Vehicle event measurement method and device

Abstract

The present invention discloses a vehicle event measurement method and device. A vehicle state judgment method based on the fusion of acceleration and angular velocity sensors is applied to judge vehicle events. The method comprises: acquiring real-time data from the acceleration and angular velocity sensors; using a filtering fusion algorithm to obtain the real-time state and change data of the vehicle; judging vehicle events according to actual reasonable data thresholds, including rollover, sudden acceleration and deceleration, sudden braking, vehicle collision, vehicle fall and sharp turn; and outputting vehicle events.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and mainly to a vehicle event measurement method and device. Background Art

[0002] Vehicle event status measurement is a fundamental measurement project in the transportation and automotive industries. Examples include rollovers, sudden acceleration and deceleration, sudden braking, collisions, falls, and sharp turns. Accurate and real-time vehicle event assessment and measurement are crucial for driving and traffic safety, and form a crucial infrastructure for intelligent driving and transportation.

[0003] For vehicles without intelligence, vehicle events rely on the driver's sensory judgment, which has serious problems with accuracy and real-time performance. Traditional speed sensors have problems with slow response and insufficient accuracy.

[0004] Modern semiconductor accelerometers can accurately measure a vehicle's angular velocity in real time. Combined with filtering and fusion algorithms, they can measure both the vehicle's speed and attitude. Based on thresholds for various state changes and algorithms, they can be used to identify vehicle events in real time. Summary of the Invention

[0005] To address these shortcomings, according to the first aspect of the present invention, a vehicle event measurement method and device are proposed. These methods can identify vehicle events, including rollovers, sudden acceleration and deceleration, sudden braking, collisions, falls, and sharp turns, in real time with high accuracy and real-time performance. This method has practical application in intelligent driving and smart transportation, featuring low cost, high real-time performance, and multiple interfaces. The specific steps are as follows:

[0006] S1, real-time collection of data from the acceleration and angular velocity sensor;

[0007] S2. Use the filter fusion algorithm to obtain the vehicle's true speed, acceleration, angular velocity, and angle state;

[0008] S3. According to the event threshold of the actual vehicle event, the vehicle event is judged, including sudden acceleration and deceleration, sudden braking, vehicle collision, vehicle fall, sharp turn and rollover.

[0009] Furthermore, the step S2 specifically includes:

[0010] Construct the error between the expected gravity vector and the measured gravity vector to perform attitude estimation;

[0011] Using a vector cross product to obtain an angle measurement error, using the measurement error to compensate for the angular velocity measurement value, and updating the attitude;

[0012] The acceleration is integrated over time in the new posture to obtain the real speed of the vehicle.

[0013] Furthermore, the method of constructing an error between an expected gravity vector and a measured gravity vector for attitude estimation specifically includes:

[0014] The initial attitude is obtained through the accelerometer data and magnetometer data at rest;

[0015] The initial posture is converted into quaternion form, and the desired gravity vector is obtained by rotating the standard gravity vector in the geographic coordinate system to the body coordinate system. ;

[0016] In a state of rest or linear motion, the acceleration value measured by the accelerometer is the gravity vector ;

[0017] Using the desired gravity vector Gravity vector Get the angular velocity of the attitude error .

[0018] Furthermore, the method of obtaining the angle measurement error by using the vector cross product, compensating the angular velocity measurement value by using the measurement error, and updating the posture further includes the following specific steps:

[0019] Angular velocity measurements obtained from the gyroscope ;

[0020] The angular velocity of the attitude error Add a certain proportion to the angular velocity measurement value to compensate for the error of the angular velocity measurement value: , where K represents the filter gain value;

[0021] The compensated angular velocity measurement value Perform time integration to obtain a new posture.

[0022] Furthermore, the time integration of the acceleration in the new posture further includes the following specific steps:

[0023] Get the gravity vector under the new attitude , using the gravity vector Subtract the gravity vector at the new attitude , to obtain the true linear acceleration :

[0024] The true linear acceleration Convert from the body coordinate system to the geographic coordinate system or inertial coordinate system;

[0025] The transformed linear acceleration Perform time integration to obtain a new velocity estimate.

[0026] Furthermore, the quaternion form is specifically expressed as follows:

[0027] ;

[0028] in, represents the real part of the quaternion, 、 and Represent the three imaginary parts of the quaternion, represents the roll angle, represents the pitch angle, Indicates the yaw angle.

