Automatic emergency braking control method and system based on road adhesion coefficient estimation

Abstract

The invention discloses an automatic emergency braking control method and system based on road adhesion coefficient estimation, and belongs to the technical field of automatic driving. Comprising the following steps: acquiring and fitting a plurality of road adhesion coefficients and tire slip rates of the self-driving automobile in an acceleration stage or a starting stage, and generating a rising fitting line; acquiring and fitting a plurality of road adhesion coefficients and tire slip rates of the self-driving automobile in a deceleration stage, and acquiring a descent fitting line; based on the intersection point of the ascending fitting line and the descending fitting line, curve fitting is conducted on the ascending fitting line and the descending fitting line, a road surface adhesion coefficient-tire slip rate curve corresponding to the current road surface is obtained, and a road surface adhesion coefficient estimated value is extracted; and the relative vehicle speed of the automatic driving vehicle and the target obstacle is obtained, and an automatic emergency braking threshold value is determined in combination with the road adhesion coefficient estimation value. The braking threshold value can be adaptively adjusted according to the type of the road surface, and the problem that an existing AEB system is not timely in braking on the low-attachment road surface is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of autonomous driving, and in particular to an automatic emergency braking control method and system based on road adhesion coefficient estimation. Background Art

[0002] The statements in this section merely mention background art related to the present invention and do not necessarily constitute prior art.

[0003] Traditional automatic emergency braking control (AEB) systems need to observe the target in front and obtain the relative distance and relative speed between the vehicle and the target to calculate the collision time TTC. When TTC is lower than the set threshold TB, automatic emergency braking is triggered, and the AEB system issues a maximum deceleration command, which is responded and executed by the braking system.

[0004] This strategy does not take the road adhesion coefficient into consideration. When driving on a road with a low adhesion coefficient, the braking system cannot respond to the maximum deceleration command issued by the AEB system, and the actual deceleration will be lower than expected, which may easily lead to a collision risk. Therefore, it is particularly necessary for the AEB system to consider the road adhesion coefficient during operation, and the braking command should be issued in advance on a road with a low adhesion coefficient (low adhesion road).

[0005] In the Chinese invention patent with application number 202011603975.5, a visual target detection algorithm is used to identify dry cement roads, dry asphalt roads, wet cement roads, wet asphalt roads, and icy and snowy roads, and calculates the safe distance according to the adhesion coefficient ranges corresponding to different roads. However, this method is based on supervised deep learning, and its estimation of the adhesion coefficient depends on training samples. Once an unrecognizable road type appears, the adhesion coefficient of the road cannot be estimated.

[0006] In the Chinese invention patent with application number 202111225837.2, an interactive multi-model is established, and the adhesion coefficient set by each model is probability-weighted to obtain the road adhesion coefficient at the current moment. However, the calculated adhesion coefficient can only represent the road adhesion coefficient under the current tire slip rate, and cannot represent the maximum adhesion coefficient that the current road surface can provide. Summary of the invention

[0007] In order to address the deficiencies of the prior art, the present invention provides an automatic emergency braking control method, system, electronic device, computer-readable storage medium and computer program product based on road adhesion coefficient estimation, which adaptively adjusts the TTC value in combination with the dynamic changes of the road adhesion coefficient to improve the performance of the AEB system on low-adhesion roads.

[0008] In a first aspect, the present invention provides an automatic emergency braking control method based on road adhesion coefficient estimation;

[0009] An automatic emergency braking control method based on road adhesion coefficient estimation comprises:

[0010] Obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in the acceleration phase or the starting phase and fit them to generate an ascending fitting line; obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in the deceleration phase and fit them to obtain a descending fitting line;

[0011] Based on the intersection of the ascending fitting line and the descending fitting line, curve fitting is performed on the ascending fitting line and the descending fitting line to obtain a road adhesion coefficient-tire slip rate curve corresponding to the current road surface and extract an estimated value of the road adhesion coefficient;

[0012] The relative speed of the autonomous driving vehicle and the target obstacle is obtained, and the automatic emergency braking threshold is determined in combination with the estimated value of the road adhesion coefficient, so as to perform automatic emergency braking based on the automatic emergency braking threshold and the collision time.

