Vehicle control method and device, vehicle and storage medium

Abstract

The invention discloses a vehicle control method and device, a vehicle and a readable storage medium, and the method comprises the steps: obtaining a linear distance between a reflection point of a radar signal of a radar at a collection time point and the vehicle for each collection time point of a plurality of collection time points in a vehicle driving process, and taking the linear distance as a measurement distance corresponding to the collection time point; determining a change rule of a relative distance between the radar and the reflection point according to the measurement angle and the measurement distance of the radar at each acquisition time point; according to a relative distance change rule, determining a road surface recognition result of the own vehicle lane; and controlling the vehicle according to the road surface recognition result. According to the method and the device, when the road conditions in front of the lane of the vehicle are different, the change rule of the relative distance between the radar and the reflection point is also different, so that the road conditions in front of the lane of the vehicle can be accurately obtained according to the change rule of the relative distance, and a road identification result with relatively high accuracy is obtained.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and more specifically, to a vehicle control method, device, vehicle and computer-readable storage medium. Background Art

[0002] At present, there are situations in which vehicles do not accurately recognize the road surface ahead of their own lane during driving. For example, a continuous downhill road ahead is mistakenly identified as a deep pothole, or a deep pothole is mistakenly identified as a downhill road. This causes safety hazards during vehicle driving and poor safety during vehicle driving. Summary of the invention

[0003] The present application proposes a vehicle control method, device, vehicle and computer-readable storage medium to improve the above-mentioned defects.

[0004] In a first aspect, an embodiment of the present application provides a vehicle control method for a vehicle equipped with a radar, comprising: for each of a plurality of acquisition time points during vehicle driving, obtaining the straight-line distance between the reflection point of the radar signal of the radar at the acquisition time point and the vehicle as the measurement distance corresponding to the acquisition time point; the reflection point is a road surface point in front of the vehicle in the self-vehicle lane in which the vehicle is traveling and reflects the radar signal; along the vehicle driving direction, the reflection point corresponding to the latter of any two adjacent acquisition time points is in front of the reflection point corresponding to the former; according to the measurement angle and measurement distance of the radar at each acquisition time point, determining the relative distance change law between the radar and the reflection point; according to the relative distance change law, determining the road surface recognition result of the self-vehicle lane; the road surface recognition result is used to indicate whether there is a road surface depression in front of the vehicle in the self-vehicle lane; and controlling the vehicle according to the road surface recognition result.

[0005] In a second aspect, an embodiment of the present application further provides a vehicle control device for a vehicle equipped with a radar, comprising: an acquisition module, for acquiring, for each of a plurality of acquisition time points during the driving process of the vehicle, a straight-line distance between a reflection point of a radar signal of the radar at the acquisition time point and the vehicle, as the measurement distance corresponding to the acquisition time point; the reflection point is a road surface point in front of the vehicle in the self-vehicle lane in which the vehicle is traveling and reflects the radar signal; along the driving direction of the vehicle, the reflection point corresponding to the latter of any two adjacent acquisition time points is in front of the reflection point corresponding to the previous acquisition time point; a first determination module, for determining a relative distance change law between the radar and the reflection point according to the measurement angle and measurement distance of the radar at each acquisition time point; a second determination module, for determining a road surface recognition result of the self-vehicle lane according to the relative distance change law; the road surface recognition result is used to indicate whether there is a road surface depression in front of the vehicle in the self-vehicle lane; a control module, for controlling the vehicle according to the road surface recognition result.

[0006] In a third aspect, an embodiment of the present application further provides a vehicle, characterized in that it comprises: one or more processors; a memory; one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are configured to execute the above method.

[0007] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores a program code executable by a processor, and when the program code is executed by the processor, the processor executes the above method.

[0008] The present application provides a vehicle control method, device, vehicle and computer-readable storage medium. In the present application, for each of multiple acquisition time points during vehicle driving, the straight-line distance between the reflection point of the radar signal of the radar and the vehicle is obtained as the measurement distance corresponding to the acquisition time point; the reflection point is a road surface point located in front of the vehicle in the self-vehicle lane where the vehicle is driving and reflects the radar signal; the reflection point corresponding to the latter acquisition time point of any two adjacent acquisition time points is in front of the reflection point corresponding to the former acquisition time point, so that the measurement distances obtained at multiple acquisition time points are orderly in the vehicle driving direction. In this way, when the road surface conditions in front of the self-vehicle lane are different, the relative distance change law between the radar and the reflection point is also different. Therefore, according to the relative distance change law between the radar and the reflection point, the road surface conditions in front of the self-vehicle lane can be accurately obtained, and a road surface recognition result with a high accuracy can be obtained. Then, the vehicle is controlled according to the road surface recognition result, which can avoid the vehicle from being damaged when an accurate road surface recognition result cannot be obtained, thereby improving the safety of the vehicle driving process.

