Vehicle speed determination method and device, electronic equipment and storage medium

Abstract

The invention relates to a vehicle speed determination method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a first driving speed measured by a GPS module and first operation data measured by an IMU module in a vehicle driving process; the first operation data comprises the acceleration of the vehicle; under the condition that the GPS module is in a normal state, cross-correlation analysis is carried out on the wheel speed of the vehicle and the first running speed within preset time, and lag time of the GPS module is obtained; determining a first compensation speed of the IMU module in the lag time based on the lag time and the acceleration of the GPS module; a reference speed of the vehicle is determined based on the first driving speed and the first compensated speed. According to the invention, delay calibration is carried out on the first driving speed measured by the GPS module based on the compensation speed, so that the accuracy of the vehicle reference speed can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, and in particular to a vehicle speed determination method and device, an electronic device, and a storage medium. BACKGROUND

[0002] Vehicle speed is an important input of a vehicle control system (antilock braking system, drive slip control system, etc.), which can directly affect driving safety, energy efficiency optimization, and the accuracy of intelligent decision-making. The accuracy of vehicle speed estimation is related to the stability of vehicle control and affects vehicle driving safety.

[0003] At present, in the related art, vehicle speed can be estimated by wheel speed signals, inertial measurement unit (IMU) signals, etc., but this may result in low accuracy of vehicle speed estimation. SUMMARY

[0004] The present application provides a vehicle speed determination method and device, an electronic device, a vehicle, and a storage medium, which can improve the accuracy of vehicle speed estimation.

[0005] The present application provides a vehicle speed determination method, which comprises the following steps:

[0006] During vehicle driving, a first driving speed measured by a GPS module and first running data measured by an IMU module are obtained; the first running data comprises the acceleration of the vehicle;

[0007] In the case that the GPS module is in a normal state, cross-correlation analysis is performed on the wheel speed of the vehicle and the first driving speed within a preset time to obtain the lag time of the GPS module;

[0008] Based on the lag time of the GPS module and the acceleration, a first compensation speed of the IMU module within the lag time is determined;

[0009] Based on the first driving speed and the first compensation speed, a reference speed of the vehicle is determined.

[0010] According to the above technical means, considering that the traditional GPS signal has a delay and the IMU module may increase errors in long-time cumulative integration, in the case that the GPS module is in a normal state, the lag time of the GPS module can be determined, but the length of the lag time is short, so the compensation speed of the IMU module can be determined within a short lag time, that is, the error of the compensation speed is small. The first driving speed measured by the GPS module is calibrated based on the compensation speed, so that the accuracy of the reference speed estimation of the vehicle can be improved.

[0011] In some embodiments, the method further comprises: determining whether the first running data is valid data based on the acceleration in the case that the GPS module is in an abnormal state;

[0012] In the case that the first running data is invalid data, receiving second running data of the adjacent vehicles sent by the V2X module; wherein the second running data comprises second driving speeds of the adjacent vehicles;

[0013] Determining the reference speed of the vehicle based on the second driving speeds of the adjacent vehicles and the weight coefficients corresponding to the adjacent vehicles.

[0014] According to the above technical means, in the case that the GPS module is in an abnormal state and the first running data measured by the IMU is invalid data, the parallel fusion of multi-vehicle data can be completed within milliseconds by fusing the second driving speeds of the V2X roadside units and the adjacent vehicles, based on the second driving speeds of the adjacent vehicles and the weight coefficients corresponding to the adjacent vehicles, so as to improve the estimation accuracy and efficiency of the reference speed of the vehicle in complex traffic scenarios.

[0015] In some embodiments, the second running data further comprises positioning accuracy factors of the adjacent vehicles, and the method for determining the weight coefficients comprises:

[0016] For each adjacent vehicle, obtaining a communication distance between the adjacent vehicle and the vehicle;

[0017] Determining the weight coefficient corresponding to the adjacent vehicle based on the communication distance and the positioning accuracy factor of the adjacent vehicle.

[0018] According to the above technical means, based on the communication distance and the positioning accuracy factor of the adjacent vehicle, the weight coefficient corresponding to the adjacent vehicle can be determined, that is, the closer the communication distance, the higher the signal strength, and the larger the weight coefficient, so the weight coefficient can be dynamically changed to avoid the lag of the output reference speed caused by the fixed weight.

[0019] In some embodiments, the first running data further comprises an angular velocity of the vehicle, and the method further comprises:

[0020] In the case that the first running data is valid data, determining a change amount of an attitude angle of the vehicle based on the angular velocity;

[0021] Determining the reference speed of the vehicle based on the change amount of the attitude angle and the acceleration.

[0022] According to the above technical means, in the case that the first running data is valid data, the direction of the acceleration can be corrected by the attitude angle, so as to avoid the inertial measurement error caused by the tilting of the vehicle body, thereby improving the accuracy of the reference speed of the vehicle.

[0023] In some embodiments, the method further comprises:

[0024] When it is detected that the variance of the wheel speed is greater than a first preset threshold, determining a second compensation speed within the lag time based on the lag time and acceleration of the GPS module;

[0025] determining a third compensation speed within the lag time based on the lag time and the rate of change of the acceleration of the GPS module;

[0026] A reference speed of the vehicle is determined based on the first traveling speed, the second compensation speed, and the third compensation speed.

[0027] According to the above technical means, by integrating the multi-order dynamic compensation of the first driving speed with GPS lag, IMU acceleration and jerk (and the rate of change of speed), when the wheel speed is unreliable (such as when the variance exceeds the threshold due to slippage), the long-term stability of GPS and the short-term real-time performance of IMU are used to complement each other. Through first-order compensation (second compensation speed) and second-order compensation (third compensation speed), a low-latency, highly reliable reference speed is output, which effectively solves the problems of GPS signal delay and IMU integral error accumulation, thereby improving the accuracy of vehicle speed estimation.

[0028] In some embodiments, a method for determining whether a GPS module is in a normal state includes:

[0029] Get the number of satellites and positioning precision factor in the GPS module;

[0030] When the number of satellites is greater than the second preset threshold and the positioning precision factor is less than the third preset threshold, it is determined that the GPS module is in a normal state.

[0031] According to the above technical means, by real-time monitoring of the number of GPS satellites and the positioning precision factor, the validity of the GPS signal is dynamically determined, ensuring that GPS data is used under high-confidence conditions, thereby improving the reliability of vehicle speed estimation.

[0032] In some embodiments, the method further comprises:

[0033] determining a first time based on a reference speed and a first coefficient when it is detected that the rate of change of the acceleration is greater than a fourth preset threshold;

[0034] Within a first time, a reference speed corresponding to the acceleration is constrained within a preset safety interval; wherein the preset safety interval is determined based on an upper threshold and a lower threshold of the reference speed.

[0035] According to the above technical means, by monitoring the acceleration change rate in real time, in the case that the acceleration change rate is large, the first time (safety response time window) is dynamically calculated based on the current reference speed and the preset coefficient, and the speed is constrained in the preset safety interval within the time window, so that the speed estimation jump caused by sensor noise, delay or extreme driving behavior can be effectively inhibited.

[0036] The embodiment of the application provides a speed determination device of a vehicle, and the device comprises:

[0037] The acquisition unit is configured to acquire a first driving speed measured by a GPS module and first running data measured by an IMU module during driving of the vehicle, wherein the first running data comprises acceleration of the vehicle.

