period, i.e., the driver accelerated without a load while the tested vehicle was idling. The engine of the tested vehicle turned extremely fast, generating high-amplitude, high-frequency vibrations. This confirms that the driver accelerated without a load during the detection period.

[0062] Optionally, if the first difference, the second difference, and the third difference are all less than or equal to a preset difference threshold, it indicates that the amplitude changes of the X-axis acceleration value, Y-axis acceleration value, or Z-axis acceleration value of the tested vehicle collected by the triaxial acceleration sensor are small during the detection period, and the driver did not press the accelerator pedal without braking during the detection period, thus confirming that no uncontrolled acceleration behavior occurred during the detection period.

[0063] Optionally, after determining that the accelerator pedal was pressed while driving during the detection period, the method further includes: outputting driving behavior alarm information through an alarm module.

[0064] Optionally, the driving behavior alarm information can be preset information used to alert the driver of the tested vehicle that abnormal driving behavior has occurred, such as the driver pressing the accelerator pedal while the tested vehicle is idling. The alarm module can be a device for outputting driving behavior alarm information.

[0065] Optionally, the driving behavior alarm information can be either a voice alarm or a text alarm. The voice alarm is a pre-set message indicating that the driver of the test vehicle has engaged in abnormal driving behavior, specifically by pressing the accelerator pedal while the vehicle is idling. The text alarm is a pre-set message indicating that the driver of the test vehicle has engaged in abnormal driving behavior, specifically by pressing the accelerator pedal while the vehicle is idling. The alarm module can be a voice player or a display screen integrated into an electronic device.

[0066] Optionally, the alarm module can output driving behavior alarm information, including playing driving behavior alarm voice messages through a voice player.

[0067] Optionally, the alarm module can output driving behavior alarm information, including displaying driving behavior alarm text on a display screen.

[0068] Optionally, after acquiring the three-axis acceleration value of the vehicle under test according to the detection cycle, the method further includes: after detecting that the vehicle state of the vehicle under test has been updated from idle state to non-idle state, stopping the acquisition of the three-axis acceleration value of the vehicle under test according to the detection cycle.

[0069] Optionally, when the electronic device newly acquires a current vehicle speed greater than or equal to a preset speed threshold, it determines that the vehicle state of the tested vehicle has been updated from idle to non-idle. After detecting that the vehicle state of the tested vehicle has been updated from idle to non-idle, it stops acquiring the three-axis acceleration value of the tested vehicle according to the detection cycle, thereby stopping the detection of abnormal driving behavior such as the driver pressing the accelerator while the vehicle is idling when the vehicle state of the tested vehicle is non-idle.

[0070] The technical solution of this invention obtains the current vehicle speed of the vehicle under test; then, based on the current vehicle speed, detects whether the vehicle is in an idling state; if the vehicle is detected to be in an idling state, the three-axis acceleration value of the vehicle is obtained according to the detection cycle; based on the three-axis acceleration value in each detection cycle, it detects whether the driver has engaged in idling acceleration behavior. This solves the problem that related technologies mainly rely on the vehicle's ECU for driving behavior detection, which cannot detect abnormal driving behavior such as idling acceleration when the vehicle is idling if the docking with the vehicle's ECU fails. The invention achieves the beneficial effect of automatically detecting whether abnormal driving behavior such as idling acceleration occurs based on the vehicle speed and three-axis acceleration value, without needing to dock with the vehicle's ECU, ensuring accurate determination of whether abnormal driving behavior such as idling acceleration occurs even if the docking with the vehicle's ECU fails.

[0071] Example 2

[0072] Figure 2 This is a flowchart illustrating a driving behavior detection method according to Embodiment 2 of the present invention. Embodiments of the present invention can be combined with various optional solutions from one or more of the above embodiments. For example... Figure 2 As shown, the method includes:

[0073] Step 201: Obtain the current vehicle speed of the vehicle being tested.

[0074] Step 202: Determine whether the current vehicle speed is less than a preset speed threshold: if yes, proceed to step 203; if no, proceed to step 206.

[0075] Step 203: Determine that the vehicle status of the tested vehicle is idling.

[0076] Step 204: Obtain the three-axis acceleration values ​​of the vehicle under test according to the detection cycle.

[0077] Optionally, the detection cycle is 10 seconds, with a time interval of 1 second. Each detection cycle consists of 10 time intervals. After detecting that the vehicle under test is in an idling state, each 10-second period constitutes a detection cycle. For each detection cycle, the triaxial acceleration value collected by the triaxial accelerometer within the 10 seconds of the detection cycle is the triaxial acceleration value within that detection cycle. When the electronic device detects that the vehicle under test is in an idling state, it acquires the triaxial acceleration value of the vehicle under test according to the detection cycle, obtaining the triaxial acceleration value within each detection cycle. That is, the electronic device acquires the triaxial acceleration value collected by the triaxial accelerometer within 10 seconds every 10 seconds, obtaining the triaxial acceleration value within each 10-second period.