[0029] Furthermore, the angular velocity measurement value after compensation Perform time integration, where the quaternion differentiation method is used for time integration. The specific formula is as follows:

[0030] ;

[0031] in, Represents the derivative of the quaternion q with respect to time, represents the rotation rate of the vehicle, q represents the quaternion of the current rotation state, represents the angular velocity quaternion, Represents the quaternion multiplication symbol.

[0032] Furthermore, based on the obtained real motion speed, acceleration, angular velocity and angle state, an event threshold for determining a vehicle event is obtained. The event threshold specifically includes:

[0033] If the vehicle tilts more than 35 degrees, it is considered a rollover vehicle;

[0034] If the vehicle's forward acceleration is ≥0.5g, it is considered rapid acceleration;

[0035] The vehicle's forward acceleration is ≤-0.5g, which is considered a sudden deceleration;

[0036] If the vehicle's forward acceleration is ≤ -1g, it is considered an emergency brake;

[0037] If the vehicle's forward acceleration is ≤ -10g, it is considered a vehicle collision;

[0038] If the vertical acceleration of the vehicle is ≤0.2g within 0.45 seconds, it is considered a fall event;

[0039] The vehicle's turning angular velocity is ≥79 degrees per second and the vehicle's forward acceleration is greater than 20 km / , it is determined to be a sharp turn.

[0040] According to a second aspect of the present invention, a computer program product is provided, on which one or more computer programs are stored. When the one or more computer programs are executed by a computer processor, the above method is implemented.

[0041] The above one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

[0042] This invention combines measurement data from an accelerometer and an angular velocity meter to provide high-precision attitude estimation and event recognition capabilities. First, through the use of a filtering fusion algorithm, the advantages of both sensors are effectively combined, avoiding the errors associated with using them separately. The angular velocity meter provides good stability at high frequencies, while the accelerometer maintains good long-term stability at low frequencies. The two complement each other, effectively reducing the effects of noise and drift.

[0043] The present invention can also accurately identify various driving events, such as sudden acceleration, sudden braking, and rollover, helping to improve vehicle safety and intelligence. By analyzing sensor data in real time, the system can respond promptly during driving and make judgments and handle emergencies.

[0044] The fusion algorithm effectively addresses noise and drift in sensor data, improving the accuracy of vehicle posture and velocity estimation. Furthermore, the real-time event recognition system efficiently identifies unexpected driving events, ensuring driving safety and avoiding the slow response of traditional vehicle safety systems. Overall, this approach significantly improves the reliability, stability, and safety of vehicle systems through precise data fusion and intelligent event recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings are included to provide a further understanding of the embodiments and are incorporated into and constitute a part of this specification. The accompanying drawings illustrate the embodiments and, together with the description, serve to explain the principles of the present invention. Other embodiments and many of the expected advantages of the embodiments will be readily apparent as they become better understood by reference to the following detailed description. The elements of the drawings are not necessarily to scale with respect to each other. Like reference numerals designate corresponding similar parts.

[0046] Figure 1 A schematic flow chart of a vehicle event measurement method according to an embodiment of the present invention is shown.

[0047] Figure 2 A flowchart of a specific method for obtaining the true speed of a vehicle and judging vehicle events using a filtering fusion algorithm according to an embodiment of the present invention is shown.

[0048] Figure 3 It is a structural diagram of a computer system suitable for implementing the electronic device of the embodiment of the present application. DETAILED DESCRIPTION

[0049] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0050] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0051] Figure 1 FIG. 4 shows a flow chart of a vehicle event measurement method according to an embodiment of the present invention. Figure 1 As shown:

[0052] S1, real-time collection of data from the acceleration and angular velocity sensor;

[0053] Vehicle systems continuously acquire acceleration and angular velocity data through sensors during operation. Accelerometers detect the acceleration or deceleration of an object, while angular velocity sensors measure its rotational rate. This data is real-time, meaning it is continuously updated, allowing the system to understand the object's motion status at all times.

[0054] S2. Use the filter fusion algorithm to obtain the vehicle's true speed, acceleration, angular velocity and angle state, such as Figure 2 As shown, the specific steps include:

[0055] Construct the error between the expected gravity vector and the measured gravity vector to perform attitude estimation;

[0056] Using a vector cross product to obtain an angle measurement error, using the measurement error to compensate for the angular velocity measurement value, and updating the attitude;

[0057] The acceleration is integrated over time in the new posture to obtain the real speed of the vehicle.