[0038] The cross-correlation analysis unit is configured to, in the case that the GPS module is in a normal state, perform cross-correlation analysis on the wheel speed and the first driving speed of the vehicle within a preset time to obtain a lag time of the GPS module.

[0039] The first determination unit is configured to determine a first compensation speed of the IMU module within the lag time based on the lag time of the GPS module and the acceleration.

[0040] The second determination unit is configured to determine a reference speed of the vehicle based on the first driving speed and the first compensation speed.

[0041] The embodiment of the application provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program capable of running on the processor, and the processor implements the steps in any one of the above methods when executing the computer program.

[0042] The embodiment of the application provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps in any one of the above methods when executed by a processor.

[0043] The embodiment of the application provides a computer program product, comprising a computer program or instructions, and the computer program or instructions implement the steps in any one of the above methods when executed by a processor.

[0044] The embodiment of the application provides a vehicle, comprising the above electronic device.

[0045] The embodiment of the application provides a vehicle, comprising the above electronic device.

[0046] (1) In the case that the GPS module is in a normal state, the hysteresis time of the GPS module can be determined, but the length of the hysteresis time is short, so the compensation speed of the IMU module can be determined in a short hysteresis time, that is, the error of the compensation speed is small, and the first driving speed measured by the GPS module is delayed and calibrated based on the compensation speed, so as to improve the accuracy of the vehicle reference speed estimation.

[0047] (2) The second driving speed of the V2X roadside unit and the adjacent vehicle can be fused, the second driving speed of each adjacent vehicle and the weight coefficient corresponding to each adjacent vehicle are based on, the parallel fusion of multi-vehicle data is completed within milliseconds, so as to improve the estimation accuracy and efficiency of the reference speed of the vehicle in a complex traffic scene.

[0048] (3) Based on the communication distance and the positioning accuracy factor of the adjacent vehicle, the weight coefficient corresponding to the adjacent vehicle can be determined, that is, the closer the communication distance, the higher the signal strength, the lower the data packet loss rate, and the larger the weight coefficient, so the weight coefficient can be dynamically changed, avoiding the lag of the output reference speed caused by the fixed weight.

[0049] (4) In the case that the first running data is valid data, the acceleration direction is corrected by the attitude angle, so as to avoid the inertial measurement error caused by the body tilt, thereby improving the accuracy of the reference speed of the vehicle.

[0050] (5) By fusing the first driving speed of the GPS hysteresis, the multi-order dynamic compensation of the IMU acceleration and the jerk (and the rate of change of speed), when the wheel speed is not reliable (such as slip caused by variance exceeding threshold), the long-term stability of GPS and the short-term real-time of IMU are complementary, through first-order compensation (second compensation speed) and second-order compensation (third compensation speed), the output of low delay and high reliable reference speed effectively solves the problem of GPS signal delay and IMU integral error accumulation, so as to improve the accuracy of vehicle speed estimation.

[0051] (6) By monitoring the number of GPS satellites and the positioning accuracy factor in real time, the effectiveness of the GPS signal is dynamically determined, and the GPS data is used only under high confidence condition, so as to improve the reliability of vehicle speed estimation.

[0052] (7) By monitoring the rate of change of acceleration in real time, in the case that the rate of change of acceleration is large, the first time (safety response time window) is dynamically calculated based on the current reference speed and the preset coefficient, and the speed is constrained in the preset safety interval within the time window, so as to effectively suppress the speed estimation jump caused by sensor noise, delay or extreme driving behavior. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1A flowchart of a speed determination method of a vehicle according to an embodiment of the present application Figure 1 ;

[0054] Figure 2 A flowchart of a speed determination method of a vehicle according to an embodiment of the present application Figure 2 ;

[0055] Figure 3 A flowchart of a speed determination method of a vehicle according to an embodiment of the present application Figure 3 ;

[0056] Figure 4 A working signal flow architecture diagram of a speed determination method of a vehicle according to an embodiment of the present application

[0057] Figure 5 A flowchart of a speed determination method of a vehicle according to an embodiment of the present application Figure 4 ;

[0058] Figure 6 A component structure diagram of a speed determination device of a vehicle according to an embodiment of the present application

[0059] Figure 7 A hardware entity diagram of an electronic device according to an embodiment of the present application DETAILED DESCRIPTION

[0060] Other advantages and effects of the present application can be easily understood by those skilled in the art from the above description of the preferred embodiments of the present application. The present application can be implemented or applied in other different specific embodiments, and the details in the specification can be modified or changed based on different views and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, and are not intended to limit the protection scope of the present application.

[0061] It should be noted that the diagrams provided in the following embodiments only schematically illustrate the basic concept of the present application, and only the components related to the present application are shown in the diagrams, not the number, shape and size of the components when actually implemented. The shape, number and ratio of the components when actually implemented can be arbitrarily changed, and the layout pattern of the components can be more complex.

[0062] In the following description, "some embodiments" are described, which describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0063] In the following description, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0064] In this embodiment, the term "and / or" is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, object A and / or object B may represent three situations: object A exists alone, object A and object B exist at the same time, and object B exists alone.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0066] Vehicle speed is a key input for vehicle control systems (such as anti-lock braking systems and drive anti-skid systems), directly impacting driving safety, energy efficiency optimization, and the accuracy of intelligent decision-making. Accurate speed estimation affects vehicle control stability and thus driving safety.

[0067] Currently, in related technologies, vehicle speed can be estimated by wheel speed signals, Global Positioning System (GPS), Inertial Measurement Unit (IMU) signals, etc.

[0068] However, the related technologies may have the following problems:

[0069] (1) Insufficient GPS signal delay and dynamic compensation. Delay error accumulation: Traditional GPS signals have an inherent delay of 0.5-2 seconds, which leads to significant speed estimation errors in high-speed scenarios (for example, at a speed of 120 km / h, the position error can reach 33-66 meters). Existing methods mostly use static time offset compensation and lack real-time prediction and high-order correction for dynamic delays.

[0070] (2) Sensor heterogeneity conflicts. Wheel speed sensors are prone to failure on low-adhesion roads, IMU integration has cumulative errors, GPS signals are lost in tunnels and other scenarios, and reliance on a single data source leads to insufficient all-weather robustness.

[0071] (3) Vehicle to Everything (V2X) collaborative data utilization is insufficient. The existing system does not effectively fuse the collaborative data of V2X roadside units (RSUs) and adjacent vehicles (OBU), especially in blind area or intersection scenarios, and lacks a dynamic credibility weight distribution mechanism.

[0072] (4) Real-time bottleneck of multi-vehicle collaboration. The solution in the related art is difficult to complete the parallel fusion of multi-vehicle data within milliseconds, resulting in a lag in updating the reference vehicle speed in complex traffic scenarios.

[0073] (5) Noise sensitivity and misjudgment of dynamic slope algorithm. The dynamic slope method in the related art is based on peak detection of wheel speed curve slope and is susceptible to noise interference (such as road bumps), resulting in misjudgment of the critical point of wheel lock or slip, especially in sudden acceleration and deceleration working conditions.

