Method and system for measuring and calculating acceleration of vehicle ahead in auxiliary driving and storage medium

Abstract

The invention provides a method and a system for measuring and calculating the acceleration of a front vehicle in auxiliary driving and a storage medium, and the method comprises the following steps: collecting the distance information and image information of the front vehicle in front of a target vehicle through a radar and a camera which are disposed on the target vehicle; the distance information and the image information are combined, and a fusion controller is used for calculating the real-time front vehicle speed of the front vehicle; in combination with the real-time preceding vehicle speed and a preset sampling period, a first preceding vehicle acceleration of the preceding vehicle is calculated through a tracking differentiator function; in combination with the real-time preceding vehicle speed and the sampling period, a second preceding vehicle acceleration of the preceding vehicle is calculated through a fitting method; and carrying out acceleration fusion on the first preceding vehicle acceleration and the second preceding vehicle acceleration to obtain the real-time preceding vehicle acceleration of the preceding vehicle. The method has the effect of accurately and stably calculating the acceleration of the front vehicle.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent driving technology, and specifically relates to a method, system and storage medium for calculating the acceleration of a vehicle ahead for assisting driving. Background Art

[0002] At present, 1.3 million people die in traffic accidents every year in the world, and this number continues to grow as the number of vehicles increases. Big data analysis of accidents shows that more than 90% of accidents are caused by human error. Improving vehicle safety and preventing collision risks are crucial to traffic safety. With the help of assisted driving technology, the incidence of traffic accidents is expected to be greatly reduced. Assisted driving refers to providing auxiliary support during the driving process, making it easier and safer for the driver to drive the vehicle. The content of assisted driving includes collision warning, emergency braking, lane keeping assistance, adaptive cruise control, etc.

[0003] In assisted driving, the operating status of the vehicle in front is obtained through sensing methods such as cameras and millimeter-wave radars, and then the vehicle itself is assisted in control, thereby improving driving safety and comfort. In assisted driving, accurate perception of the motion status of the vehicle in front is the key. The perceived states include position, speed, acceleration, type, size, etc. Among these states, position and speed are very important for maintaining a safe distance between vehicles and achieving safe driving. The acceleration state of the target can be used to calculate the driving intention of the vehicle in front, predict the driving behavior of the vehicle in front, and achieve safety and comfort control of the vehicle. Therefore, accurate perception of the acceleration of the vehicle in front is crucial.

[0004] Combining the advantages of cameras and millimeter-wave radars, the two targets can be effectively integrated to output the position of the target in front more accurately, and then the speed of the target can be obtained through differential operation. However, this method uses the second-order difference method, and it is difficult to further accurately obtain the acceleration of the target. In current technology, it is difficult to calculate the acceleration of the vehicle in front through the position or speed of the target. Therefore, it is necessary to design a more reasonable method to accurately and stably calculate the acceleration of the vehicle in front. Summary of the invention

[0005] The present invention provides a method, system and storage medium for calculating the acceleration of a leading vehicle for assisting driving, so as to solve the problem that it is difficult to accurately and stably calculate the acceleration of the leading vehicle.

[0006] In a first aspect, the present invention provides a method for calculating the acceleration of a vehicle ahead for assisting driving, the method comprising the following steps:

[0007] The distance information and image information of the front vehicle located in front of the target vehicle are collected by using the radar and camera arranged on the target vehicle;

[0008] Combining the distance information and the image information, and using a fusion controller to calculate the real-time front vehicle speed of the front vehicle;

[0009] Combining the real-time front vehicle speed and a preset sampling period, a first front vehicle acceleration of the front vehicle is calculated using a tracking differentiator function;

[0010] Combining the real-time front vehicle speed and the sampling period, and calculating the second front vehicle acceleration of the front vehicle by a fitting method;

[0011] The first front vehicle acceleration and the second front vehicle acceleration are accelerated and fused to obtain a real-time front vehicle acceleration of the front vehicle.

[0012] Optionally, the function input of the tracking differentiator function is the sampling period, the first state quantity, the second state quantity and the real-time leading vehicle speed, and the function output of the tracking differentiator function is the first state update quantity and the second state update quantity, wherein the first state update quantity is the acceleration of the first leading vehicle at the current sampling moment in the sampling period.