[0058] The method of constructing an error between an expected gravity vector and a measured gravity vector for attitude estimation specifically includes:

[0059] The initial attitude is obtained through the accelerometer data and magnetometer data at rest;

[0060] The initial posture is converted into quaternion form, and the desired gravity vector is obtained by rotating the standard gravity vector in the geographic coordinate system (usually [0,0,-g]) to the body coordinate system. ;

[0061] The accelerometer measures acceleration including gravity. In a stationary or linear motion state, the acceleration value measured by the accelerometer is the gravity vector ;

[0062] Using the desired gravity vector Gravity vector Get the angular velocity of the attitude error This error reflects the deviation between the current attitude estimate and the actual acceleration direction. This vector can be understood as the required correction angular velocity .

[0063] The step of converting the initial posture into a quaternion form further includes:

[0064] The accelerometer senses the gravitational acceleration when the device is stationary, and the output data is used to calculate the pitch and roll angles of the device.

[0065] A magnetometer is used to measure the relative direction of the device and the Earth's magnetic field, which is used to calculate the yaw angle.

[0066] When at rest, the device's accelerometer data reflects the direction of gravity, while the magnetometer gives the direction of magnetic north.

[0067] The raw data of the accelerometer (acceleration vector ) Calculate the pitch and roll angles of the device:

[0068] Roll angle : According to the accelerometer and Axis data:

[0069] ;

[0070] Pitch angle: According to the accelerometer and Axis data:

[0071] ;

[0072] These angles reflect the tilt of the device relative to the horizontal plane of the ground.

[0073] The yaw angle is the angle between the geomagnetic direction measured by the magnetometer and the magnetic north direction of the device. The data output by the magnetometer can be used to calculate the yaw angle of the device:

[0074] ;

[0075] in, and Represent the components of the magnetometer in the x and y directions respectively;

[0076] After obtaining the pitch, roll, and yaw angles, the Euler angles need to be converted into quaternions. Quaternions are a mathematical structure used to represent rotations. They are more stable than Euler angles. The quaternion form is specifically represented as follows:

[0077] ;

[0078] in, represents the real part of the quaternion, 、 and Represent the three imaginary parts of the quaternion, represents the roll angle, represents the pitch angle, Indicates the yaw angle.

[0079] The formula for quaternion is: , i, j, k represent the three imaginary units of the quaternion respectively.

[0080] Convert the standard gravity vector in the geographic coordinate system to the (Assuming that the acceleration due to gravity is 9.81m / ) is converted to the body coordinate system, the quaternion rotation formula is as follows:

[0081] ;

[0082] Among them, q represents the rotation quaternion from the geographic coordinate system to the body coordinate system, represents the standard gravity vector in the geographic coordinate system, Represents the gravity vector in the body coordinate system.

[0083] The method of obtaining an angle measurement error by using a vector cross product, compensating an angular velocity measurement value by using the measurement error, and updating the attitude further comprises:

[0084] Angular velocity measurements obtained from the gyroscope , used to describe the instantaneous rotation change;

[0085] The angular velocity of the attitude error Add a certain proportion to the angular velocity measurement value to compensate for the error of the angular velocity measurement value: , where K represents the filter gain value; this step is to use the low-frequency information (anti-drift) provided by the accelerometer to compensate for the low-frequency error of the gyroscope.

[0086] The compensated angular velocity measurement value Perform time integration to obtain a new posture. The quaternion differential method is used for time integration. The specific formula is as follows:

[0087] ;

[0088] in, Represents the derivative of the quaternion q with respect to time, represents the rotation rate of the vehicle, q represents the quaternion of the current rotation state, represents the angular velocity quaternion, Represents the quaternion multiplication symbol.

[0089] Among them, the angular velocity quaternion The structure is: , ( , , ) represents the angular velocity vector.

[0090] The time integration of the acceleration in the new posture further includes the following specific steps:

[0091] Get the gravity vector under the new attitude , using the gravity vector Subtract the gravity vector at the new attitude , to obtain the true linear acceleration :

[0092] The true linear acceleration Convert from the body coordinate system to the geographic coordinate system or inertial coordinate system;

[0093] The transformed linear acceleration Perform time integration to obtain a new velocity estimate.