[0074] Based on this, the embodiments of the present application provide a vehicle speed determination method, the method comprising: during vehicle driving, acquiring a first driving speed measured by a GPS module and first running data measured by an IMU module; the first running data comprising the acceleration of the vehicle; in the case that the GPS module is in a normal state, cross-correlation analysis is performed on the wheel speed and the first driving speed of the vehicle within a preset time to obtain the lag time of the GPS module; based on the lag time of the GPS module and the acceleration, a first compensation speed of the IMU module within the lag time is determined; and based on the first driving speed and the first compensation speed, a reference speed of the vehicle is determined. In this way, considering that the traditional GPS signal has a delay and the IMU module may increase errors in long-time cumulative integration, in the case that the GPS module is in a normal state, the lag time of the GPS module can be determined. Since the length of the lag time is short, the compensation speed of the IMU module can be determined within a short lag time, that is, the error of the compensation speed is small. The first driving speed measured by the GPS module is calibrated based on the compensation speed, thereby improving the accuracy of the reference speed estimation of the vehicle.

[0075] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application.

[0076] Figure 1 A flowchart of a vehicle speed determination method provided by the embodiments of the present application Figure 1 As shown in Figure 1 , the method can be applied to the electronic control unit of the vehicle, comprising S101-S104, wherein:

[0077] S101, obtaining a first driving speed measured by a GPS module and first running data measured by an IMU module during driving of the vehicle.

[0078] The first running data can include acceleration and angular velocity of the vehicle.

[0079] It should be noted that the vehicle includes at least a multi-source data acquisition module, where the multi-source data acquisition module can include the GPS module and the IMU module.

[0080] For example, the GPS module can measure geographic coordinates of the vehicle and speed information of the vehicle, and the IMU module can measure three-axis linear acceleration and angular velocity of the vehicle.

[0081] In some embodiments, when it is determined that the vehicle is in a driving state, the electronic control unit can obtain the first driving speed measured by the GPS module and the first running data measured by the IMU module in real time, or the electronic control unit can periodically obtain the first driving speed measured by the GPS module and the first running data measured by the IMU module within a preset time period.

[0082] S102, when the GPS module is in a normal state, cross-correlation analysis is performed on wheel speed and the first driving speed of the vehicle within a preset time to obtain a lag time of the GPS module.

[0083] It should be noted that the multi-source data acquisition module can also include a wheel speed sensor, which can obtain independent rotation speed signals of four wheels of the vehicle and transmit the signals to the electronic control unit (also referred to as a processing unit) through a CAN bus.

[0084] In some embodiments, when the GPS module is in a normal state, cross-correlation analysis is performed on derivatives of the wheel speed and the first driving speed based on a cross-correlation function within a preset time, and a peak value of a cross-correlation function of the wheel speed derivative and the GPS speed derivative is calculated, so that the lag time of the GPS module can be determined.

[0085] It can be understood that the cross-correlation analysis is a method for analyzing similarity between two signals, and by calculating cross-correlation coefficients of the wheel speed derivative and the GPS speed derivative under different time delays, a time delay with the largest cross-correlation coefficient is found, which is the lag time of the GPS module.

[0086] For example, the cross-correlation function of the wheel speed derivative and the GPS speed derivative can be represented as:

[0087]

[0088] where R WGR (τ) represents the cross-correlation function of the wheel speed derivative and the GPS speed derivative, reflecting the similarity of the wheel speed derivative and the GPS speed derivative at different time delays τ; R (τ) represents the wheel speed derivative at time k, that is, the change rate of the wheel speed; R (τ) represents the GPS speed derivative at time k-τ, that is, the change rate of the GPS speed; N represents a preset time, that is, a sliding time window.

[0089] For example, the length of the sliding time window can be determined according to the product of the sampling frequency and the window time length, that is:

[0090] N=T ω ×f s (2)

[0091] wherein, T ω represents the window time length, which can be dynamically adjusted according to the vehicle speed, for example, shortened to 5 seconds at high speed and lengthened to 15 seconds at low speed; f s represents the data sampling rate of the sensor or system (unit: Hz), that is, the number of samples collected per second.

[0092] For example, the calculation of the peak value of the cross-correlation function of the wheel speed derivative and the GPS speed derivative can be represented as:

[0093] Δt=argmaxR WG (τ) (3)

[0094] It can be understood that by determining the time delay τ of the maximum value of the cross-correlation function, that is, the lag time of the GPS signal relative to the wheel speed signal.

[0095] Of course, the above formula (1), formula (2) and formula (3) can also be obtained by other formula transformations, which are not limited in the embodiments of the present application.

[0096] In some embodiments, the method for determining whether the GPS module is in a normal state can include the following steps:

[0097] S1021, acquiring the number of satellites and the positioning accuracy factor in the GPS module.

[0098] It should be noted that the data measured by the GPS module can include the number of satellites received by the GPS module and the positioning accuracy factor (Dilution of Precision, DOP) of the vehicle in addition to the first driving speed of the vehicle.

[0099] Here, the positioning accuracy factor can quantify the amplification degree of the positioning error caused by the satellite geometric distribution, and is a dimensionless value. Exemplarily, the positioning accuracy factor can include, but is not limited to, a horizontal accuracy factor, a position dilution of precision (PDOP), and a vertical accuracy factor.

[0100] Exemplarily, if the PDOP < 2, it indicates that the satellite distribution is excellent, and the positioning error is small; if 2≤PDOP≤4, it indicates an acceptable range, which is suitable for most scenarios; and if PDOP>6, it indicates that the satellite distribution is poor, and the positioning error is significantly increased.

[0101] Here, the number of satellites refers to the number of effective satellites that the GPS module can track in real time.

[0102] Exemplarily, if the number of satellites is ≥6, it indicates an ideal state, and redundant data can improve the anti-interference capability; if the number of satellites is 4-5, it indicates that the positioning can basically be completed, but the accuracy and robustness are low; and if the number of satellites is <4, it indicates that the positioning cannot be completed (only two-dimensional positioning or failure).

[0103] S1022, in a case where the number of satellites is greater than a second preset threshold and the positioning accuracy factor is less than a third preset threshold, it is determined that the GPS module is in a normal state.

[0104] In some embodiments, if the number of satellites is greater than the second preset threshold and the positioning accuracy factor is less than the third preset threshold, it can be determined that the GPS module is in a normal state; if the number of satellites is less than the second preset threshold or the positioning accuracy factor is greater than the third preset threshold, it can be determined that the GPS module is in an abnormal state.

[0105] It should be noted that the second preset threshold and the third preset threshold can be default values configured by the system, or can be set by the user according to the actual scene. For example, if the estimation accuracy of the vehicle speed is high, the second preset threshold can be set to 5 and the third preset threshold can be set to 2; if the estimation accuracy of the vehicle speed is moderate, the second preset threshold can be set to 4 and the third preset threshold can be set to 3.

[0106] In this way, by monitoring the number of GPS satellites and the positioning accuracy factor in real time, the effectiveness of the GPS signal is dynamically determined, and the GPS data is ensured to be used only under high confidence conditions, so that the reliability of the vehicle speed estimation can be improved, and low-quality GPS signals can be quickly identified and removed in complex environments such as urban canyons and tunnel exits, thereby ensuring the stability and safety of the multi-sensor fusion system.

[0107] S103, based on the lag time of the GPS module and the acceleration, a first compensation speed of the IMU module within the lag time is determined.