[0013] In some implementations, obtaining the road adhesion coefficient and tire slip rate of the autonomous driving vehicle during the acceleration phase or the starting phase includes:

[0014] Obtain the acceleration of the autonomous vehicle during the acceleration or starting phase, and determine the road adhesion coefficient based on the acceleration and gravity acceleration;

[0015] The speed, angular velocity of the driving wheels and the rolling radius of the tires of the autonomous vehicle during the acceleration or starting phase are obtained to determine the tire slip rate.

[0016] In some implementations, obtaining the road adhesion coefficient and tire slip rate of the autonomous driving vehicle during the deceleration phase includes:

[0017] Obtain the deceleration of the autonomous vehicle during the deceleration phase, and determine the road adhesion coefficient based on the deceleration and gravity acceleration;

[0018] The speed of the autonomous vehicle during the deceleration phase, the angular velocity of the braking wheel, and the tire rolling radius are obtained to determine the tire slip rate.

[0019] In some embodiments, the curve fitting of the ascending fit line and the descending fit line based on the intersection of the ascending fit line and the descending fit line is specifically as follows: a plurality of fitting points are determined on the ascending fit line and the descending fit line according to confidence, and the plurality of fitting points and the intersection of the ascending fit line and the descending fit line are fitted by a second-order Bezier curve.

[0020] In some implementations, the automatic emergency braking threshold is expressed as:

[0021]

[0022] Where V L represents the relative speed between the autonomous driving vehicle and the target obstacle, μ max represents the estimated value of the road adhesion coefficient, and T0 represents the response time of the braking system.

[0023] In some implementations, based on the automatic emergency braking threshold and the collision time, performing the automatic emergency braking includes: performing emergency braking when the collision time is lower than the automatic emergency braking threshold.

[0024] In a second aspect, the present invention provides an automatic emergency braking control system based on road adhesion coefficient estimation;

[0025] An automatic emergency braking control system based on road adhesion coefficient estimation, comprising:

[0026] The fitting module is configured to: obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in an acceleration phase or a starting phase and fit them to generate an ascending fitting line; obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in a deceleration phase and fit them to obtain a descending fitting line;

[0027] The road adhesion coefficient estimation module is configured to: perform curve fitting on the ascending fitting line and the descending fitting line based on the intersection of the ascending fitting line and the descending fitting line, obtain a road adhesion coefficient-tire slip rate curve corresponding to the current road surface, and extract an estimated value of the road adhesion coefficient;

[0028] The automatic emergency braking module is configured to obtain the relative speed of the autonomous driving vehicle and the target obstacle, determine the automatic emergency braking threshold in combination with the estimated value of the road adhesion coefficient, and perform automatic emergency braking based on the automatic emergency braking threshold and the collision time.

[0029] In a third aspect, the present invention provides an electronic device;

[0030] An electronic device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the automatic emergency braking control method based on road adhesion coefficient estimation.

[0031] In a fourth aspect, the present invention provides a computer-readable storage medium;

[0032] A computer-readable storage medium stores a computer program / instruction, which, when executed by a processor, implements the steps of the automatic emergency braking control method based on road adhesion coefficient estimation.

[0033] In a fifth aspect, the present invention provides a computer program product;

[0034] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned automatic emergency braking control method based on road adhesion coefficient estimation.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. The technical solution provided by the present invention samples the road adhesion coefficient-slip rate during acceleration and braking during vehicle driving, fits the straight line segment of the adhesion coefficient-slip rate graph by a linear regression method, and fits the curve segment of the adhesion coefficient-slip rate by a second-order Bezier curve, thereby estimating the maximum adhesion coefficient of the road surface, adjusting the time threshold for triggering automatic emergency braking, and considering the calculation of the road adhesion coefficient under different tire slip rates, so that the automatic emergency braking function can exert the maximum effect on roads with different adhesion coefficients.