[0094] In attitude prediction, the Euler integral can be used to approximate the update of the quaternion:

[0095] ;

[0096] in, The quaternion representing the current moment, Represents the quaternion at the previous moment, represents the angular velocity vector, represents the angular velocity quaternion matrix, Indicates the use of intervals, Represents the scaling factor. Perform normalization to reduce errors.

[0097] This quaternion attitude prediction method uses Euler integration to rapidly integrate the vehicle's angular velocity. Combined with the normalized update of the unit quaternion, it achieves stable, continuous, and efficient estimation of the vehicle's three-dimensional attitude (roll, pitch, and yaw). Compared to traditional Euler angle integration, this method effectively avoids the gimbal lock problem, maintaining the numerical stability and physical interpretability of the attitude representation. It is suitable for vehicle navigation and control systems with high real-time requirements and limited computing resources. It ensures the accuracy and robustness of attitude estimation while maintaining computational efficiency.

[0098] Calculate the yaw angle again from the updated quaternion to predict whether the attitude solution is correct:

[0099] ;

[0100] In summary, the advantages of the fusion algorithm are:

[0101] Short-term accuracy: The gyroscope's angular velocity data is stable and reliable in a short period of time, suitable for rapid dynamic response of attitude;

[0102] Long-term stability: The gravity direction of the accelerometer is more stable after long-term averaging, which can be used to correct the offset caused by gyro integration;

[0103] Suppressing drift and jitter: The fused system avoids the drift caused by gyro integration alone, while also reducing the impact of high-frequency vibrations from the accelerometer.

[0104] Good real-time performance: Only simple vector operations and integration are required, suitable for embedded real-time processing.

[0105] S3. According to the event threshold of the actual vehicle event, the vehicle event is judged, including sudden acceleration and deceleration, sudden braking, vehicle collision, vehicle fall, sharp turn and rollover; finally, the vehicle event is output.

[0106] The basis for judging vehicle events based on the threshold obtained through training is as follows:

[0107] A vehicle tilting at an angle of 35 degrees or more is considered a rollover. According to the standards of GB7258-2017, "Technical Conditions for Motor Vehicle Operation Safety," a passenger car with no load and static conditions must maintain a roll stability angle greater than 35 degrees to the left and right. This means that under normal ground adhesion conditions, a vehicle with a roll angle of 35 degrees may roll over.

[0108] For passengers, the acceleration exceeds 0.3g (g is the acceleration due to gravity, generally 9.8m / or 10 m / ) will alert, 1g is equivalent to the limit of emergency braking, and passengers will have a clear physical feeling. Therefore, if the vehicle's forward acceleration is ≤-1g, it is judged as an emergency brake;

[0109] Normally, lightly pressing the accelerator, it takes 5 seconds to accelerate from 0 to 30 km / h. Deeply pressing the accelerator, it takes 2 seconds to accelerate from 0 to 40-50 km / h. Repeatedly extract the above experimental data and take the average. In this embodiment, the sampled data is as follows:

[0110]

[0111] In the above experiment, when the acceleration is greater than 0.5g, the driver and passengers subjectively report a strong sense of push back. Therefore, if the vehicle's forward acceleration is ≥0.5g, it can be determined as rapid acceleration.

[0112] Similarly, in a sudden deceleration, release the accelerator and quickly apply the brakes, decelerating from 50 km / h to 0 within 2 seconds. Record the acceleration change process. If the deceleration reaches -0.59g within 2 seconds, the passengers and driver will experience a noticeable forward lean. Therefore, the vehicle's forward acceleration is ≤-0.5g, which can be determined as a sudden deceleration.

[0113] According to GB11551-2014 "Occupant Protection in Motor Vehicle Frontal Collisions," the theoretical collision acceleration is 23.6g at a speed of 50km / h and a collision time of 60ms. In scenario testing, at lower speeds, such as around 30km / h, the IMU records peak accelerations of 10g to 12g. Therefore, a collision is considered if the vehicle's forward acceleration is ≤ -10g. A severe collision occurs when the forward acceleration reaches -30g.