[0009] Other features and advantages of the embodiments of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the embodiments of the present application. The purposes and other advantages of the embodiments of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic diagram of a vehicle hardware environment suitable for an embodiment of the present application is shown.

[0012] Figure 2 A flow chart of a vehicle control method proposed according to an embodiment of the present application is shown.

[0013] Figure 3 A schematic diagram showing a distance variation rule in an embodiment of the present application is shown.

[0014] Figure 4 A schematic diagram showing another distance variation rule in an embodiment of the present application is shown.

[0015] Figure 5 Shows Figure 3 The road surface recognition results corresponding to the distance change law shown.

[0016] Figure 6 Shows Figure 4 The road surface recognition results corresponding to the distance change law shown.

[0017] Figure 7 A flow chart of a vehicle control method proposed according to another embodiment of the present application is shown.

[0018] Figure 8 A schematic diagram showing the application process of a vehicle control method in an embodiment of the present application is shown.

[0019] Fig. 9 A structural block diagram of a vehicle control device proposed in one embodiment of the present application is shown. DETAILED DESCRIPTION

[0020] In order to make those skilled in the art better understand the present application scheme, the technical scheme in the present application embodiment will be clearly and completely described below in conjunction with the drawings in the present application embodiment. Obviously, the described embodiment is only a part of the present application embodiment, rather than all the embodiments. The components of the present application embodiment usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0021] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0022] See also Figure 1 , Figure 1 A schematic diagram of a vehicle hardware environment suitable for an embodiment of the present application is shown, where a vehicle 100 includes a radar 110 , a processor 111 , and a memory 112 .

[0023] Radar 110 is used to collect the straight-line distance between the vehicle and the road in front of the vehicle during driving. The radar can be set at any position on the vehicle that can be used to detect the road in front of the vehicle and is at a certain height from the road, such as near the hood of the vehicle, on the top of the vehicle, or at the front of the vehicle.

[0024] The processor 111 may be a microcontroller unit (MCU) having a built-in memory 112 . The memory 112 stores a program that can execute the contents of the following embodiments, and the processor 111 may execute the program stored in the memory 112 .

[0025] The processor 111 may include one or more processors. The processor 111 uses various interfaces and lines to connect various parts of the entire vehicle 100, and executes various functions of the vehicle 100 and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 112, and calling data stored in the memory 112.

[0026] The memory 112 may include a random access memory (RAM) or a read-only memory (ROM). The memory 112 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 112 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the following various method embodiments, etc.

[0027] See also Figure 2 , Figure 2 A flow chart of a vehicle control method proposed in one embodiment of the present application is shown, which is used for a vehicle equipped with a radar, and the method includes:

[0028] S101. For each of a plurality of collection time points during a vehicle driving process, obtain a straight-line distance between a reflection point of a radar signal of a radar and the vehicle at the collection time point as a measured distance corresponding to the collection time point.

[0029] Among them, the reflection point is a point on the road surface that is located in front of the vehicle in the vehicle lane and reflects the radar signal; along the vehicle's driving direction, the reflection point corresponding to the latter of any two adjacent acquisition time points is in front of the reflection point corresponding to the previous acquisition time point.

[0030] In some embodiments, the measurement angles of each acquisition time point may be the same, or the measurement angles of each acquisition time point may be different. In the case where the measurement angles of each acquisition time point are different, the difference in the measurement angles needs to satisfy that when measuring according to the measurement angle, the reflection point corresponding to the latter of any two adjacent acquisition time points is in front of the reflection point corresponding to the former acquisition time point, thereby ensuring that the multiple reflection points are distributed in sequence along the extension direction of the vehicle lane in the vehicle driving direction according to the sequence of the corresponding acquisition time points, so that when determining the relative distance change law according to the measured distance at each acquisition time point, the relative distance change law obtained can accurately indicate the change law of the road surface of the vehicle lane in front of the vehicle in the vehicle driving direction.

[0031] Among them, the vehicle can be an electric car or a fuel vehicle, and can be a sedan, SUV, bus, truck, etc. The radar installed on the vehicle can be a millimeter wave radar, laser radar, ultrasonic radar, etc. The higher the setting height of the radar, the greater the measurement distance obtained.