[0013] Optionally, the step of combining the real-time front vehicle speed and a preset sampling period and calculating the first front vehicle acceleration of the front vehicle by using a tracking differentiator function comprises the following steps:

[0014] Determine an initial first state update amount based on the real-time preceding vehicle speed, and set an initial second state update amount to zero;

[0015] Perform a unit delay operation on the initial first state update amount and the initial second state update amount to obtain the first state amount and the second state amount at the initial sampling moment in the sampling period;

[0016] Determining a time parameter of the tracking differentiator function according to a preset sampling period;

[0017] Calculating a step size parameter by combining the time parameter and a step size factor preset in the tracking differentiator function;

[0018] Calculate a speed parameter by combining the step size parameter, the second state quantity and the real-time front vehicle speed;

[0019] Substituting the difference between the speed parameter and the first state quantity, the second state quantity, the time parameter and the fast factor preset in the tracking differentiator function into the fastest comprehensive function in the tracking differentiator function to calculate the adjustment parameter;

[0020] Calculate the first state update amount at the initial sampling time by combining the first state amount, the sampling period and the second state amount;

[0021] The second state update amount at the initial sampling time is calculated by combining the second state amount, the sampling period and the adjustment parameter;

[0022] Performing a unit delay operation on the first state update amount and the second state update amount at the initial sampling moment to obtain a first state amount and a second state amount at a moment next to the initial sampling moment in the sampling period;

[0023] The above calculation steps are repeated to obtain the acceleration of the first leading vehicle at each sampling moment in the sampling period.

[0024] Optionally, the calculation formula of the tracking differentiator function is as follows:

[0025]

[0026] Where: h0 represents the time parameter, T s represents the sampling period, K represents the step size factor, h1 represents the step size parameter, v represents the speed parameter, V represents the real-time preceding vehicle speed, x1 represents the first state quantity, x2 represents the second state quantity, Fhan(·) represents the fastest comprehensive function, r represents the fast factor, f represents the adjustment parameter, Dx1 represents the first state update quantity, and Dx2 represents the second state update quantity.

[0027] Optionally, the calculation formula of the fastest comprehensive function is as follows:

[0028]

[0029] Where: sign(·) represents a digital sign function, and Out represents the function output of the fastest comprehensive function.

[0030] Optionally, combining the real-time front vehicle speed and the sampling period and calculating the second front vehicle acceleration of the front vehicle by a fitting method comprises the following steps:

[0031] Obtaining a speed acquisition time corresponding to the real-time front vehicle speed;

[0032] The real-time preceding vehicle speed and the corresponding speed acquisition time are used as speed points;

[0033] Performing linear fitting on all the speed points to obtain a speed fitting equation;

[0034] The speed fitting equation and the sampling period are combined and the second front vehicle acceleration of the front vehicle is obtained by least square derivation.

[0035] Optionally, combining the speed fitting equation and the sampling period and using least squares to derive the second front vehicle acceleration of the front vehicle comprises the following steps:

[0036] Extracting n speed points in the speed fitting equation to construct a basic speed matrix;

[0037] The standard velocity matrix is ​​calculated according to the basic velocity matrix, and the first row of the standard velocity matrix is ​​used as the standard vector. The calculation formula of the standard velocity matrix is ​​as follows:

[0038] W=(A T ×A) -1 ×A T

[0039] Wherein: W represents the standard speed matrix, A represents the basic speed matrix, and F represents matrix transposition;

[0040] The n real-time preceding vehicle speeds which are in a continuous state at the speed acquisition moment constitute a speed vector;

[0041] The second front vehicle acceleration of the front vehicle is calculated by combining the speed vector, the standard vector and the sampling period. The calculation formula of the second front vehicle acceleration is as follows:

[0042]

[0043] Where: a2 represents the second front vehicle acceleration, W1 represents the standard vector, represents the velocity vector, T s represents the sampling period.