[0037] 2. The technical solution provided by the present invention determines the relationship between the road adhesion coefficient and the tire slip rate in combination with the real-time driving state of the vehicle, and then obtains the real-time road adhesion coefficient estimation value corresponding to the corresponding road section, and adjusts the automatic emergency braking threshold according to the real-time driving state of the vehicle and the road state, thereby improving driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0039] Figure 1 A schematic flow chart of an automatic emergency braking control method based on road adhesion coefficient estimation provided by an embodiment of the present invention;

[0040] Figure 2 An example diagram of a road adhesion coefficient-tire slip rate (μ-s) curve provided in an embodiment of the present invention;

[0041] Figure 3 An example diagram of μ-s straight line segment fitting provided by an embodiment of the present invention;

[0042] Figure 4 An example diagram of μ-s curve segment fitting provided by an embodiment of the present invention;

[0043] Figure 5 μ provided in the embodiment of the present invention max Example diagram for determining the value. DETAILED DESCRIPTION

[0044] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0045] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "include" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0047] Embodiment 1

[0048] The automatic emergency braking function of existing vehicles does not take into account the impact of different road types on vehicle braking; therefore, the present invention provides an automatic emergency braking control method based on road adhesion coefficient estimation, which reflects the road state through the real-time driving state of the vehicle and dynamically adjusts the automatic emergency braking threshold based on this, thereby improving driving safety.

[0049] Next, combine Figure 1-Figure 5 , an automatic emergency braking control method based on road adhesion coefficient estimation disclosed in this embodiment is described in detail. The automatic emergency braking control method based on road adhesion coefficient estimation includes the following steps:

[0050] S1. Obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in the acceleration phase or the starting phase and fit them to generate an ascending fitting line; obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in the deceleration phase and fit them to obtain a descending fitting line. Specifically including:

[0051] S101. Obtain multiple accelerations of the autonomous driving vehicle during the acceleration phase or the starting phase, and determine multiple road adhesion coefficients μ1 according to the acceleration and the acceleration of gravity; obtain multiple speeds of the autonomous driving vehicle during the acceleration phase or the starting phase, multiple angular velocities of driving wheels and tire rolling radii, and determine the tire slip rate s1; fit the multiple collected (μ1, s1) sample values ​​through a linear regression method to obtain an ascending fitting line, i.e., the first half (ascending section) of the μ-s curve.

[0052] Here, μ1 is expressed as:

[0053]

[0054] Where a1 represents the acceleration of the autonomous vehicle, g represents the acceleration due to gravity, v represents the speed of the autonomous vehicle, w1 represents the angular velocity of the driving wheel, and r represents the rolling radius of the tire.

[0055] S102. Obtain multiple decelerations of the autonomous driving vehicle in the deceleration stage, and determine the road adhesion coefficient based on the multiple decelerations and gravity acceleration; obtain multiple speeds of the autonomous driving vehicle in the deceleration stage, multiple angular velocities of the brake wheels, and tire rolling radii, and determine multiple tire slip rates; fit the multiple collected (μ2, s2) sample values ​​through a linear regression method to obtain a descending fitting line, that is, the second half (descending section) of the μ-s curve.

[0056] Here, μ2 is expressed as:

[0057]

[0058] s2 is represented by:

[0059]

[0060] Where a2 represents the deceleration of the autonomous vehicle, g represents the acceleration of gravity, v represents the speed of the autonomous vehicle, w2 represents the angular velocity of the brake wheel, and r represents the rolling radius of the tire.

[0061] Furthermore, during the acceleration or constant speed driving stage, the speed of the autonomous driving vehicle is determined based on the angular velocity of the non-driving wheel and the rolling radius of the tire, which is expressed as:

[0062] v = w0r;

[0063] Where w0 represents the angular velocity of the non-driven wheel.

[0064] In the deceleration stage, the angular velocity of the autonomous vehicle is determined based on the vehicle speed before deceleration and the deceleration during deceleration, which is expressed as:

[0065]

[0066] Where v0 represents the vehicle speed before deceleration, and a represents the deceleration during deceleration, which is measured by the deceleration sensor.

[0067] S2, determine whether the rising fitting line and the falling fitting line are fitted successfully, if so, execute S3, otherwise, execute S1.

[0068] S3. Based on the intersection of the ascending fitting line and the descending fitting line, curve fitting is performed on the ascending fitting line and the descending fitting line to obtain a road adhesion coefficient-tire slip rate curve corresponding to the current road surface and extract an estimated value of the road adhesion coefficient.