[0032] In some implementations, the time interval between any two adjacent collection time points among the multiple collection time points is the same, or the vehicle travel distance interval between any two adjacent collection time points among the multiple collection time points is the same.

[0033] Among them, the number of multiple collection time points can be set according to needs, such as 10 or 20, etc.; the time interval and driving distance interval can be set according to needs, and are not limited here, for example, the time interval is 1s or 2s, and the driving distance interval is 5m or 10m.

[0034] During vehicle driving, the vehicle's radar transmits a radar signal at every specified time interval or at every specified driving distance interval. The vehicle then receives the echo signal of the radar signal (that is, the radar signal is received and reflected by a road surface point on the road surface of the vehicle's lane, with the reflected radar signal serving as an echo signal and the road surface point that receives the radar signal serving as a reflection point). Based on the time interval between the radar signal and the echo signal, the straight-line distance at the collection time point is calculated as the measured distance at the collection time point.

[0035] S102: Determine a change rule of the relative distance between the radar and the reflection point according to the measurement angle and the measurement distance of the radar at each acquisition time point.

[0036] Among them, the relative distance change law between the radar and the reflection point can be at least one of the distance change law of the measured distance between the radar and the reflection point, the vertical distance change law of the measured distance in the vertical direction, and the horizontal distance change law of the measured distance in the horizontal direction.

[0037] In some implementations, S102 includes: determining a vertical distance variation rule of the measured distance in the vertical direction according to the measurement angle and the measurement distance of the radar at each acquisition time point as a relative distance variation rule between the radar and the reflection point.

[0038] The vertical distance variation law of the measured distance in the vertical direction can most directly reflect the road condition in front of the vehicle in the own lane. For example, if the vertical distance suddenly increases, it is considered that there is a sudden change in the height of the road in front of the vehicle in the own lane (for example, a downhill, a bulge, a depression, etc.). Among them, the vertical distance variation law of the measured distance in the vertical direction can be the variation law of the vertical distance between the vehicle's radar and the reflection point, or the variation law of the vertical distance between the position where the vehicle's tire contacts the road surface and the reflection point.

[0039] When the vertical distance variation rule of the measured distance in the vertical direction is the former, the vertical distance H1 between the radar of the vehicle and the reflection point is =L×sinα, where L is the measured distance and α is the measurement angle of the radar.

[0040] When the vertical distance variation law of the measured distance in the vertical direction is the latter, the vertical distance H2 between the position where the vehicle tire contacts the road surface and the reflection point is |L×sinα-h|, where h is the setting height of the radar.

[0041] Even when the measurement angle of the radar is different at each acquisition time point, the measurement distance L will change with the change of the measurement distance α and the position of the reflection point. Since the multiple reflection points are distributed in sequence along the extension direction of the vehicle driving direction on the self-vehicle lane according to the sequence of the corresponding acquisition time points, that is, the vertical distances at multiple time points are orderly distributed on the self-vehicle lane according to the acquisition sequence, the change of the measurement distance α affects the orderliness of the vertical distance, so that the vertical distance change law of the measurement distance in the vertical direction is determined according to the vertical distance at each acquisition time point. As the relative distance change law between the radar and the reflection point, it can reflect the position change of the reflection point in front of the vehicle on the self-vehicle lane, so that the road surface recognition result of the self-vehicle lane in front of the vehicle can be determined according to the relative distance change law.

[0042] Taking the vertical distance change law of the measured distance in the vertical direction as an example, the vertical distance change law between the vehicle's radar and the reflection point, the vertical distance at the acquisition time point t1 is H11, the vertical distance of the radar at the acquisition time point t2 is H12, and the vertical distance of the radar at the acquisition time point t3 is H13. If H12 is greater than H11 and the difference between H12 and H11 is greater than the first distance difference threshold, it is considered that the vertical distance has changed suddenly (suddenly increased). If H13 is equal to H12, it is considered that the vertical distance ahead has not changed. The vertical distance change law is that it suddenly increases first and then remains unchanged.

[0043] Since the road cannot be completely flat, it is common to have small vertical distance changes. When H13∈[H12-△H, H12+△H], the vertical distance can also be considered to remain unchanged, where △H is the error threshold of the vertical distance, which can be set according to needs.