[0108] In some embodiments, the acceleration measured by the IMU module can be integrated within the lag time of the GPS module, so as to obtain a first compensation speed of the IMU module within the lag time.

[0109] It can be understood that the IMU module may accumulate errors due to long-time integration, resulting in inaccurate vehicle speed. The embodiments of the present application calculate the lag time of the GPS (which is relatively short), that is, the IMU is used for short-time compensation, and the acceleration measured by the IMU module is integrated within the lag time, so that the integration error will not accumulate too much.

[0110] Exemplarily, the calculation formula of the first compensation speed can be represented as:

[0111]

[0112] In S104, a reference speed of the vehicle is determined based on the first driving speed and the first compensation speed.

[0113] In some embodiments, the reference speed of the vehicle can be determined by calculating the sum of the first driving speed measured by the GPS module and the first compensation speed.

[0114] Exemplarily, the calculation formula of the reference speed of the vehicle can be represented as:

[0115]

[0116] wherein, V Ref represents the reference speed of the vehicle; V GPS (t-Δt) represents the first driving speed measured by the GPS module at t-Δt.

[0117] Of course, the above formula (4) and formula (5) can also be obtained by other formula transformation, which is not limited in the embodiments of the present application.

[0118] In the embodiments of the present application, considering that the traditional GPS signal has a delay and the IMU module may increase errors in long-time cumulative integration, in the case that the GPS module is in a normal state, the lag time of the GPS module can be determined. Since the length of the lag time is relatively short, the compensation speed of the IMU module can be determined within a short lag time, that is, the error of the compensation speed is small. The first driving speed measured by the GPS module is calibrated based on the compensation speed, so as to improve the accuracy of the estimation of the reference speed of the vehicle.

[0119] In some embodiments, Figure 2 The flowchart of a speed determination method of a vehicle provided by the embodiments of the present application is shown in FIG. 2. Figure 2 As shown in FIG. 2, the speed determination method of the vehicle provided by the embodiments of the present application includes the following steps: Figure 3As shown, the method can further include S201 to S203, wherein:

[0120] S201, in the case that the GPS module is in an abnormal state, determining whether the first running data is valid data based on acceleration.

[0121] Here, the acceleration can include lateral acceleration and longitudinal acceleration.

[0122] Wherein, the lateral acceleration refers to the acceleration perpendicular to the direction of motion, for example, the acceleration caused by centrifugal force when the vehicle turns; the longitudinal acceleration refers to the acceleration along the direction of motion of the object, for example, the acceleration when the vehicle accelerates or brakes.

[0123] In some embodiments, the method of determining whether the first running data is valid data can include the following steps:

[0124] In the case that the lateral acceleration is less than or equal to a fifth preset threshold value, and the longitudinal acceleration is less than or equal to a sixth preset threshold value, the first running data is determined to be valid data;

[0125] In the case that the lateral acceleration is greater than the fifth preset threshold value, or the longitudinal acceleration is greater than the sixth preset threshold value, the first running data is determined to be invalid data.

[0126] It should be noted that the fifth threshold value can be set to 0.3g (g is the acceleration of gravity), and the sixth preset threshold value can be set to 0.5g, which can be preconfigured by the system or customized by the user according to the actual scene, and the present application does not limit this.

[0127] S202, in the case that the first running data is invalid data, receiving second running data of adjacent vehicles sent by the V2X module.

[0128] Wherein, the second running data includes the second driving speed of each adjacent vehicle and the positioning accuracy factor of each adjacent vehicle.

[0129] It should be noted that the second running data can be the running data of the adjacent vehicles sent by the V2X module, or the running data broadcast by the roadside unit; or the cooperative running data combined with the running data of the adjacent vehicles and the running data broadcast by the roadside unit.

[0130] S203, determining the reference speed of the vehicle based on the second driving speed of each adjacent vehicle and the corresponding weight coefficient of each adjacent vehicle.

[0131] In some embodiments, in the case that the GPS module is abnormal and the first running data measured by the IMU is invalid, the electronic control unit of the vehicle can receive the second driving speed of each adjacent vehicle and the positioning accuracy factor of each adjacent vehicle, and fuse the second driving speed of one or more adjacent vehicles based on the corresponding weight coefficient of each adjacent vehicle and the second driving speed of each adjacent vehicle using a weighted average method.

[0132] Exemplarily, the calculation formula of the reference vehicle speed of the vehicle can be represented as:

[0133]

[0134] wherein, V Ref represents the reference vehicle speed fused based on the second driving speed of n adjacent vehicles; represents the second driving speed of the i-th adjacent vehicle; ω i represents the weight coefficient of the i-th adjacent vehicle.

[0135] In the embodiments of the present application, in the case that the GPS module is in an abnormal state and the first running data measured by the IMU is invalid data, the parallel fusion of multi-vehicle data can be completed within milliseconds based on the second driving speed of each adjacent vehicle and the corresponding weight coefficient of each adjacent vehicle by fusing the second driving speed of the V2X roadside unit and the adjacent vehicle, so as to improve the estimation accuracy and efficiency of the reference speed of the vehicle in a complex traffic scene.

[0136] In a possible implementation, the method for determining the weight coefficient can include the following steps:

[0137] S2031, for each adjacent vehicle, obtaining the communication distance between the adjacent vehicle and the vehicle;

[0138] S2032, determining the corresponding weight coefficient of the adjacent vehicle based on the communication distance and the positioning accuracy factor of the adjacent vehicle.

[0139] In some embodiments, for the weight coefficient of each adjacent vehicle, the electronic control unit of the vehicle can receive the communication distance between the adjacent vehicle and the current target vehicle sent by the V2X module, and determine the weight coefficient of the adjacent vehicle based on the product of the square of the communication distance and the positioning accuracy factor of the adjacent vehicle.

[0140] Exemplarily, the calculation formula of the weight coefficient of the i-th adjacent vehicle can be represented as:

[0141]

[0142] wherein, d i represents the communication distance between the i-th adjacent vehicle and the target vehicle, PDOP ia positioning accuracy factor of the ith neighboring vehicle.

[0143] Of course, the above formula (6) and formula (7) can also be obtained by other formula transformation, which is not limited in the embodiments of the present application.

[0144] In the embodiments of the present application, based on the communication distance and the positioning accuracy factor of the neighboring vehicle, the weight coefficient corresponding to the neighboring vehicle can be determined, that is, the closer the communication distance, the higher the signal strength, the lower the data packet loss rate, and the larger the weight coefficient, so the weight coefficient can be dynamically changed to avoid the lag of the output reference speed caused by the fixed weight.

[0145] In another possible implementation, the method for determining the weight coefficient can further include the following steps:

[0146] Obtaining the signal-to-noise ratio of each neighboring vehicle; determining the communication quality weight coefficient of each neighboring vehicle based on the signal-to-noise ratio of each neighboring vehicle and the total signal-to-noise ratio; determining the penalty coefficient based on the second driving speed of each neighboring vehicle, the driving speed of the current target vehicle and the second coefficient; determining the weight coefficient based on the communication quality weight coefficient of each neighboring vehicle and the penalty coefficient.

[0147] In some embodiments, the signal-to-noise ratio of each neighboring vehicle can reflect the quality (i.e. reliability) of the communication link; for example, if the signal-to-noise ratio is high, it means that the signal is clear and less affected by noise; if the signal-to-noise ratio is low, it means that the signal may be affected by noise.