[0044] Optionally, the performing acceleration fusion on the first front vehicle acceleration and the second front vehicle acceleration to obtain the real-time front vehicle acceleration of the front vehicle comprises the following steps:

[0045] determining whether the acceleration of the second front vehicle exceeds a preset acceleration range;

[0046] If the second front vehicle acceleration exceeds the acceleration range, the first front vehicle acceleration is used as the real-time front vehicle acceleration of the front vehicle;

[0047] If the second front vehicle acceleration does not exceed the acceleration interval, calculating the acceleration difference between the first front vehicle acceleration and the second front vehicle acceleration;

[0048] Determining whether the acceleration difference is greater than a preset difference threshold;

[0049] If the acceleration difference is greater than the difference threshold, a first weight is assigned to the first front vehicle acceleration, a second weight is assigned to the second front vehicle acceleration, and the product of the first front vehicle acceleration and the first weight plus the product of the second front vehicle acceleration and the second weight is used as the real-time front vehicle acceleration, and the first weight is greater than the second weight;

[0050] If the acceleration difference is less than or equal to the difference threshold, a third weight is assigned to the first leading vehicle acceleration, a fourth weight is assigned to the second leading vehicle acceleration, and the product of the first leading vehicle acceleration and the third weight plus the product of the second leading vehicle acceleration and the fourth weight is used as the real-time leading vehicle acceleration, the third weight is less than the fourth weight, and the sum of the first weight and the second weight is equal to the sum of the third weight and the fourth weight.

[0051] In a second aspect, the present invention further provides a system for measuring the acceleration of a vehicle ahead for assisted driving, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the system implements the method for measuring the acceleration of a vehicle ahead for assisted driving as described in the first aspect when the processor executes the computer program.

[0052] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method for calculating the acceleration of a vehicle ahead for assisted driving described in the first aspect are implemented.

[0053] The beneficial effects of the present invention are:

[0054] In assisted driving, the fusion perception method of cameras and millimeter-wave radars is used to directly obtain the running status of the vehicle in front, including position and speed information, but the accurate acquisition of acceleration information has not yet been solved and requires further research. The traditional method of obtaining acceleration is generally to differentiate the velocity. However, the actual speed information contains noise, which has a great impact on the differentiation, making it difficult to obtain the acceleration accurately and stably. The use of filtering to pre-process the speed information will inevitably cause a large delay and bring a large amount of calculation. In addition, the actual situation of frame loss and inconsistent communication cycles when obtaining speed information from cameras and radars also makes it difficult to apply the differentiation method to obtain acceleration.

[0055] The present invention proposes an acceleration calculation method combining a tracking differentiator and a speed differential fitting. According to the speed information obtained from the camera and the radar, a tracking differentiator and a fitting method are adopted, and by modeling the signal, a differential tracker is designed to obtain the acceleration of the preceding vehicle. At the same time, the speed differential is fitted, and another acceleration is obtained by weighted summation. The two accelerations are fused to obtain the final acceleration of the preceding vehicle. The present invention can comprehensively solve the problems of noise influence, phase delay, large amount of calculation, and sampling frame loss influence in the traditional acceleration obtaining process, and realize accurate and stable acceleration acquisition. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 The figure is a flowchart of a method for calculating the acceleration of a vehicle ahead for assisting driving in the present invention.

[0057] Figure 2 The present invention is a flowchart of a method for calculating the acceleration of a vehicle ahead for assisting driving.

[0058] Figure 3 It is a schematic diagram of the calculation of the tracking differentiator function in the present invention. DETAILED DESCRIPTION

[0059] The terms "first", "second", etc. in the specification and claims of the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0060] The present invention discloses a method for calculating the acceleration of a vehicle ahead of an assisted driving vehicle. The framework of the method for calculating the acceleration of a vehicle ahead of an assisted driving vehicle disclosed in the present invention is as follows: Figure 1 As shown in the figure, the original front vehicle speed (V) information is obtained from the perception fusion controller of the assisted driving, and the sampling period (T) of the speed information is obtained according to the communication period. s ). The acceleration is obtained by using the method proposed by the present invention according to the speed information and the sampling period. The method of the present invention comprises three parts, namely, a tracking differentiator method, a differential fitting method and a fusion rule. The first front vehicle acceleration is obtained by using the tracking differentiator method, the second front vehicle acceleration is obtained by using the differential fitting method, and finally the two accelerations are fused by using the fusion rule, and the final front vehicle acceleration is output.

[0061] Specifically, refer to Figure 2, the method for calculating the acceleration of the vehicle ahead for assisted driving specifically includes the following steps:

[0062] S101. Collect distance information and image information of a vehicle in front of the target vehicle through a radar and a camera provided on the target vehicle.