[0044] If H12 is greater than H11 and the difference between H12 and H11 is greater than the first distance difference threshold, it is considered that the vertical distance has changed suddenly (suddenly increased); if H13 is greater than H12+△H, it is considered that the vertical distance ahead has decreased. The vertical distance change pattern is that it suddenly increases first and then decreases.

[0045] Among them, the first distance difference threshold can be set according to needs. For example, when the road depression has no impact on the vehicle, that is, the vehicle can drive in and out without causing damage to the chassis or body, the first distance difference threshold is set to be larger and △H is set to be larger to avoid emergency braking of the vehicle in this situation.

[0046] In some other embodiments, if the measurement angle of the radar at each acquisition time point is the same, the distance change law of the measured distance or the horizontal distance change law of the measured distance in the horizontal direction is determined according to the measurement distance of the radar at each acquisition time point as the relative distance change law between the radar and the reflection point.

[0047] When the measurement angle of the radar at each acquisition time point is different, the distance change law of the measured distance and the horizontal distance change law of the measured distance in the horizontal direction are difficult to accurately reflect the road condition in front of the vehicle in the ego lane. For example, a sudden increase or decrease in the horizontal distance may be caused by a change in the measurement angle of the radar, not a sudden change in the road surface height. Therefore, the distance change law of the measured distance and the horizontal distance change law of the measured distance in the horizontal direction cannot intuitively reflect the road condition in front of the vehicle in the ego lane.

[0048] However, when the radar's measurement angle at each acquisition time point is the same, the vertical distance variation law of the measured distance in the vertical direction and the horizontal distance variation law of the measured distance in the horizontal direction can also intuitively reflect the road conditions in front of the vehicle in the ego lane. For example, if the measured distance suddenly increases, it is considered that there is a sudden change in height of the road surface in front of the vehicle in the ego lane (for example, a downhill slope, a depression, etc.), and if the horizontal measured distance suddenly decreases, it is considered that there is a sudden change in height of the road surface in front of the vehicle in the ego lane (for example, an uphill slope, a bulge, etc.). Among them, the vertical distance variation law of the measured distance in the vertical direction can be the variation law of the vertical distance between the vehicle's radar and the reflection point, or it can be the variation law of the vertical distance between the position where the vehicle's tire contacts the road surface and the reflection point.

[0049] Among them, the distance variation law of the measured distance is the variation law of the straight-line distance between the vehicle's radar and the reflection point, and the vertical distance variation law of the measured distance in the horizontal direction is the variation law of the horizontal distance between the vehicle's radar and the reflection point, and the horizontal distance S=L×cosα.

[0050] Since the vertical distance H1 = L×sinα and H2 = |L×sinα-h|, α remains unchanged, H1 and H2 are only related to L. It can be seen that the distance change law of the measured distance is the same as the vertical distance change law in the vertical direction. The distance change law can also most intuitively reflect the road conditions in front of the vehicle.

[0051] Taking the acquisition time points t1, t2 and t3 as examples, the straight-line distance at the acquisition time point t1 is L1, the straight-line distance of the radar at the acquisition time point t2 is L2, and the straight-line distance of the radar at the acquisition time point t3 is L3. Similarly, if L2 is greater than L1 and the difference between L2 and L1 is greater than the second distance difference threshold, it is considered that the straight-line distance has changed suddenly (suddenly increased). If L3 is equal to L2, it is considered that the straight-line distance ahead has not changed. The distance change rule is as follows: Figure 3 As shown, it suddenly becomes larger and then remains unchanged.

[0052] Similarly, since the road cannot be completely flat, it is common for small ups and downs to cause changes in the straight-line distance. When L3∈[L2-△L, L2+△L], the straight-line distance can also be considered to remain unchanged, where △L is the error threshold of the straight-line distance, which can be set according to needs.

[0053] If L2 is greater than L1 and the difference between L2 and L1 is greater than the second distance difference threshold, it is considered that the straight-line distance has changed suddenly (suddenly increased). If L3 is greater than L2+△L, it is considered that the straight-line distance ahead has decreased. The change rule of the straight-line distance is as follows: Figure 4 As shown, it suddenly becomes larger and then becomes smaller.

[0054] Similarly, horizontal distance S = L × cosα, α remains unchanged, and S is only related to L. It can be seen that the horizontal distance change law of the measured distance in the horizontal direction is the same as the distance change law, and the horizontal distance change law can also most intuitively reflect the road conditions in front of the vehicle.

[0055] S103: Determine the road surface recognition result of the own vehicle lane according to the relative distance change rule.