[0069] After the rising fitting line and the falling fitting line are successfully fitted, for example, Figure 3 As shown, the circles are several collected (μ1, s1) sample values, which are fitted into a straight line L1, and the triangles are several collected (μ2, s2) sample values, which are fitted into a straight line L2.

[0070] Combination Figure 4 ,First, select the P point and Q point with higher confidence, which meet the preset conditions, which are expressed as:

[0071]

[0072] In the formula, s P 、s Q represents the coordinates of point P and point Q on the s-axis, represents the maximum value of μ1 in the (μ1, s1) sample, is the minimum value of s2 in the (μ2, s2) sample, and ε and δ are preset thresholds.

[0073] Secondly, according to point P, point Q and the intersection point O of L1 and L2, a second-order Bezier curve is used for fitting to obtain a road adhesion coefficient-tire slip rate curve corresponding to the current road surface.

[0074] Here, this embodiment does not limit the curve fitting method, and may also be based on other curve fitting methods or fitting methods based on deep learning.

[0075] Finally, combined Figure 5 , take the extreme point of the fitted μ-s curve as μ max The estimated value of the road adhesion coefficient.

[0076] S3. Obtain the relative speed of the autonomous driving vehicle and the target obstacle, and determine the automatic emergency braking threshold in combination with the estimated road adhesion coefficient; the automatic emergency braking threshold is expressed as:

[0077]

[0078] Where V L represents the relative speed between the autonomous driving vehicle and the target obstacle, μ max represents the estimated value of the road adhesion coefficient, T0 represents the response time of the braking system, According to μ max Deceleration speed V L Reduced to 0 time.

[0079] In actual driving, the maximum deceleration provided by the braking system does not represent the maximum deceleration that the vehicle can achieve during actual deceleration. max <|a max |, the actual deceleration will not reach a max ,Therefore, if only the maximum deceleration that can be achieved during the actual deceleration of the vehicle is considered in the ,threshold determination process, there is a greater safety risk.

[0080] S4. Execute automatic emergency braking based on the automatic emergency braking threshold and the collision time.

[0081] Specifically, when the collision time TTC is lower than the automatic emergency braking threshold, emergency braking is performed.

[0082] Here, calculating the collision time TTC based on the relative distance and relative speed between the autonomous driving vehicle and the target object is a conventional technical means in this field and will not be repeated here.

[0083] Embodiment 2

[0084] This embodiment discloses an automatic emergency braking control system based on road adhesion coefficient estimation, including:

[0085] The fitting module is configured to: obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in an acceleration phase or a starting phase and fit them to generate an ascending fitting line; obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in a deceleration phase and fit them to obtain a descending fitting line;

[0086] The road adhesion coefficient estimation module is configured to: perform curve fitting on the ascending fitting line and the descending fitting line based on the intersection of the ascending fitting line and the descending fitting line, obtain a road adhesion coefficient-tire slip rate curve corresponding to the current road surface, and extract an estimated value of the road adhesion coefficient;

[0087] The automatic emergency braking module is configured to obtain the relative speed of the autonomous driving vehicle and the target obstacle, determine the automatic emergency braking threshold in combination with the estimated value of the road adhesion coefficient, and perform automatic emergency braking based on the automatic emergency braking threshold and the collision time.

[0088] It should be noted that the above-mentioned fitting module, road adhesion coefficient estimation module and automatic emergency braking module correspond to the steps in Embodiment 1, and the examples and application scenarios implemented by the above-mentioned modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned Embodiment 1. It should be noted that the above-mentioned modules, as part of the system, can be executed in a computer system such as a set of computer executable instructions.

[0089] Embodiment 3

[0090] Embodiment 3 of the present invention provides an electronic device, including a memory and a processor, and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps of the automatic emergency braking control method based on road adhesion coefficient estimation are completed.

[0091] Embodiment 4

[0092] Embodiment 4 of the present invention provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the steps of the above-mentioned automatic emergency braking control method based on road adhesion coefficient estimation are completed.

[0093] Embodiment 5

[0094] Embodiment 5 of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned automatic emergency braking control method based on road adhesion coefficient estimation.