[0114] In the test experiment, the vehicle fell from a height of 1 meter, which took about 0.45 seconds. During this period, the vehicle was in a weightless state, and the vertical acceleration collected by the IMU was 0.2g. Therefore, if the vertical acceleration of the vehicle within 0.45 seconds was ≤0.2g, it could be determined as a fall event;

[0115] According to the motor vehicle driving regulations, when driving a motor vehicle at a sharp turn, the maximum speed shall not exceed 30 kilometers per hour (8.3 meters per second). The turning radius of a small car is 6 meters, and that of a truck ranges from 9 meters to 20 meters. Taking a small car as a reference, the turning circumference is meters, the vehicle takes 37.68 / 8.3=4.54 seconds to make a circle, 360 / 4.54 79 degrees per second; In the simulation experiment of this embodiment, when the small tricycle makes a sharp turn, the turning angular velocity is greater than 79 degrees and the vehicle speed is more than 20 kilometers per hour; Therefore, the vehicle turning angular velocity is ≥ 79 degrees per second and the vehicle forward acceleration is greater than 20km / , it is judged as a sharp turn.

[0116] according to Figure 2 As shown, the judgment process of an event occurring during vehicle driving is as follows:

[0117] When the vehicle's turning angular velocity is greater than 79 degrees per second and the vehicle's forward acceleration is greater than 20 km / h , it is determined that the vehicle is making a sharp turn; if the vehicle is not making a sharp turn and the roll angle is greater than or equal to 35 degrees, it is determined that the vehicle is overturning; if the vehicle maintains normal driving and continues to obtain forward acceleration, if the forward acceleration is less than or equal to -10g, the collision state is triggered, and the collision level is further determined. If the forward acceleration is less than or equal to -30g, it is determined that the vehicle has a serious collision; if the forward acceleration of the vehicle is greater than -10g but less than or equal to -1g, it is determined that the vehicle is braking suddenly; if the forward acceleration of the vehicle is greater than -1g and greater than 0.5g or less than -0.5g, it is determined that the vehicle is accelerating or decelerating suddenly; if the forward acceleration of the vehicle maintains normal driving, the vertical acceleration is less than or equal to 0.2g and the duration is within 0.45 seconds, it is determined that the vehicle has fallen; if no vehicle event is triggered, the vehicle event detection is continuously maintained.

[0118] When an event occurs, the vehicle system promptly records the time, location, vehicle status (such as speed, acceleration, angle, etc.), and possible causes. Event records facilitate subsequent analysis, accident investigation, and optimization of prediction and warning systems.

[0119] For serious events (such as collisions, rollovers, etc.), the system should promptly issue an alarm signal and trigger an emergency response (such as emergency braking, alarm sounds, etc.) according to actual needs. At the same time, relevant departments or personnel can obtain event data through the remote system for processing.

[0120] In summary, the present invention proposes a high-precision, real-time vehicle event recognition method suitable for the fields of intelligent driving and smart transportation. First, the system collects vehicle acceleration and angular velocity sensor data in real time to ensure the continuity and accuracy of the basic data. Then, a filter fusion algorithm is used to process the sensor data. By calculating the cross product error between the gravity vector measured by the accelerometer and the expected gravity vector in the estimated posture, the angular velocity measurement value is compensated, and the compensated angular velocity is integrated to obtain a new posture. The acceleration data is integrated based on the updated posture to obtain the true velocity information. The algorithm effectively combines the high-frequency stability of angular velocity measurement and the long-term stability of acceleration measurement, avoids angular velocity integral drift and high-frequency jitter of acceleration data, and improves the accuracy of posture and motion state estimation.

[0121] Reference below Figure 3 , which shows a structural diagram of a computer system 300 suitable for implementing an electronic device of an embodiment of the present application. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0122] like Figure 3 As shown, the computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage unit 308 into a random access memory (RAM) 303. Various programs and data required for the operation of the system 300 are also stored in the RAM 303. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0123] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output section 307 including devices such as a liquid crystal display (LCD) and speakers; a storage section 308 including devices such as a hard disk; and a communication section 309 including a network interface card such as a LAN card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 310 as needed, so that computer programs read therefrom can be installed into the storage section 308 as needed.

[0124] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, the above-mentioned functions defined in the method of the present application are executed. It should be noted that the computer-readable storage medium of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable storage medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0125] Computer program code for performing the operations of the present application can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0126] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0127] The modules described in the embodiments of the present application may be implemented by software or hardware.