[0056] The road surface recognition result is used to indicate whether there is a road depression in front of the vehicle in the own vehicle lane.

[0057] In some embodiments, when the road surface recognition result indicates that there is no road depression in front of the vehicle in the own lane, the specific road conditions in front of the vehicle in the own lane can be further indicated, such as a flat road surface, a raised road surface, a downhill road surface, etc.

[0058] In some implementations, S103 includes: determining a road surface height feature corresponding to a relative distance variation rule; and obtaining a road surface recognition result corresponding to the road surface height feature as a road surface recognition result of the vehicle lane.

[0059] Among them, the road surface height feature refers to the shape of the lane surface of the vehicle lane. The shape of the lane surface can be flat, raised, sunken, downhill and uphill, etc., which can be obtained by analyzing multiple sample road surfaces. Taking the measurement angle of the radar at each acquisition time point as the same and the vertical distance as H1 as an example, the relative distance change law is that the vertical distance change law of the measured distance in the vertical direction is unchanged. At this time, the road surface height feature is flat road surface. For example, the relative distance change law is that the vertical distance change law of the measured distance in the vertical direction is that the vertical distance first decreases and then increases, then the road surface height feature is raised road surface. For example, the relative distance change law is that the vertical distance change law of the measured distance in the vertical direction is that the vertical distance first increases and then decreases, then the road surface height feature is sunken road surface. For example, the relative distance change law is that the vertical distance change law of the measured distance in the vertical direction is that the vertical distance first increases and then remains unchanged, then the road surface height feature is downhill.

[0060] After determining the road surface height feature, the road surface recognition result can be determined based on the specific road surface height feature. For example, if the road surface height feature is an uphill road surface, the road surface recognition result is that there is no road surface depression in front of the vehicle in the own lane. For another example, if the road surface height feature is a road surface depression, the road surface recognition result is that there is a road surface depression in front of the vehicle in the own lane.

[0061] Among them, according to Figure 3 The road surface recognition result determined by the corresponding distance change law is as follows Figure 5 As shown, the road surface recognition result shows that there is a slope in front of the vehicle; according to Figure 4The road surface recognition result determined by the corresponding distance change law is as follows Figure 6 As shown in the figure, the road surface recognition result shows that there is a road depression in front of the vehicle. Figure 5 and Figure 6 The black triangles in the figure are reflection points.

[0062] S104: Control the vehicle according to the road surface recognition result.

[0063] In some embodiments, the identification represented by the road surface recognition result can be displayed on the human-machine interface (HMI) of the vehicle, for example, a concave road surface is a pit, a convex road surface is a convex hull, etc., and the user controls the vehicle according to the identification displayed on the human-machine interface.

[0064] In some implementations, if the road surface recognition result of the vehicle's lane is that the road surface in front of the vehicle is flat, it may not be displayed on the human-machine interface.

[0065] In this embodiment, for each of the multiple acquisition time points during the vehicle's driving process, the straight-line distance between the reflection point of the radar signal of the radar and the vehicle is obtained as the measurement distance corresponding to the acquisition time point; the reflection point is a road surface point located in front of the vehicle in the self-vehicle lane where the vehicle is traveling and reflects the radar signal; the reflection point corresponding to the latter of any two adjacent acquisition time points is in front of the reflection point corresponding to the former, so that the measurement distances obtained at the multiple acquisition time points are orderly in the vehicle's driving direction. In this way, when the road surface conditions in front of the self-vehicle lane are different, the relative distance change law between the radar and the reflection point is also different. Therefore, according to the relative distance change law between the radar and the reflection point, the road surface conditions in front of the self-vehicle lane can be accurately obtained, and a road surface recognition result with a higher accuracy can be obtained. Then, the vehicle is controlled according to the road surface recognition result, which can avoid the vehicle being damaged when an accurate road surface recognition result cannot be obtained, thereby improving the safety of the vehicle driving process.

[0066] In one embodiment, if Figure 7 As shown, S104 includes:

[0067] S201. If the road surface recognition result shows that there is a road depression in front of the vehicle in the own vehicle lane, obtain the shortest distance between the vehicle and the road depression.

[0068] In some embodiments, the method for obtaining the shortest distance between a vehicle and a road depression includes: obtaining the horizontal distance of a collection time point corresponding to a sudden change in the vertical distance among multiple collection time points and the driving distance between the collection time point and the last collection time point during the driving process of the vehicle; and calculating the difference between the horizontal distance and the driving distance as the shortest distance between the vehicle and the road depression.