[0063] Among them, the radar sensor on the target vehicle can detect the position and distance information of the vehicle in front. The radar converts the time and intensity of the reflected signal sent back into distance and relative speed information. The camera on the target vehicle can capture the image information of the vehicle in front. Through the image processing algorithm, the position and movement status of the vehicle in front can be identified.

[0064] S102. Combine the distance information and the image information and use the fusion controller to calculate the real-time front vehicle speed of the front vehicle.

[0065] Among them, the fusion controller fuses and processes the data from the radar and the camera to obtain more accurate information about the position and speed of the target vehicle. The fusion controller can use the sensor fusion algorithm to fuse the data from the radar and the camera, eliminate noise and errors, and improve the accuracy of the data. Based on the data processed by the fusion controller, the speed of the target vehicle can be calculated. By comparing the position information of the vehicle in front at two points in time, the displacement of the target vehicle can be calculated, and the speed of the target vehicle can be calculated based on the time interval.

[0066] It should be noted that the algorithm and accuracy of the fusion controller will affect the acquired target vehicle speed. At the same time, in certain situations (such as fast changes in the speed and direction of the vehicle ahead, sensor occlusion, etc.), it may be challenging to obtain the accurate target vehicle speed. Therefore, in practical applications, it is necessary to comprehensively consider various factors to evaluate and use the acquired target vehicle speed data.

[0067] S103. Combining the real-time front vehicle speed and the preset sampling period, the first front vehicle acceleration of the front vehicle is calculated using the tracking differentiator function.

[0068] Among them, refer to Figure 3 The input of the tracking differentiator function is the speed V and the sampling period T s , the output is acceleration. x1 and x2 are internal state variables, which are updated to Dx1 and Dx2 after this calculation. Among them, Dx1 tracks the input signal V and is the velocity value after filtering; theoretically, x3 = x1. Therefore, Dx2 can be regarded as the approximate differential value of velocity V. Dx1 and Dx2 pass through 1 / z, and the state value at this moment is returned to the next moment, forming a recursive operation. The initial value of Dx1 is x 10 , which is generally taken as the first value of velocity V. The initial value of Dx2 is x 2o, which is generally taken as 0. In this way, the acceleration corresponding to the speed can be continuously output.

[0069] In the tracking differentiator, 1 / z represents a unit delay operation, where z is a complex variable representing the z-transform of a unit delay. The 1 / z operation transfers the state value of the current moment to the next moment, realizing recursive operation. Specifically, the tracking differentiator is a discrete-time system that updates state variables and output values ​​through recursive operation. In each discrete time step, the input signal is filtered and processed to obtain the output value. The 1 / z operation transfers the state value of the current moment to the next moment as the input for the next calculation. The 1 / z operation realizes the delayed transfer of state variables, ensuring that the state value at each moment can correctly participate in the next calculation. By dividing the state value of the current moment by z, that is, 1 / z, it can be passed to the next moment as the input for the next calculation.

[0070] S104. Combining the real-time front vehicle speed and the sampling period, and calculating the second front vehicle acceleration of the front vehicle through a fitting method.

[0071] The principle of using the fitting method to obtain acceleration is to convert velocity-time (V i , t i ) as a point, and perform linear fitting on n such points to obtain the fitting equation V i =a2·t i +b, the slope is the required acceleration a3. Then the least square method is used to derive the acceleration a2.

[0072] S105. Perform acceleration fusion on the first front vehicle acceleration and the second front vehicle acceleration to obtain the real-time front vehicle acceleration of the front vehicle.

[0073] Among them, the above acceleration a1 is obtained by tracking differentiator, and acceleration a2 is obtained by fitting method. The tracking differentiator method has a small phase delay, which can resist the influence of velocity value frame loss, and the calculation result is highly stable, but the accuracy is related to the adjusted parameters. The fitting method has high accuracy, no parameters need to be adjusted, and small amount of calculation, but the velocity value frame loss will cause the calculation result to jump, and the stability is not high. Accuracy and stability can be improved through fusion.

[0074] The implementation principle of this embodiment is:

[0075] According to the speed information obtained from the camera and radar, a tracking differentiator and fitting method are adopted to model the signal and design a differential tracker to obtain the acceleration of the vehicle in front. At the same time, the speed difference is fitted and another acceleration is obtained by weighted summation. The two accelerations are fused to obtain the final acceleration of the vehicle in front. The present invention can comprehensively solve the problems of noise influence, phase delay, large amount of calculation, and sampling frame loss in the traditional acceleration process, and realize accurate and stable acceleration acquisition.