[0078] Step 205: Based on the triaxial acceleration values ​​in each detection cycle, detect whether the accelerator pedal was pressed without braking during each detection cycle.

[0079] Optionally, the triaxial acceleration values ​​include X-axis acceleration, Y-axis acceleration, and Z-axis acceleration. The step of detecting whether a "free-throttle" behavior occurs within each detection cycle based on the triaxial acceleration values ​​within each detection cycle includes: performing the following operations on the triaxial acceleration values ​​within each detection cycle: filtering the X-axis, Y-axis, and Z-axis acceleration values ​​within each time interval of the detection cycle to obtain filtered X-axis, Y-axis, and Z-axis acceleration values ​​within each time interval; calculating the filtered X-axis, Y-axis, and Z-axis acceleration values ​​within each time interval. The standard deviation of the acceleration values; based on the standard deviations of the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​within each time interval, the standard deviation statistics of the detection period are determined; wherein, the standard deviation statistics of the detection period include the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values, the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values, and the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​within each time interval; based on the standard deviation statistics, it is determined whether any uncontrolled acceleration behavior occurred within the detection period.

[0080] Optionally, determining whether a "free-throttle" behavior occurred within the detection period based on the standard deviation statistics includes: calculating a first difference between the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values ​​in each time interval; calculating a second difference between the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values ​​in each time interval; calculating a third difference between the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​in each time interval; determining whether the first difference, the second difference, and the third difference are greater than a preset difference threshold; if the first difference, the second difference, or the third difference is greater than the preset difference threshold, then it is determined that a "free-throttle" behavior occurred within the detection period.

[0081] Optionally, after acquiring the three-axis acceleration value of the vehicle under test according to the detection cycle, the method further includes: after detecting that the vehicle state of the vehicle under test has been updated from idle state to non-idle state, stopping the acquisition of the three-axis acceleration value of the vehicle under test according to the detection cycle.

[0082] Optionally, when the vehicle under test is in an idling state, the three-axis acceleration value of the vehicle under test is acquired according to the detection cycle. Based on the three-axis acceleration value in each detection cycle, it is detected whether abnormal driving behavior such as the driver stepping on the accelerator while the vehicle is idling occurs in each monitoring cycle, until the vehicle under test is updated from an idling state to a non-idling state.

[0083] Step 206: Determine that the vehicle status of the tested vehicle is non-idling.

[0084] Optionally, if the vehicle being tested is in a non-idling state, it is determined that it is not necessary to detect whether the driver has engaged in abnormal driving behavior such as pressing the accelerator while the vehicle is idling, and the process ends.

[0085] The technical solution of this invention can acquire the three-axis acceleration value of the vehicle under test according to the detection cycle when the vehicle is in an idling state. Based on the three-axis acceleration value in each detection cycle, it can detect whether the abnormal driving behavior of the driver stepping on the accelerator while the vehicle is idling occurs in each monitoring cycle. It does not require docking with the vehicle's ECU, and can accurately determine whether the abnormal driving behavior of the driver stepping on the accelerator while the vehicle is idling occurs even if docking with the vehicle's ECU fails.

[0086] Example 3

[0087] Figure 3 This is a schematic diagram of a driving behavior detection device according to Embodiment 3 of the present invention. The device can be configured in an electronic device. Figure 3As shown, the device includes: a speed acquisition module 301, a state detection module 302, an acceleration value acquisition module 303, and a behavior detection module 304.

[0088] The system includes a speed acquisition module 301 for acquiring the current vehicle speed of the vehicle under test; a state detection module 302 for detecting whether the vehicle under test is in an idling state based on the current vehicle speed; an acceleration value acquisition module 303 for acquiring the three-axis acceleration value of the vehicle under test according to a detection cycle if the vehicle under test is detected to be in an idling state; and a behavior detection module 304 for detecting whether the vehicle has engaged in idling acceleration behavior within each detection cycle based on the three-axis acceleration value within each detection cycle.