[0069] S202: Determine the driving time for the vehicle to reach the road depression according to the shortest distance and the driving speed of the vehicle.

[0070] The driving speed may be the speed of the vehicle at the last acquisition time point, or may be a speed predicted based on the acceleration of the vehicle and the speed at the last acquisition time point.

[0071] S203: Determine the road surface risk level at the road surface depression according to the comparison result between the travel time and the time threshold.

[0072] The time threshold is the sum of the vehicle braking time and the user's reaction time.

[0073] If the driving time is greater than the time threshold, the road surface risk level at the road depression is determined to be the first risk level; if the driving time is not greater than the time threshold, the road surface risk level at the road depression is determined to be the second risk level. Among them, the risk level of the second risk level is higher than the first risk level, that is, the risk of a vehicle driving into a depression at the second risk level is higher than the risk of a vehicle driving into a depression at the first risk level.

[0074] S204: Control the vehicle according to the road surface risk level at the road depression.

[0075] In some embodiments, S203 includes: if the road surface risk level at the road surface depression is the first risk level, establishing a road surface height dot matrix rendering map of the road surface depression according to the measurement angle and measurement distance of the radar at each acquisition time point; and controlling the vehicle to display the road surface height dot matrix rendering map.

[0076] Among them, taking 4D millimeter-wave radar as an example, the detection range of the radar is an area with a radial distance of 300 meters, a horizontal angle of ±75°, and a pitch angle of ±15°. Therefore, the measurement distance within a certain length range and a certain width range in front of the vehicle can be obtained. According to the measurement distance and the measurement distance, the road surface height within a certain length range and a certain width range in front of the vehicle can be obtained, and then a road surface height dot matrix rendering diagram can be drawn according to the road surface height.

[0077] In some embodiments, a road surface height dot matrix rendering diagram of a road surface depression is established based on the measurement angle and measurement distance of the radar at each acquisition time point, including: calculating the vertical distance between the reflection point and the target road surface at each acquisition time point based on the measurement angle, measurement distance and setting height of the radar at each acquisition time point; the target road surface at the acquisition time point refers to the road surface at the position of the vehicle on the vehicle lane at the acquisition time point; and drawing a road surface height dot matrix rendering diagram at the road surface depression based on the vertical distance between the reflection point and the target road surface of the vehicle at each acquisition time point.

[0078] Among them, the vertical distance between the reflection point and the target road surface of the vehicle is the aforementioned H1, and the value or color in each grid in the road height dot matrix rendering diagram represents the size of H1. For example, the darker the color, the larger H1 is.

[0079] In some embodiments, while the vehicle's human-machine interface displays a dot matrix rendering of the road height, an audio-visual reminder is given to park the vehicle in the face of danger. If a changeable lane is detected in the direction of the vehicle's travel, the changeable lane is displayed on the human-machine interface.

[0080] In some implementations, S203 includes: if the road surface risk level at the road surface depression is a second risk level, controlling the vehicle to stop; the risk level of the second risk level is higher than the first risk level.

[0081] When the road risk level is the second risk level, braking prompt information can also be output while controlling the vehicle to stop. The braking prompt information can be, for example, sound and light prompt information, such as voice prompt parking brake, lighting up the double flash lights, etc.

[0082] When the road surface risk level is the second risk level, it means that the risk level is high and there is a depression in the road surface ahead of the vehicle's lane. It is necessary to stop the vehicle to avoid the vehicle entering the depression. At this time, the vehicle is controlled to stop to avoid safety accidents caused by the vehicle entering the depression.

[0083] In some embodiments, after determining that the road surface risk level of a road surface depression is the first risk level and the second risk level, the risk of damage to the vehicle when entering or exiting the road surface depression can also be judged based on the chassis ground clearance and the road surface height, including whether the vehicle can drive out after entering the road surface depression and whether the chassis or body will be damaged.

[0084] If the chassis ground clearance is greater than the maximum value of the road depression H1, it is considered that the vehicle can drive out after entering the road depression and the chassis or body will not be damaged; if the chassis ground clearance is not greater than the maximum value of the road depression H1, it is considered that the vehicle has the risk of being unable to drive out of the road depression and / or the risk of damage to the chassis or body.

[0085] Furthermore, the vehicle's approach angle and departure angle can also be obtained, and the chassis ground clearance, approach angle and departure angle can be comprehensively used to determine whether the vehicle can drive out after entering a depression in the road, and whether the chassis or body will be damaged.