[0076] In one embodiment, the function input of the tracking differentiator function is a sampling period, a first state quantity, a second state quantity and a real-time leading vehicle speed, and the function output of the tracking differentiator function is a first state update quantity and a second state update quantity, and the first state update quantity is the acceleration of the first leading vehicle at the current sampling moment in the sampling period.

[0077] In this embodiment, step S103 specifically includes the following steps:

[0078] Determine an initial first state update amount based on the real-time preceding vehicle speed, and set an initial second state update amount to zero;

[0079] Perform a unit delay operation on the initial first state update amount and the initial second state update amount to obtain the first state amount and the second state amount at the initial sampling time in the sampling period;

[0080] Determining a time parameter of a tracking differentiator function according to a preset sampling period;

[0081] The step size parameter is calculated by combining the time parameter and the step size factor preset in the tracking differentiator function;

[0082] The speed parameter is calculated by combining the step length parameter, the second state quantity and the real-time front vehicle speed;

[0083] Substituting the difference between the speed parameter and the first state quantity, the second state quantity, the time parameter and the fast factor preset in the tracking differentiator function into the fastest comprehensive function in the tracking differentiator function, and calculating the adjustment parameter;

[0084] The first state update amount at the initial sampling time is calculated by combining the first state amount, the sampling period and the second state amount;

[0085] The second state update amount at the initial sampling time is calculated by combining the second state amount, the sampling period and the adjustment parameter;

[0086] Perform a unit delay operation on the first state update amount and the second state update amount at the initial sampling moment to obtain the first state amount and the second state amount at the next moment after the initial sampling moment in the sampling period;

[0087] Repeat the above calculation steps to obtain the acceleration of the first leading vehicle at each sampling moment in the sampling period.

[0088] In this embodiment, refer to Figure 3 , Figure 3 The core of the tracking differentiator function is the Tracking Differentiator (TD), and the calculation formula of the tracking differentiator function is as follows:

[0089]

[0090] Where: h0 represents the time parameter, T s represents the sampling period, K represents the step size factor, h1 represents the step size parameter, v represents the speed parameter, V represents the real-time front vehicle speed, x1 represents the first state quantity, x2 represents the second state quantity, Fhan(·) represents the fastest comprehensive function, r represents the fast factor, f represents the adjustment parameter, Dx1 represents the first state update quantity, and Dx2 represents the second state update quantity.

[0091] The input is the first state quantity x1, the second state quantity x2, the real-time front vehicle speed V and the sampling period T s . The output is the updated value of the state quantity, the first state update quantity Dx1, and the second state update quantity Dx2. h0, h1, v, and f are all internal parameter variables. The adjustable parameter r is the fast factor. The larger r is, the faster x1 can track the signal, but it is also more affected by noise. r is generally taken as 30. The adjustable parameter K is the step size factor. The larger K is, the better the filtering effect, but the greater the phase loss of signal x1 tracking signal V. The value range of K is 1 to 1.5, and is generally taken as 1. By properly adjusting r and K, a tracking effect with small delay and small noise pollution can be obtained.

[0092] The core function of the tracking differentiator is Fhan(·). The differential function is realized by tracking the input signal "as quickly as possible". The optimal control theory is applied to avoid the chattering phenomenon when the system enters the steady state. The fastest comprehensive function Fhan(·) is derived based on the needs of numerical calculation. The calculation formula of the fastest comprehensive function is as follows:

[0093]

[0094] Where: sign(·) represents the digital sign function, and Out represents the function output of the fastest synthesis function. The sign(·) function returns an integer variable indicating the positive or negative sign of the parameter. The parameter in the function is any valid numeric expression. The return result is as follows: if the function parameter is greater than 0, sign(·) returns 1; if the function parameter is equal to 0, sign(·) returns 0; if the function parameter is less than 0, sign(·) returns -1. Therefore, the sign of the function parameter determines the return value of the sign(·) function.

[0095] In one implementation manner, step S104 specifically includes the following steps:

[0096] Get the speed acquisition time corresponding to the real-time front vehicle speed;

[0097] The real-time front vehicle speed and the corresponding speed acquisition time are taken as speed points;

[0098] Perform linear fitting on all velocity points to obtain the velocity fitting equation;

[0099] The speed fitting equation and the sampling period are combined and the second front vehicle acceleration of the front vehicle is derived by least squares.