[0089] The technical solution of this invention obtains the current vehicle speed of the vehicle under test; then, based on the current vehicle speed, detects whether the vehicle is in an idling state; if the vehicle is detected to be in an idling state, the three-axis acceleration value of the vehicle is obtained according to the detection cycle; based on the three-axis acceleration value in each detection cycle, it detects whether the driver has engaged in idling acceleration behavior. This solves the problem that related technologies mainly rely on the vehicle's ECU for driving behavior detection, which cannot detect abnormal driving behavior such as idling acceleration when the vehicle is idling if the docking with the vehicle's ECU fails. The invention achieves the beneficial effect of automatically detecting whether abnormal driving behavior such as idling acceleration occurs based on the vehicle speed and three-axis acceleration value, without needing to dock with the vehicle's ECU, ensuring accurate determination of whether abnormal driving behavior such as idling acceleration occurs even if the docking with the vehicle's ECU fails.

[0090] In an optional embodiment of the present invention, the state detection module 302 is specifically used to: determine whether the current vehicle speed is less than a preset speed threshold; if the current vehicle speed is less than the preset speed threshold, then determine that the vehicle state of the tested vehicle is idling; if the current vehicle speed is greater than or equal to the preset speed threshold, then determine that the vehicle state of the tested vehicle is non-idling.

[0091] In an optional embodiment of the present invention, the triaxial acceleration values ​​may include X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values; the behavior detection module 304 is specifically configured to: perform the following operations on the triaxial acceleration values ​​in each detection cycle: filter the X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​in each time interval of the detection cycle to obtain filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​in each time interval; calculate the standard value of the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​in each time interval. Standard deviation; based on the standard deviations of the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​within each time interval, the standard deviation statistics of the detection period are determined; wherein, the standard deviation statistics of the detection period include the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values, the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values, and the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​within each time interval; based on the standard deviation statistics, it is determined whether any uncontrolled acceleration behavior occurred within the detection period.

[0092] In an optional embodiment of the present invention, the behavior detection module 304, when performing the operation of determining whether a "free-throttle" behavior has occurred within the detection period based on the standard deviation statistics, is specifically configured to: calculate a first difference between the maximum and minimum values ​​of the standard deviations of the filtered X-axis acceleration values ​​within each time interval; calculate a second difference between the maximum and minimum values ​​of the standard deviations of the filtered Y-axis acceleration values ​​within each time interval; calculate a third difference between the maximum and minimum values ​​of the standard deviations of the filtered Z-axis acceleration values ​​within each time interval; determine whether the first difference, the second difference, and the third difference are greater than a preset difference threshold; if the first difference, the second difference, or the third difference is greater than the preset difference threshold, then it is determined that a "free-throttle" behavior has occurred within the detection period.

[0093] In an optional embodiment of the present invention, the behavior detection module 304 may also be used to: output driving behavior alarm information through the alarm module.

[0094] In an optional embodiment of the present invention, the speed acquisition module 301 is specifically used to: acquire the current vehicle speed of the vehicle under test according to a preset time interval.

[0095] In an optional embodiment of the present invention, the acceleration value acquisition module 303 is further configured to: stop acquiring the three-axis acceleration value of the vehicle under test according to the detection cycle after detecting that the vehicle state of the vehicle under test has been updated from the idling state to the non-idling state.

[0096] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0097] The aforementioned driving behavior detection device can execute the driving behavior detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the driving behavior detection method.

[0098] Example 4

[0099] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement the driving behavior detection method of embodiments of the present invention is shown. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the invention described and / or claimed herein.

[0100] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or a computer program constructed from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0101] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0102] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as driving behavior detection methods.

[0103] In some embodiments, the driving behavior detection method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is built into RAM 13 and executed by processor 11, one or more steps of the driving behavior detection method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the driving behavior detection method by any other suitable means (e.g., by means of firmware).