[0148] In some embodiments, the communication quality weight coefficient of each neighboring vehicle can be determined according to the ratio of the signal-to-noise ratio of each neighboring vehicle and the total signal-to-noise ratio.

[0149] For example, the communication quality weight coefficient of each neighboring vehicle can be expressed as:

[0150]

[0151] wherein SN i represents the signal-to-noise ratio of the ith neighboring vehicle; and ∑SNR represents the sum of the signal-to-noise ratios of all neighboring vehicles.

[0152] In some embodiments, the driving speed of the target vehicle can be measured by a vehicle-mounted sensor; the speed difference between the driving speed of the current target vehicle and the second driving speed of each neighboring vehicle is calculated, and the ratio of the square of the speed difference and the second coefficient is negatively exponentially weighted to obtain the penalty coefficient.

[0153] For example, the calculation formula of the penalty coefficient can be expressed as:

[0154]

[0155] wherein V ego represents a current driving speed of the target vehicle; represents a second driving speed of the ith neighboring vehicle; 2σ 2 is a second coefficient, and σ represents a speed difference tolerance threshold, which is used to measure an acceptable degree of difference between the speed of the target vehicle and the speed of the neighboring vehicle, and an example value of σ can be 5 kilometers per hour; J i represents a penalty coefficient of the ith neighboring vehicle.

[0156] In some embodiments, the weight coefficient of the ith neighboring vehicle can be determined according to a product of a communication quality weight coefficient of the ith neighboring vehicle and a penalty coefficient of the ith neighboring vehicle.

[0157] An example calculation formula of the weight coefficient of the ith neighboring vehicle can be represented as:

[0158] ω i = S i · J i (10)

[0159] Of course, the above formula (8), formula (9) and formula (10) can also be obtained by other formula transformations, which are not limited in the embodiments of the present application.

[0160] In some embodiments, in a case where the first running data is valid data, the attitude angle change amount of the vehicle can be determined based on the angular velocity; and the reference speed of the vehicle can be determined based on the attitude angle change amount and the acceleration.

[0161] It should be noted that during the running of the vehicle, the IMU module can continuously collect the first running data, but not all collected data can accurately reflect the real state of the vehicle, and there can be cases of data abnormalities caused by sensor failure, external interference, etc. Therefore, the validity of the first running data can be judged, and only when the first running data is determined to be valid data, the subsequent vehicle attitude and speed information obtained based on these running data can be ensured to be consistent with the real running condition of the vehicle.

[0162] It can be understood that in a case where the first running data is valid data, the electronic control unit can obtain the angular velocity of the vehicle, and integrate the angular velocity, that is, accumulate the change of the angular velocity with time, so as to obtain the rotation angle of the vehicle around each axis in the corresponding time period, that is, the attitude angle change amount. For example, when the vehicle is turning, there will be an angular velocity around the vertical axis, and integrating the angular velocity can obtain the angle change of the vehicle turning, so as to determine the change of the vehicle attitude in the horizontal direction.

[0163] After determining the change of the attitude angle of the vehicle, in combination with the acceleration data measured by the IMU module, the reference speed of the vehicle can be further determined, that is, the direction of the acceleration can be corrected by the change of the attitude angle of the vehicle, because the actual direction of the acceleration may deviate from the direction measured by the sensor due to the different attitudes of the vehicle. Further, the electronic control unit can perform integral operation on the corrected acceleration, so as to obtain the reference speed of the vehicle.

[0164] In the embodiments of the present application, when the first running data is valid data, the direction of the acceleration is corrected by the attitude angle, so that the inertial measurement error caused by the tilting of the vehicle body can be avoided, and thus the accuracy of the reference speed of the vehicle can be improved.

[0165] In some embodiments, Figure 3 A flowchart of a speed determination method of a vehicle provided in the embodiments of the present application is shown in Figure 4 As shown in Figure 4 The above method can further include the following steps:

[0166] S301, in a case where the variance of the wheel speed is greater than a first preset threshold, determining a second compensation speed in the lag time based on the lag time of the GPS module and the acceleration.

[0167] It can be understood that if the variance of the wheel speed is greater than the first preset threshold, it indicates that the vehicle may be on an icy road at this time, or the wheels are in a slipping state, that is, the vehicle speed measured by the wheel sensor is unreliable.

[0168] In some embodiments, the second compensation speed (which can also be referred to as a first-order compensation term) can be determined according to the product of the lag time of the GPS module and the acceleration measured by the IMU module.

[0169] It should be noted that the second compensation speed can compensate for the linear deviation of the speed caused by the constant acceleration during the GPS lag.

[0170] Exemplarily, the second compensation speed can be expressed as:

[0171] V2=α IMU ·Δt (11)

[0172] S302, determining a third compensation speed in the lag time based on the lag time of the GPS module and the change rate of the acceleration.

[0173] In some embodiments, the third compensation speed (which can also be referred to as a second-order compensation term) can be determined according to the product between the square of the lag time of the GPS module and the third coefficient and the change rate of the acceleration.

[0174] It should be noted that the third compensation speed can compensate for the deviation of the speed curve caused by the non-linear change of acceleration (such as emergency braking or sudden acceleration).

[0175] Exemplarily, the third compensation speed can be represented as:

[0176] V3=c·Jerk·Δt 2 (12)

[0177] Wherein, c can represent a third coefficient, for example, the third coefficient can be 0.5; V3 represents the third compensation speed.

[0178] S303, based on the first driving speed, the second compensation speed and the third compensation speed, determining the reference speed of the vehicle.

[0179] In some embodiments, the reference speed of the vehicle can be determined by calculating the sum of the first driving speed, the second compensation speed and the third compensation speed of the vehicle.

[0180] Exemplarily, the calculation formula of the reference speed of the vehicle can be represented as:

[0181] V Ref =V GPS (t-Δt)+V2+V3 (13)

[0182] Of course, the above formula (11), formula (12) and formula (13) can also be obtained by other formula transformation, which is not limited in the embodiment of the application.

[0183] In the embodiment of the application, by fusing the first driving speed of the GPS lag, the IMU acceleration and the jerk (and the rate of change of speed), the multi-order dynamic compensation is used when the wheel speed signal is unreliable (such as slip caused by variance exceeding threshold), the long-term stability of GPS and the short-term real-time of IMU are complementary, the first-order compensation (second compensation speed) and second-order compensation (third compensation speed) are used, the low-delay and high-reliable reference speed is output, the GPS signal delay and IMU integral error accumulation are effectively solved, and the accuracy of vehicle speed estimation is improved.

[0184] In some embodiments, the above method further comprises the following steps:

[0185] In the case where the rate of change of acceleration is greater than the fourth preset threshold, the first time is determined based on the reference speed and the first coefficient, and the reference speed corresponding to the acceleration is constrained in the preset safety interval within the first time.

[0186] Here, the rate of change of acceleration (also referred to as jerk) refers to the derivative of the acceleration measured by the IMU module, which is used to indicate the rate of change of acceleration.

[0187] Exemplarily, the rate of change of acceleration can be expressed as:

[0188]

[0189] In some embodiments, the first time can be determined based on the product of the reference speed of the vehicle and the first coefficient.