[0100] In this embodiment, when the real-time front vehicle speed is obtained by the fusion controller, the corresponding speed acquisition time is obtained by the timestamp of the real-time front vehicle speed signal, and the i-th real-time front vehicle speed and the corresponding i-th speed acquisition time are used as the speed point (V i , t i ), perform linear fitting on all velocity points and obtain the velocity fitting equation V i =a2·t i +b.

[0101] In one embodiment, the steps of combining the speed fitting equation and the sampling period and using least squares to derive the second front vehicle acceleration of the front vehicle specifically include the following steps:

[0102] Extract n velocity points in the velocity fitting equation to construct a basic velocity matrix;

[0103] The standard velocity matrix is ​​calculated based on the basic velocity matrix, and the first row of the standard velocity matrix is ​​used as the standard vector. The calculation formula of the standard velocity matrix is ​​as follows:

[0104] W=(A T ×A) -1 ×A T

[0105] Where: W represents the standard velocity matrix, A represents the basic velocity matrix, and T represents the matrix transpose;

[0106] The n real-time front vehicle speeds that are in a continuous state at the time of speed acquisition constitute a speed vector;

[0107] The second front vehicle acceleration of the front vehicle is calculated by combining the velocity vector, the standard vector and the sampling period. The calculation formula of the second front vehicle acceleration is as follows:

[0108]

[0109] Where: a2 represents the acceleration of the second front vehicle, W1 represents the standard vector, represents the velocity vector, T s Indicates the sampling period.

[0110] In this implementation, usually n≥6, n speed points in the speed fitting equation are extracted to construct a basic speed matrix, and the basic speed matrix is ​​specifically as follows:

[0111]

[0112] Based on the basic speed matrix in the above formula, the standard speed matrix is ​​calculated by the calculation formula of the standard speed matrix. The n real-time front vehicle speeds that are in a continuous state at the time of speed acquisition constitute the speed vector Finally, the second front vehicle acceleration of the front vehicle is calculated by combining the speed vector, the standard vector and the sampling period, and the second front vehicle acceleration is calculated by the calculation formula of the second front vehicle acceleration. In this embodiment, after n is selected, the standard vector W1 can be calculated offline according to the construction of the basic speed matrix and the calculation formula of the standard speed matrix, and the calculation of the second front vehicle acceleration a2 is simplified to the weighted sum, which greatly reduces the amount of calculation.

[0113] In one implementation manner, step S105 specifically includes the following steps:

[0114] Determining whether the acceleration of the second front vehicle exceeds a preset acceleration range;

[0115] If the second front vehicle acceleration exceeds the acceleration range, the first front vehicle acceleration is used as the real-time front vehicle acceleration of the front vehicle;

[0116] If the acceleration of the second front vehicle does not exceed the acceleration interval, calculating the acceleration difference between the acceleration of the first front vehicle and the acceleration of the second front vehicle;

[0117] Determine whether the acceleration difference is greater than a preset difference threshold;

[0118] If the acceleration difference is greater than the difference threshold, a first weight is assigned to the first front vehicle acceleration, a second weight is assigned to the second front vehicle acceleration, and the product of the first front vehicle acceleration and the first weight plus the product of the second front vehicle acceleration and the second weight is used as the real-time front vehicle acceleration, and the first weight is greater than the second weight;

[0119] If the acceleration difference is less than or equal to the difference threshold, the third weight is assigned to the first front vehicle acceleration, the fourth weight is assigned to the second front vehicle acceleration, and the product of the first front vehicle acceleration and the third weight plus the product of the second front vehicle acceleration and the fourth weight is taken as the real-time front vehicle acceleration, the third weight is less than the fourth weight, and the sum of the first weight and the second weight is equal to the sum of the third weight and the fourth weight.

[0120] In this embodiment, the acceleration fusion process is shown in Table 1. An acceleration greater than 0 is acceleration, and less than 0 is deceleration. Generally, the acceleration is between -6 and 6, that is, the preset acceleration interval is [-6, 6]. Because the acceleration a1 of the first front vehicle is very stable and will not jump, only the abnormal value of the acceleration a2 of the second front vehicle is judged. When the acceleration a2 of the second front vehicle is outside the acceleration interval [-6, 6], only the acceleration a1 of the first front vehicle is taken as the output.