[0128] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed by the electronic device, the electronic device is enabled to: collect data from the acceleration and angular velocity sensor in real time; obtain the vehicle's true motion speed, as well as the acceleration, angular velocity, and angle state using a filtering fusion algorithm; and determine vehicle events according to event thresholds of actual vehicle events, including sudden acceleration and deceleration, sudden braking, vehicle collision, vehicle fall, sharp turn, and rollover.

[0129] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A vehicle event measurement method, characterized in that: include: S1, real-time collection of data from the acceleration and angular velocity sensor; S2. Use the filter fusion algorithm to obtain the vehicle's true velocity, acceleration, angular velocity, and angle state, including: Construct the error between the expected gravity vector and the measured gravity vector to perform attitude estimation; Using a vector cross product to obtain an angle measurement error, using the measurement error to compensate for the angular velocity measurement value, and updating the attitude; Integrate the acceleration over time in the new posture to get the real speed of the vehicle; The method of constructing an error between an expected gravity vector and a measured gravity vector for attitude estimation specifically includes: The initial attitude is obtained through the accelerometer data and magnetometer data at rest; The initial posture is converted into quaternion form, and the desired gravity vector is obtained by rotating the standard gravity vector in the geographic coordinate system to the body coordinate system. ; In a state of rest or linear motion, the acceleration value measured by the accelerometer is the gravity vector ; Using the desired gravity vector Gravity vector Get the angular velocity of the attitude error ; S3. According to the event threshold of the actual vehicle event, the vehicle event is judged, including sudden acceleration and deceleration, sudden braking, vehicle collision, vehicle fall, sharp turn and rollover.

2. The vehicle event measurement method according to claim 1, characterized in that: The method of obtaining an angle measurement error by using a vector cross product, compensating an angular velocity measurement value by using the measurement error, and updating the attitude further comprises: Angular velocity measurements obtained from the gyroscope ; The angular velocity of the attitude error Add a certain proportion to the angular velocity measurement value to compensate for the error of the angular velocity measurement value: , where K represents the filter gain value; The compensated angular velocity measurement value Perform time integration to obtain a new posture.

3. The vehicle event measurement method according to claim 1, characterized in that: The time integration of the acceleration in the new posture further includes the following specific steps: Get the gravity vector under the new attitude , using the gravity vector Subtract the gravity vector at the new attitude , to obtain the true linear acceleration : The true linear acceleration Convert from the body coordinate system to the geographic coordinate system or inertial coordinate system; The transformed linear acceleration Perform time integration to obtain a new velocity estimate.

4. The vehicle event measurement method according to claim 1, characterized in that: The quaternion form is specifically expressed as follows: in, represents the real part of the quaternion, and Represent the three imaginary parts of the quaternion, represents the roll angle, represents the pitch angle, Indicates the yaw angle.

5. The vehicle event measurement method according to claim 2, characterized in that: The compensated angular velocity measurement value Perform time integration, where the quaternion differentiation method is used for time integration. The specific formula is as follows: in, Represents the derivative of the quaternion q with respect to time, represents the rotation rate of the vehicle, q represents the quaternion of the current rotation state, represents the angular velocity quaternion, Represents the quaternion multiplication symbol.

6. A vehicle event measurement method according to any one of claims 1 to 5, characterized in that: According to the obtained actual motion speed, acceleration, angular velocity and angle state, an event threshold for determining a vehicle event is obtained. The event threshold specifically includes: If the vehicle tilts more than 35 degrees, it is considered a rollover vehicle; If the vehicle's forward acceleration is ≥0.5g, it is considered rapid acceleration; The vehicle's forward acceleration is ≤-0.5g, which is considered a sudden deceleration; If the vehicle's forward acceleration is ≤ -1g, it is considered an emergency brake; If the vehicle's forward acceleration is ≤ -10g, it is considered a vehicle collision; If the vertical acceleration of the vehicle is ≤0.2g within 0.45 seconds, it is considered a fall event; The vehicle's turning angular velocity is ≥79 degrees per second and the vehicle's forward acceleration is greater than 20 km / , it is determined to be a sharp turn.

7. A computer program device, characterized in that A computer program is stored thereon, which implements the method according to any one of claims 1 to 6 when executed by a processor.

8. A computing system, characterized in that: The method comprises a processor and a memory, wherein the processor is configured to execute the method according to any one of claims 1 to 6.

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