[0190] wherein the first time refers to the locking time of the reference speed of the vehicle, that is, within the current locking time, the reference speed of the vehicle changes within a certain preset range.

[0191] Exemplarily, the calculation formula of the first time can be expressed as:

[0192]

[0193] wherein a / b represents the first coefficient; Exemplarily, the value of a in the first coefficient can be 0.5 or 0.6, and the value of b in the first coefficient can be 100 or 110; Of course, the values of a and b can also be other values, for example, when driving at high speed, the vehicle state changes more drastically, and a longer time is needed to stabilize, so the first coefficient can be set larger; While driving at low speed, the first coefficient can be smaller, which is not limited in the embodiments of the present application.

[0194] Of course, the above formula (14) and formula (15) can also be obtained by other formula deformation, which is not limited in the embodiments of the present application.

[0195] It can be understood that the preset safety interval can be determined based on the upper threshold and the lower threshold of the reference speed, that is, the preset safety interval is set based on the safety operation requirement of the vehicle, and the upper threshold and the lower threshold can limit the maximum and minimum values of the reference speed, respectively.

[0196] In some embodiments, in order to avoid system misjudgment or loss of control due to abnormal acceleration, the reference speed corresponding to the acceleration is constrained within the preset safety interval within the first time. For example, when emergency braking, although the actual speed of the vehicle may be rapidly decreasing, in order to prevent the system from producing misoperation due to the speed decreasing too fast, the reference speed is limited within a safe range to ensure the stable operation of the vehicle and the safety of the vehicle and personnel.

[0197] Exemplarily, it is assumed that the vehicle is normally driving on the highway at a speed of 80km / h, at this time the acceleration sensor is suddenly interfered by the electromagnetic interference of the nearby high-voltage line, and a noise signal is generated. The noise signal causes the acceleration measurement value to jump from 0m / s 2 to 5m / s 2. Within the 0.1 seconds, the Jerk value exceeds the fourth preset threshold set by the system. In order to avoid the reference speed of the vehicle being calculated incorrectly due to noise interference and changing too fast, the system determines a first time of 2 seconds according to the current reference speed (80 km / h) and a first coefficient. Within the 2 seconds, the system restricts the reference speed to a safe interval of 70-90 km / h. Even if the noise causes an abnormal jump in acceleration, the reference speed will not exceed the safe interval due to noise interference, thereby ensuring the stable operation of other control systems of the vehicle, such as the automatic cruise control system, which will not make incorrect acceleration or deceleration decisions due to false changes in speed.

[0198] Another example is that when the vehicle is suddenly braked during driving, the acceleration decreases rapidly, and the Jerk value is greater than the fourth preset threshold. The system determines a first time of 4 seconds according to the current reference speed (such as 80 m / h) and a first coefficient (such as 0.05). Within the 4 seconds, the system restricts the reference speed corresponding to the acceleration to a preset safe interval (such as 40-60 km / h). Even if the actual speed of the vehicle decreases rapidly during the sudden braking, the reference speed will be adjusted within this interval to avoid misjudgment or loss of control of the system due to abnormal speed.

[0199] In the embodiments of the present application, by monitoring the acceleration change rate in real time, when the acceleration change rate is detected to be large, a first time (a safe response time window) is dynamically calculated based on the current reference speed and a preset coefficient, and the speed is restricted within a preset safe interval within the time window, so that the speed estimation jump caused by sensor noise, delay or extreme driving behavior can be effectively suppressed.

[0200] The following describes the application of the vehicle speed determination method provided by the embodiments of the present application in actual scenarios.

[0201] The embodiments of the present application relate to the cross field of intelligent transportation and vehicle dynamics control, and specifically relate to a vehicle reference speed real-time correction method and system based on GPS signal delay compensation, V2X cooperative communication and multi-sensor fusion, which is used to solve the problem of reference speed jump caused by traditional GPS positioning lag and multi-source data conflict in complex working conditions, so as to improve the control stability of the automatic driving system in emergency braking, turning on a curve and other scenarios.

[0202] In some embodiments, Abnormal code A working signal flow architecture diagram of a vehicle speed determination method provided by the embodiments of the present application is shown in FIG. 4. Trigger condition As shown in FIG. 4, the architecture in the embodiments of the present application can include a perception module 401, a preprocessing module 402, a core processing module 403 and an output module 404.

[0203] In some embodiments, the perception module 401 can include a GPS unit 4011, a six-axis inertial measurement unit 4012, a wheel speed sensor unit 4013, and a V2X communication unit 4014. Exemplarily, the dual-frequency GPS unit 4011 can provide timestamp, geographic coordinates, and speed information, support real-time dynamic positioning technology, and minimize multipath error. The six-axis inertial measurement unit 4012 can measure three-axis linear acceleration and angular velocity for vehicle body attitude solution and dynamic integral prediction. The wheel speed sensor unit 4013 can capture four-wheel independent rotation speed signals, which are transmitted to the processing unit via CAN bus. The V2X communication unit 4014 can receive cooperative positioning data broadcast by adjacent vehicles (OBU) and roadside units (RSU), including speed, positioning accuracy factor.

[0204] In some embodiments, the preprocessing module 402 can include a GPS data preprocessing unit 4021, an IMU data preprocessing unit 4022, a wheel speed data preprocessing unit 4023, and a V2X data preprocessing unit 4024. Exemplarily, the GPS data preprocessing unit 4021 includes GPS validity check, for example, based on the number of satellites (≥4) and positioning accuracy factor (PDOP <3) to determine data validity. The IMU data preprocessing unit 4022 can include IMU drift compensation, which corrects acceleration zero point offset using a temperature-drift fitting model, and realizes real-time conversion of vehicle body coordinate system to global coordinate system through quaternion algorithm. The wheel speed data preprocessing unit 4023 can use median filtering to eliminate transient pulse noise, and identify abnormal wheel speed through variance detection.

[0205] In some embodiments, the core processing module 403 includes a GPS delay dynamic prediction unit 4031, a V2X cooperative fusion unit 4032, and a dynamic slope unit 4033. Exemplarily, the GPS delay dynamic prediction unit 403 can calculate signal lag time Δt based on cross-correlation analysis of wheel speed derivative and GPS speed derivative within a sliding time window (10 seconds), and compensate for displacement error. The V2X cooperative fusion unit 4032 constructs a dynamic weight model to fuse multi-vehicle cooperative speed data. The dynamic slope unit 4033 can introduce an acceleration derivative (Jerk) threshold judgment mechanism. If the actual Jerk is detected to be greater than the threshold, the real event and noise interference are distinguished, and the current convex point is locked and the slope protection mechanism is started, the robustness of wheel speed slope analysis is optimized, and subsequent noise interference is rejected.

[0206] In some embodiments, the output module 404 can output one or more of the following: a reference vehicle speed generation unit 4041, an abnormal state code unit 4042, and a control instruction unit 4043.

[0207] In other words, the vehicle's electronic control unit can first output an abnormal status code, determine the calculation method of the vehicle's reference speed based on the abnormal status code, and then output a high-precision vehicle speed estimate (that is, the vehicle's reference speed), and simultaneously provide a control command interface to support real-time decision-making of chassis systems such as the anti-lock braking system / traction control system / vehicle dynamic control system.