[0086] When it is determined that the vehicle can drive out of a depression in the road and the chassis or body will not be damaged, the user is prompted to slow down.

[0087] When the road surface risk level at the road depression is the second risk level and it is determined that the vehicle has a risk of being unable to drive out of the road depression and / or a risk of chassis or body being damaged, emergency braking is initiated.

[0088] When the road surface risk level at the road depression is the first risk level and it is determined that the vehicle has a risk of being unable to drive out of the road depression and / or a risk of chassis or body damage, the user is reminded by sound and light to perform risk avoidance operations.

[0089] In this embodiment, if the road surface recognition result is that there is a road depression in front of the vehicle in the own vehicle lane, the shortest distance between the vehicle and the road depression is obtained; the driving time of the vehicle to reach the road depression is calculated based on the shortest distance and the vehicle's driving speed; the road surface risk level of the road surface depression is determined based on the comparison result between the driving time and the time threshold; according to the road surface risk level of the road surface depression, the vehicle is controlled, and when there is a road surface depression in front of the vehicle in the own vehicle lane, the road surface risk level of the road surface depression is defined, and different risk avoidance strategies are adopted for different road surface risk levels, thereby achieving accurate risk avoidance while ensuring the user's driving experience.

[0090] like Figure 8 As shown, Figure 8 A schematic diagram of a vehicle control process is shown, which first obtains measured distances at multiple time points; determines the relative distance variation law based on the measured distances and measurement angles; then determines the road surface recognition result of the own vehicle lane based on the relative distance variation law; if the road surface recognition result is that there is a road depression in front of the vehicle in the own vehicle lane, determines the road surface risk level at the road surface depression; then, if the road surface risk level at the road surface depression is the first risk level, draws a road surface height dot matrix rendering map, controls the vehicle based on the road surface height dot matrix rendering map, and controls the vehicle to stop if the road surface risk level at the road surface depression is the second risk level.

[0091] See attached Fig. 9 , Fig. 9 The structure block diagram of a vehicle control device proposed in one embodiment of the present application is shown. For a vehicle equipped with a radar, the vehicle control device 900 includes:

[0092] The acquisition module 910 is used to acquire, for each of the multiple acquisition time points during the vehicle's driving process, a straight-line distance between a reflection point of a radar signal of the radar at the acquisition time point and the vehicle as a measurement distance corresponding to the acquisition time point; the reflection point is a road surface point in front of the vehicle in the vehicle lane in which the vehicle is traveling and reflects the radar signal; along the vehicle's driving direction, the reflection point corresponding to the latter of any two adjacent acquisition time points is in front of the reflection point corresponding to the former acquisition time point;

[0093] The first determination module 920 is used to determine the change rule of the relative distance between the radar and the reflection point according to the measurement angle and the measurement distance of the radar at each acquisition time point;

[0094] The second determination module 930 is used to determine the road surface recognition result of the own vehicle lane according to the relative distance change rule; the road surface recognition result is used to indicate whether there is a road surface depression in front of the vehicle in the own vehicle lane;

[0095] The control module 940 is used to control the vehicle according to the road surface recognition result.

[0096] Optionally, the first determination module 920 is further used to determine the vertical distance variation law of the measured distance in the vertical direction according to the measurement angle and measurement distance of the radar at each acquisition time point, as the relative distance variation law between the radar and the reflection point.

[0097] Optionally, the first determination module 920 is also used to determine the distance change law of the measured distance or the horizontal distance change law of the measured distance in the horizontal direction according to the measured distance of the radar at each acquisition time point if the measurement angle of the radar at each acquisition time point is the same, as the relative distance change law between the radar and the reflection point.

[0098] Optionally, the control module 940 is also used to obtain the shortest distance between the vehicle and the road depression if the road surface recognition result is that there is a road depression in front of the vehicle in the own lane; determine the driving time of the vehicle to reach the road depression based on the shortest distance and the vehicle's driving speed; determine the road surface risk level of the road surface depression based on the comparison result between the driving time and the time threshold; and control the vehicle according to the road surface risk level of the road surface depression.

[0099] Optionally, the control module 940 is also used to draw a road surface height dot matrix rendering diagram at the road surface depression if the road surface risk level at the road surface depression is the first risk level according to the measurement angle and measurement distance of the radar at each acquisition time point; and control the vehicle to display the road surface height dot matrix rendering diagram.