[0121] When the first front vehicle acceleration a1 and the second front vehicle acceleration a2 are very close, that is, the difference between the two is less than the preset difference threshold 0.5, both are considered to be relatively accurate. At this time, the second front vehicle acceleration a2 is chosen to be more trusted, and the first weight 0.4 and the second weight 0.6 are assigned to the first front vehicle acceleration and the second front vehicle acceleration respectively, and the product of the first front vehicle acceleration and the first weight plus the product of the second front vehicle acceleration and the second weight is taken as the real-time front vehicle acceleration.

[0122] When the error between the first leading vehicle acceleration a1 and the second leading vehicle acceleration a2 is large, the first leading vehicle acceleration a1 is chosen to be more trusted, and thus the third weight 0.8 and the fourth weight 0.2 are assigned to the first leading vehicle acceleration and the second leading vehicle acceleration respectively, and the product of the first leading vehicle acceleration and the third weight plus the product of the second leading vehicle acceleration and the fourth weight is taken as the real-time leading vehicle acceleration.

[0123] Table 1 Acceleration fusion process

[0124]

[0125] The present invention also discloses a system for measuring the acceleration of a vehicle ahead for assisted driving, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for measuring the acceleration of a vehicle ahead for assisted driving as described in any of the above-mentioned embodiments is implemented.

[0126] The present invention also discloses a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for calculating the acceleration of a vehicle ahead of assisted driving as described in any of the above-mentioned embodiments are implemented.

[0127] A person skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of protection of the present application is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present application as above, which are not provided in detail for the sake of simplicity.

[0128] One or more embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of the present application should be included in the protection scope of the present application.

Claims

1. A method for calculating the acceleration of a vehicle ahead for assisting driving, characterized in that: The steps include: The distance information and image information of the front vehicle located in front of the target vehicle are collected by using the radar and camera arranged on the target vehicle; Combining the distance information and the image information, and using a fusion controller to calculate the real-time front vehicle speed of the front vehicle; Combining the real-time front vehicle speed and a preset sampling period, a first front vehicle acceleration of the front vehicle is calculated using a tracking differentiator function; Combining the real-time front vehicle speed and the sampling period, and calculating the second front vehicle acceleration of the front vehicle by a fitting method; The first front vehicle acceleration and the second front vehicle acceleration are accelerated and fused to obtain a real-time front vehicle acceleration of the front vehicle.

2. The method for calculating the acceleration of the vehicle ahead for assisted driving according to claim 1, characterized in that: The function input of the tracking differentiator function is the sampling period, the first state quantity, the second state quantity and the real-time leading vehicle speed, and the function output of the tracking differentiator function is the first state update quantity and the second state update quantity, wherein the first state update quantity is the acceleration of the first leading vehicle at the current sampling moment in the sampling period.

3. The method for calculating the acceleration of the vehicle ahead for assisted driving according to claim 2, characterized in that: The step of combining the real-time front vehicle speed and the preset sampling period and calculating the first front vehicle acceleration of the front vehicle by using the tracking differentiator function comprises the following steps: Determine an initial first state update amount based on the real-time preceding vehicle speed, and set an initial second state update amount to zero; Perform a unit delay operation on the initial first state update amount and the initial second state update amount to obtain the first state amount and the second state amount at the initial sampling moment in the sampling period; Determining a time parameter of the tracking differentiator function according to a preset sampling period; Calculating a step size parameter by combining the time parameter and a step size factor preset in the tracking differentiator function; Calculate a speed parameter by combining the step size parameter, the second state quantity and the real-time front vehicle speed; Substituting the difference between the speed parameter and the first state quantity, the second state quantity, the time parameter and the fast factor preset in the tracking differentiator function into the fastest comprehensive function in the tracking differentiator function to calculate the adjustment parameter; Calculate the first state update amount at the initial sampling time by combining the first state amount, the sampling period and the second state amount; The second state update amount at the initial sampling time is calculated by combining the second state amount, the sampling period and the adjustment parameter; Performing a unit delay operation on the first state update amount and the second state update amount at the initial sampling moment to obtain a first state amount and a second state amount at a moment next to the initial sampling moment in the sampling period; The above calculation steps are repeated to obtain the acceleration of the first leading vehicle at each sampling moment in the sampling period.