[0208] For example, Table 1 shows the exception codes and corresponding processing strategies for different exception codes provided in an embodiment of the present application. As shown in Table 1, if the exception code is 0x01, it indicates that the GPS failure lasts for more than 30 seconds, and the corresponding processing strategy is to switch to the IMU / V2X prediction mode; if the exception code is 0x02, it indicates a V2X data conflict, and the corresponding processing strategy is to eliminate outlier data and request retransmission; if the exception code is 0x03, it indicates that a single wheel speed signal is lost for more than 5 seconds, and the corresponding processing strategy is to use the average of the remaining wheel speeds as a substitute; if the exception code is 0x04, it indicates that the IMU temperature drift exceeds the limit, and the corresponding processing strategy is to disable attitude angle integration and reduce the sampling rate.

[0209] Table 1

[0210] Processing strategy GPS failure lasts more than 30 seconds Switch to IMU / V2X prediction mode 0x01 V2X data conflict Reject outlier data and request retransmission 0x02 Single wheel speed signal loss greater than 5 seconds Use the remaining wheel speed mean instead 0x03 IMU temperature drift exceeds limit Disable attitude angle integration, reduce sampling rate 0x04 Figure 5 Figure 4

[0211] In some embodiments, Figure 5 A flow chart of a method for determining vehicle speed provided in an embodiment of the present application Figure 6 ;like Figure 6 As shown, the flowchart in the embodiment of the present application may include the following steps.

[0212] S501, starting the vehicle;

[0213] S502, determine whether the GPS signal is valid, if the GPS signal is valid, execute S503, otherwise execute S507;

[0214] S503, enter GPS calibration mode;

[0215] S504, calculating the lag time based on the cross-correlation function; illustratively, a GPS signal delay prediction model may be constructed through a wheel speed-acceleration joint analysis to calculate the GPS lag time Δt in real time;

[0216] S505, fusing IMU data; illustratively, obtaining a first compensation velocity based on the lag time and the acceleration measured by the IMU;

[0217] S506, outputting a reference speed; illustratively, determining a reference speed of the vehicle based on a first driving speed measured by GPS and a first compensation speed;

[0218] S507, enter prediction mode;

[0219] S508, determining whether the IMU data is valid. If the IMU data is valid, executing S509; otherwise, executing S510;

[0220] S509, IMU integration prediction; illustratively, integrating the acceleration and angular velocity measured by the IMU module to obtain a reference velocity of the vehicle;

[0221] S510, determine whether the V2X data is valid data; if it is valid data, execute S511; otherwise, execute S512;

[0222] S511, performing a fusion process based on the second driving speeds of each adjacent vehicle and the weight coefficient corresponding to each adjacent vehicle to determine a reference speed of the vehicle;

[0223] S512, enter the fail-safe mode; illustratively, if the fail-safe mode is entered, a preset reference vehicle speed may be output and a fixed deceleration rate control (0.3g) may be triggered.

[0224] It should be noted that the preset reference vehicle speed can be a fixed value set by the system, or it can be set by the user according to the actual scenario.

[0225] For example, if a vehicle is traveling in an urban tunnel and the GPS signal is lost, it relies on IMU integration and V2X coordination. After entering the tunnel, the GPS module mark is invalid (i.e., the exception code is 0x01), and the system switches to prediction mode; the IMU compensates for the slope effect (θ = 3°) and continuously outputs the reference speed. If the IMU data is detected to be invalid, the V2X data of the vehicle in front (SNR>25dB, d<50m) is connected after 10 seconds, and the reference speed is generated by weighted fusion; further, if the vehicle in front is detected to be decelerating rapidly (jerk = -18m / s^3), the slope protection window is triggered and the braking system is pre-pressurized.

[0226] As another example, if the vehicle is traveling on a low-adhesion road and the wheel speed sensor fails, the wheel speed variance exceeds the limit, triggering the 0x03 exception code. The wheel speed weight is reduced to 10%, and the reference speed is generated using the above formula (13) or V2X data. The dynamic slope method detects a wheel locking trend (sudden slope change), triggering the anti-lock braking system to intervene.

[0227] In this embodiment, GPS delay compensation accuracy can be improved to ±0.1 seconds (compared to ±0.5 seconds in related technologies), with a speed error of less than 0.2 km / h. In V2X collaborative mode, the speed estimation error in tunnels is reduced to 1.5 km / h (compared to the traditional IMU integration error of more than 5 km / h).

[0228] Based on the above embodiment, the present application also provides a vehicle speed determination device. Figure 7A schematic diagram of the structure of a vehicle speed determination device provided in an embodiment of the present application is shown in FIG. Figure 7 As shown, the vehicle speed determination device 600 includes an acquisition unit 601, a cross-correlation analysis unit 602, a first determination unit 603, and a second determination unit 604, wherein:

[0229] An acquisition unit 601 is configured to acquire, during a vehicle driving process, a first driving speed measured by a GPS module and first operating data measured by an IMU module; the first operating data includes an acceleration of the vehicle;

[0230] The cross-correlation analysis unit 602 is configured to perform a cross-correlation analysis on the wheel speed of the vehicle and the first driving speed within a preset time when the GPS module is in a normal state, so as to obtain a lag time of the GPS module;

[0231] A first determining unit 603 is configured to determine a first compensation velocity of the IMU module within the lag time based on the lag time and acceleration of the GPS module;

[0232] The second determining unit 604 is configured to determine a reference speed of the vehicle based on the first driving speed and the first compensation speed.

[0233] In some embodiments of the present application, the speed determination device 600 further includes: a third determination unit, a receiving unit, and a fourth determination unit, wherein:

[0234] a third determining unit, configured to determine whether the first operating data is valid data based on the acceleration when the GPS module is in an abnormal state;

[0235] a receiving unit, configured to receive, when the first operating data is invalid data, second operating data of neighboring vehicles sent by the V2X module; wherein the second operating data includes a second driving speed of each neighboring vehicle;

[0236] The fourth determining unit is configured to determine a reference speed of the vehicle based on the second driving speeds of the adjacent vehicles and the weight coefficients corresponding to the adjacent vehicles.

[0237] In some embodiments of the present application, the second operating data also includes the positioning accuracy factor of each neighboring vehicle, and the fourth determination unit is further used to obtain the communication distance between the neighboring vehicle and the vehicle for each neighboring vehicle; based on the communication distance and the positioning accuracy factor of the neighboring vehicle, determine the weight coefficient corresponding to the neighboring vehicle.

[0238] In some embodiments of the present application, the first operating data further includes an angular velocity of the vehicle; the speed determination device 600 further includes: a fifth determination unit and a sixth determination unit, wherein:

[0239] The fifth determining unit is configured to determine a change amount of the attitude angle of the vehicle based on the angular velocity when the first running data is valid data.

[0240] The sixth determining unit is configured to determine a reference speed of the vehicle based on the change amount of the attitude angle and the acceleration.

[0241] In some embodiments of the present application, the speed determining device 600 further comprises a seventh determining unit, an eighth determining unit and a ninth determining unit, wherein:

[0242] The seventh determining unit is configured to determine a second compensation speed within a lag time of the GPS module based on the lag time and the acceleration when the variance of the wheel speed is greater than a first preset threshold.

[0243] The eighth determining unit is configured to determine a third compensation speed within the lag time of the GPS module based on the lag time and a change rate of the acceleration.