[0104] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0105] Computer programs for implementing the driving behavior detection method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0106] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0107] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0108] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0109] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0110] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0111] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A driving behavior detection method characterized by, include: Obtain the current vehicle speed of the vehicle being tested; Based on the current vehicle speed, detect whether the vehicle status of the tested vehicle is idling. If the vehicle being tested is detected to be in an idling state, the three-axis acceleration value of the vehicle being tested is obtained according to the detection cycle. Based on the triaxial acceleration values ​​in each testing cycle, detect whether there is any uncontrolled acceleration behavior in each testing cycle; The triaxial acceleration values ​​include X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values; The method of detecting whether revving the engine without engaging in any operation within each detection cycle, based on the triaxial acceleration values ​​within each detection cycle, includes: Perform the following operations for the triaxial acceleration values ​​within each detection cycle: The X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​in each time interval within the detection period are filtered to obtain the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​in each time interval. Calculate the standard deviation of the filtered X-axis acceleration, Y-axis acceleration, and Z-axis acceleration values ​​within each time interval; The standard deviation statistics of the detection period are determined based on the standard deviations of the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​within each time interval. The standard deviation statistics of the detection period include the maximum and minimum values ​​of the standard deviation of the filtered X-axis acceleration values ​​in each time interval, the maximum and minimum values ​​of the standard deviation of the filtered Y-axis acceleration values ​​in each time interval, and the maximum and minimum values ​​of the standard deviation of the filtered Z-axis acceleration values ​​in each time interval. Based on the standard deviation statistics, determine whether revving the engine without engaging in any activity occurred within the detection period, including: Calculate the first difference between the maximum and minimum values ​​of the standard deviation of the filtered X-axis acceleration values ​​within each time interval; Calculate the second difference between the maximum and minimum values ​​in the standard deviation of the filtered Y-axis acceleration values ​​within each time interval; Calculate the third difference between the maximum and minimum values ​​in the standard deviation of the filtered Z-axis acceleration values ​​within each time interval; Determine whether the first difference, the second difference, and the third difference are greater than a preset difference threshold; If the first difference, the second difference, or the third difference is greater than a preset difference threshold, then it is determined that the accelerator pedal was pressed without a load during the detection period.

2. The method according to claim 1, characterized in that, The step of detecting whether the vehicle status of the tested vehicle is idling based on the current vehicle speed includes: Determine whether the current vehicle speed is less than a preset speed threshold; If the current vehicle speed is less than a preset speed threshold, then the vehicle state of the tested vehicle is determined to be idling. If the current vehicle speed is greater than or equal to a preset speed threshold, then the vehicle state of the tested vehicle is determined to be non-idling.

3. The method according to claim 1, characterized in that, After determining that revving the engine while idle occurred within the detection period, the process also includes: The alarm module outputs driving behavior alarm information.

4. The method according to claim 1, characterized in that, The process of obtaining the current vehicle speed of the vehicle under test includes: The current vehicle speed of the tested vehicle is obtained at preset time intervals.

5. The method according to claim 1, characterized in that, After obtaining the three-axis acceleration values ​​of the vehicle under test according to the testing cycle, the process also includes: After detecting that the vehicle status of the tested vehicle has changed from idle to non-idle, the acquisition of the three-axis acceleration value of the tested vehicle according to the detection cycle is stopped.

6. A driving behavior detection device, characterized in that, include: The speed acquisition module is used to acquire the current vehicle speed of the vehicle being tested. The status detection module is used to detect whether the vehicle status of the tested vehicle is idling based on the current vehicle speed. An acceleration value acquisition module is used to acquire the three-axis acceleration values ​​of the vehicle under test according to a detection cycle if the vehicle state of the vehicle under test is detected to be idling. The behavior detection module is used to detect whether the behavior of pressing the accelerator without pressing it occurs in each detection cycle based on the triaxial acceleration values ​​in each detection cycle. The triaxial acceleration values ​​include X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values; The method of detecting whether revving the engine without engaging in any operation within each detection cycle, based on the triaxial acceleration values ​​within each detection cycle, includes: Perform the following operations for the triaxial acceleration values ​​within each detection cycle: The X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​in each time interval within the detection period are filtered to obtain the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​in each time interval. Calculate the standard deviation of the filtered X-axis acceleration, Y-axis acceleration, and Z-axis acceleration values ​​within each time interval; The standard deviation statistics of the detection period are determined based on the standard deviations of the filtered X-axis acceleration values, Y-axis acceleration values, and Z-axis acceleration values ​​within each time interval. The standard deviation statistics of the detection period include the maximum and minimum values ​​of the standard deviation of the filtered X-axis acceleration values ​​in each time interval, the maximum and minimum values ​​of the standard deviation of the filtered Y-axis acceleration values ​​in each time interval, and the maximum and minimum values ​​of the standard deviation of the filtered Z-axis acceleration values ​​in each time interval. Based on the standard deviation statistics, determine whether revving the engine without engaging in any activity occurred within the detection period, including: Calculate the first difference between the maximum and minimum values ​​of the standard deviation of the filtered X-axis acceleration values ​​within each time interval; Calculate the second difference between the maximum and minimum values ​​in the standard deviation of the filtered Y-axis acceleration values ​​within each time interval; Calculate the third difference between the maximum and minimum values ​​in the standard deviation of the filtered Z-axis acceleration values ​​within each time interval; Determine whether the first difference, the second difference, and the third difference are greater than a preset difference threshold; If the first difference, the second difference, or the third difference is greater than a preset difference threshold, then it is determined that the accelerator pedal was pressed without a load during the detection period.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the driving behavior detection method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the driving behavior detection method according to any one of claims 1-5.

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