[0095] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0096] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing device, and a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1The steps for the functions specified in one or more boxes.

[0098] The description of each embodiment in the above embodiments has different emphases. For parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An automatic emergency braking control method based on road adhesion coefficient estimation, characterized in that: include: Obtain and fit multiple road adhesion coefficients and tire slip rates of the autonomous vehicle during the acceleration or starting phase to generate an ascending fitting line; Obtain and fit multiple road adhesion coefficients and tire slip rates of the autonomous vehicle during the deceleration phase to obtain a descending fitting line; Based on the intersection of the ascending fitting line and the descending fitting line, curve fitting is performed on the ascending fitting line and the descending fitting line to obtain a road adhesion coefficient-tire slip rate curve corresponding to the current road surface and extract an estimated value of the road adhesion coefficient; The relative speed of the autonomous driving vehicle and the target obstacle is obtained, and the automatic emergency braking threshold is determined in combination with the estimated value of the road adhesion coefficient, so as to perform automatic emergency braking based on the automatic emergency braking threshold and the collision time.

2. The automatic emergency braking control method based on road adhesion coefficient estimation according to claim 1, characterized in that: Obtaining the road adhesion coefficient and tire slip rate of an autonomous vehicle during the acceleration or starting phase includes: Obtain the acceleration of the autonomous vehicle during the acceleration or starting phase, and determine the road adhesion coefficient based on the acceleration and gravity acceleration; The speed, angular velocity of the driving wheels and the rolling radius of the tires of the autonomous vehicle during the acceleration or starting phase are obtained to determine the tire slip rate.

3. The automatic emergency braking control method based on road adhesion coefficient estimation according to claim 1, characterized in that: Obtaining the road adhesion coefficient and tire slip rate of the autonomous vehicle during the deceleration phase includes: Obtain the deceleration of the autonomous vehicle during the deceleration phase, and determine the road adhesion coefficient based on the deceleration and gravity acceleration; The speed of the autonomous vehicle during the deceleration phase, the angular velocity of the braking wheel, and the tire rolling radius are obtained to determine the tire slip rate.

4. The automatic emergency braking control method based on road adhesion coefficient estimation according to claim 1, characterized in that: The curve fitting of the ascending fit line and the descending fit line based on the intersection of the ascending fit line and the descending fit line is specifically as follows: a plurality of fitting points are determined on the ascending fit line and the descending fit line according to the confidence level, and the plurality of fitting points and the intersection of the ascending fit line and the descending fit line are fitted by a second-order Bezier curve.

5. The automatic emergency braking control method based on road adhesion coefficient estimation according to claim 1, characterized in that: The automatic emergency braking threshold is expressed as: Where V L represents the relative speed between the autonomous driving vehicle and the target obstacle, μ max represents the estimated value of the road adhesion coefficient, and T0 represents the response time of the braking system.

6. The automatic emergency braking control method based on road adhesion coefficient estimation according to claim 1, characterized in that: Based on the automatic emergency braking threshold and the collision time, the automatic emergency braking is performed specifically as follows: when the collision time is lower than the automatic emergency braking threshold, emergency braking is performed.

7. Automatic emergency braking control system based on road adhesion coefficient estimation, characterized in that: include: The fitting module is configured to: obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in an acceleration phase or a starting phase and fit them to generate an ascending fitting line; obtain multiple road adhesion coefficients and tire slip rates of the autonomous driving vehicle in a deceleration phase and fit them to obtain a descending fitting line; The road adhesion coefficient estimation module is configured to: perform curve fitting on the ascending fitting line and the descending fitting line based on the intersection of the ascending fitting line and the descending fitting line, obtain a road adhesion coefficient-tire slip rate curve corresponding to the current road surface, and extract an estimated value of the road adhesion coefficient; The automatic emergency braking module is configured to obtain the relative speed of the autonomous driving vehicle and the target obstacle, determine the automatic emergency braking threshold in combination with the estimated value of the road adhesion coefficient, and perform automatic emergency braking based on the automatic emergency braking threshold and the collision time.

8. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the automatic emergency braking control method based on road adhesion coefficient estimation according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the automatic emergency braking control method based on road adhesion coefficient estimation as described in any one of claims 1-6 are implemented.

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