[0244] The ninth determining unit is configured to determine the reference speed of the vehicle based on the first running speed, the second compensation speed and the third compensation speed.

[0245] In some embodiments of the present application, the cross-correlation analysis unit 602 is further configured to obtain a number of satellites in the GPS module and a positioning accuracy factor; and determine that the GPS module is in a normal state when the number of satellites is greater than a second preset threshold and the positioning accuracy factor is less than a third preset threshold.

[0246] In some embodiments of the present application, the speed determining device 600 further comprises a tenth determining unit and a constraint unit, wherein:

[0247] The tenth determining unit is configured to determine a first time based on the reference speed and a first coefficient when the change rate of the acceleration is greater than a fourth preset threshold.

[0248] The constraint unit is configured to constrain the reference speed corresponding to the acceleration within a preset safety interval within the first time; wherein the preset safety interval is determined based on an upper threshold and a lower threshold of the reference speed.

[0249] It should be noted that, in the embodiments of the present application, if the above method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application can be embodied in the form of a software product in essence or the part that contributes to the related art, which is stored in a storage medium, includes a number of instructions to make an electronic device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, and various media that can store program codes. Thus, the embodiments of the present application are not limited to any specific hardware and software combination.

[0250] The present application also provides an electronic device, including a memory and a processor, the memory stores a computer program capable of running on the processor, and the processor implements the above method when executing the computer program.

[0251] The present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above method. The computer readable storage medium can be transitory or non-transitory.

[0252] The present application also provides a computer program product, which includes a computer program or instructions, and the computer program or instructions are executed by a processor to implement part or all steps of the above method. The computer program product can be specifically implemented by hardware, software or a combination thereof. The computer program product can be specifically implemented by hardware, software or a combination thereof.

[0253] In an optional embodiment, the computer program product is specifically embodied as a computer storage medium, and in another optional embodiment, the computer program product is specifically embodied as a software product, such as a software development kit (SDK) and the like.

[0254] It should be noted that, ​ A hardware entity schematic diagram of an electronic device provided by the embodiments of the present application is shown in FIG. 7, which includes a processor 701, a communication interface 702 and a memory 703. ​

[0255] The processor 701 usually controls the overall operation of the electronic device 700.

[0256] The communication interface 702 can enable the electronic device 700 to communicate with other terminals or servers through a network.

[0257] ​The memory 703 is configured to store instructions and applications executable by the processor 701, and can also cache data (for example, image data, audio data, voice communication data, and video communication data) to be processed by the processor 701 and modules in the electronic device 700, and can be implemented by FLASH or RAM. The processor 701, the communication interface 702, and the memory 703 can perform data transmission through the bus 704.

[0258] Here, the electronic device can be a car machine in a vehicle.

[0259] It should be noted that the above description of the storage medium and device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of the present application, please refer to the description of the method embodiments of the present application.

[0260] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of each step / process does not mean the order of execution, and the execution order of each step / process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above sequence number of the embodiments of the present application is only for description, not representing the advantages and disadvantages of the embodiments.

[0261] It should be noted that in this paper, the term "include", "contain" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0262] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other manners. The above described device embodiments are merely schematic. For example, the division of the units is only a logical function division. There can be another division manner for the actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the above components can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or in other forms.

[0263] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units; they can be located in one place, or distributed on multiple network units; and part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0264] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be realized in the form of hardware, or in the form of hardware plus software functional units.

[0265] Those of ordinary skill in the art can understand that all or part of the steps of the above method embodiments can be completed by a program instructing related hardware, and the foregoing program can be stored in a computer readable storage medium, and when the program is executed, the steps of the method embodiments are executed; and the foregoing storage medium includes mobile storage devices, read-only memories, magnetic disks or optical disks, and various media that can store program codes.

[0266] Alternatively, when the integrated units of the present application are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the embodiments of the methods of the present application. The foregoing storage medium includes: mobile storage devices, ROM, magnetic disks or optical disks, and various media that can store program codes.

[0267] The above merely provides the implementation of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of the change or replacement within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. A method for determining the speed of a vehicle, characterized in that: The method comprises: During the vehicle's travel, obtaining a first travel speed measured by a GPS module and first operating data measured by an IMU module; the first operating data includes an acceleration of the vehicle; When the GPS module is in a normal state, performing a cross-correlation analysis on the wheel speed of the vehicle and the first driving speed within a preset time to obtain a lag time of the GPS module; Determining a first compensation velocity of the IMU module within the lag time based on the lag time of the GPS module and the acceleration; A reference speed of the vehicle is determined based on the first traveling speed and the first compensation speed.

2. The method according to claim 1, characterized in that The method further comprises: When the GPS module is in an abnormal state, determining whether the first operating data is valid data based on the acceleration; When the first operating data is invalid data, receiving second operating data of neighboring vehicles sent by the V2X module; wherein the second operating data includes a second driving speed of each of the neighboring vehicles; A reference speed of the vehicle is determined based on the second driving speeds of the adjacent vehicles and the weight coefficients corresponding to the adjacent vehicles.

3. The method according to claim 2, characterized in that The second operating data also includes a positioning precision factor of each of the adjacent vehicles. The method for determining the weight coefficient includes: For each adjacent vehicle, obtaining a communication distance between the adjacent vehicle and the vehicle; A weight coefficient corresponding to the neighboring vehicle is determined based on the communication distance and the positioning precision factor of the neighboring vehicle.

4. The method according to claim 2, characterized in that The first operating data further includes an angular velocity of the vehicle; and the method further includes: determining an attitude angle change of the vehicle based on the angular velocity when the first operating data is valid data; A reference speed of the vehicle is determined based on the attitude angle change and the acceleration.

5. The method according to claim 1, wherein The method further comprises: When it is detected that the variance of the wheel speed is greater than a first preset threshold, determining a second compensation speed within the lag time based on the lag time of the GPS module and the acceleration; determining a third compensation speed within the lag time based on a lag time of the GPS module and a rate of change of the acceleration; A reference speed of the vehicle is determined based on the first traveling speed, the second compensation speed, and the third compensation speed.

6. The method according to claim 1, characterized in that The method further comprises: Obtain the number of satellites and positioning precision factor in the GPS module; When the number of satellites is greater than a second preset threshold and the positioning precision factor is less than a third preset threshold, it is determined that the GPS module is in a normal state.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: determining a first time based on the reference speed and a first coefficient when it is detected that the rate of change of the acceleration is greater than a fourth preset threshold; During the first time, a reference speed corresponding to the acceleration is constrained within a preset safety interval; wherein the preset safety interval is determined based on an upper threshold and a lower threshold of the reference speed.

8. A vehicle speed determination device, characterized in that: The device comprises: an acquiring unit, configured to acquire, during a vehicle driving process, a first driving speed measured by a GPS module and first operating data measured by an IMU module; the first operating data including an acceleration of the vehicle; a cross-correlation analysis unit, configured to perform a cross-correlation analysis on the wheel speed of the vehicle and the first driving speed within a preset time when the GPS module is in a normal state, to obtain a lag time of the GPS module; a first determining unit, configured to determine a first compensation velocity of the IMU module within the lag time based on the lag time of the GPS module and the acceleration; The second determining unit is configured to determine a reference speed of the vehicle based on the first driving speed and the first compensation speed.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps in the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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