4. The method for calculating the acceleration of the vehicle ahead for assisted driving according to claim 3, characterized in that: The calculation formula of the tracking differentiator function is as follows: Where: h0 represents the time parameter, T s represents the sampling period, K represents the step size factor, h1 represents the step size parameter, υ represents the speed parameter, V represents the real-time preceding vehicle speed, x1 represents the first state quantity, x2 represents the second state quantity, Fhan(·) represents the fastest comprehensive function, r represents the fast factor, f represents the adjustment parameter, Dx1 represents the first state update quantity, and Dx2 represents the second state update quantity.

5. The method for calculating the acceleration of the vehicle ahead for assisted driving according to claim 4, characterized in that: The calculation formula of the fastest comprehensive function is as follows: Where: sign(·) represents a digital sign function, and Out represents the function output of the fastest comprehensive function.

6. The method for calculating the acceleration of the vehicle ahead for assisted driving according to claim 1, characterized in that: The combining the real-time front vehicle speed and the sampling period and calculating the second front vehicle acceleration of the front vehicle by a fitting method comprises the following steps: Obtaining a speed acquisition time corresponding to the real-time front vehicle speed; The real-time preceding vehicle speed and the corresponding speed acquisition time are used as speed points; Performing linear fitting on all the speed points to obtain a speed fitting equation; The speed fitting equation and the sampling period are combined and the second front vehicle acceleration of the front vehicle is obtained by least square derivation.

7. The method for calculating the acceleration of the vehicle ahead for assistive driving according to claim 6, characterized in that: The combining the speed fitting equation and the sampling period and using least squares to derive the second front vehicle acceleration of the front vehicle comprises the following steps: Extracting n speed points in the speed fitting equation to construct a basic speed matrix; The standard velocity matrix is ​​calculated according to the basic velocity matrix, and the first row of the standard velocity matrix is ​​used as the standard vector. The calculation formula of the standard velocity matrix is ​​as follows: W=(A T ×A) -1 ×A T Wherein: W represents the standard speed matrix, A represents the basic speed matrix, and T represents matrix transposition; The n real-time preceding vehicle speeds which are in a continuous state at the speed acquisition moment constitute a speed vector; The second front vehicle acceleration of the front vehicle is calculated by combining the speed vector, the standard vector and the sampling period. The calculation formula of the second front vehicle acceleration is as follows: Where: a2 represents the second front vehicle acceleration, W1 represents the standard vector, represents the velocity vector, T s represents the sampling period.

8. The method for calculating the acceleration of the vehicle ahead for assisted driving according to claim 1, characterized in that: The step of fusing the first front vehicle acceleration and the second front vehicle acceleration to obtain the real-time front vehicle acceleration of the front vehicle comprises the following steps: determining whether the acceleration of the second front vehicle exceeds a preset acceleration range; If the second front vehicle acceleration exceeds the acceleration range, the first front vehicle acceleration is used as the real-time front vehicle acceleration of the front vehicle; If the second front vehicle acceleration does not exceed the acceleration interval, calculating the acceleration difference between the first front vehicle acceleration and the second front vehicle acceleration; Determining whether the acceleration difference is greater than a preset difference threshold; If the acceleration difference is greater than the difference threshold, a first weight is assigned to the first front vehicle acceleration, a second weight is assigned to the second front vehicle acceleration, and the product of the first front vehicle acceleration and the first weight plus the product of the second front vehicle acceleration and the second weight is used as the real-time front vehicle acceleration, and the first weight is greater than the second weight; If the acceleration difference is less than or equal to the difference threshold, a third weight is assigned to the first leading vehicle acceleration, a fourth weight is assigned to the second leading vehicle acceleration, and the product of the first leading vehicle acceleration and the third weight plus the product of the second leading vehicle acceleration and the fourth weight is used as the real-time leading vehicle acceleration, the third weight is less than the fourth weight, and the sum of the first weight and the second weight is equal to the sum of the third weight and the fourth weight.

9. A system for calculating the acceleration of a vehicle ahead for assisting driving, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for calculating the acceleration of the vehicle ahead for assisted driving as described in any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for calculating the acceleration of a vehicle ahead for assisted driving according to any one of claims 1 to 8 are implemented.

Images