[0100] Optionally, the control module 940 is also used to calculate the vertical distance between the reflection point and the target road surface at each collection time point based on the measurement angle, measurement distance and setting height of the radar at each collection time point; the target road surface at the collection time point refers to the road surface at the position of the vehicle on the vehicle lane at the collection time point; based on the vertical distance between the reflection point and the target road surface at each collection time point, a dot matrix rendering of the road surface height at the road surface depression is drawn.

[0101] Optionally, the control module 940 is further configured to control the vehicle to stop if the road surface risk level at the road depression is a second risk level; the risk level of the second risk level is higher than the first risk level.

[0102] Optionally, the second determination module 930 is further used to determine the road surface height feature corresponding to the relative distance change rule; and obtain the road surface recognition result corresponding to the road surface height feature as the road surface recognition result of the vehicle lane.

[0103] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0104] In addition, each function in each embodiment of the present application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of software function module.

[0105] The present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the method in the above method embodiment.

[0106] The present application also provides a computer-readable storage medium, in which program code is stored. The program code can be called by a processor to execute the method described in the above method embodiment.

[0107] The computer readable storage medium can be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk, or a cluster of ROMs. Optionally, the computer readable storage medium includes a non-transitory computer-readable storage medium. The computer readable storage medium has storage space for program codes that execute any of the method steps in the above method. These program codes can be read from or written into one or more computer program products. The program code can be compressed, for example, in an appropriate form.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A vehicle control method, characterized in that: For vehicles equipped with radar, including: For each of the multiple collection time points during the driving process of the vehicle, the straight-line distance between the reflection point of the radar signal of the radar at the collection time point and the vehicle is obtained as the measurement distance corresponding to the collection time point; the reflection point is a road surface point in front of the vehicle in the self-vehicle lane in which the vehicle is traveling and reflects the radar signal; along the driving direction of the vehicle, the reflection point corresponding to the latter of any two adjacent collection time points is in front of the reflection point corresponding to the former collection time point; Determine a change rule of the relative distance between the radar and the reflection point according to the measurement angle and the measurement distance of the radar at each acquisition time point; Determine a road surface recognition result of the vehicle lane according to the relative distance change rule; the road surface recognition result is used to indicate whether there is a road surface depression in front of the vehicle in the vehicle lane; The vehicle is controlled according to the road surface recognition result.

2. The method according to claim 1, characterized in that Determining the change rule of the relative distance between the radar and the reflection point according to the measurement angle and the measurement distance of the radar at each acquisition time point includes: According to the measurement angle and the measurement distance of the radar at each of the acquisition time points, the vertical distance variation law of the measurement distance in the vertical direction is determined as the relative distance variation law between the radar and the reflection point.

3. The method according to claim 1, characterized in that Determining the change rule of the relative distance between the radar and the reflection point according to the measurement angle and the measurement distance of the radar at each acquisition time point includes: If the measurement angle of the radar at each collection time point is the same, the distance change law of the measured distance or the horizontal distance change law of the measured distance in the horizontal direction is determined according to the measurement distance of the radar at each collection time point as the relative distance change law between the radar and the reflection point.

4. The method according to any one of claims 1 to 3, characterized in that The step of controlling the vehicle according to the road surface recognition result includes: If the road surface recognition result indicates that there is a road surface depression in front of the vehicle in the own vehicle lane, obtaining the shortest distance between the vehicle and the road surface depression; Determining the driving time of the vehicle to reach the road depression according to the shortest distance and the driving speed of the vehicle; Determining a road surface risk level at the road surface depression according to a comparison result between the travel time and a time threshold; The vehicle is controlled according to a road surface risk level at the road surface depression.

5. The method according to claim 4, characterized in that The controlling the vehicle according to the road surface risk level of the road depression comprises: If the road surface risk level of the road surface depression is the first risk level, a road surface height dot matrix rendering diagram of the road surface depression is drawn according to the measurement angle and the measurement distance of the radar at each acquisition time point; The vehicle is controlled to display the road height dot matrix rendering image.

6. The method according to claim 5, characterized in that The step of drawing a road height dot matrix rendering diagram of the road depression according to the measurement angle and the measurement distance of the radar at each acquisition time point includes: Calculate the vertical distance between the reflection point and the target road surface at each acquisition time point according to the measurement angle and measurement distance of the radar at each acquisition time point and the setting height of the radar; the target road surface at the acquisition time point refers to the road surface at the position of the vehicle on the vehicle lane at the acquisition time point; A road surface height dot matrix rendering diagram of the road surface depression is drawn according to the vertical distance between the reflection point and the target road surface at each acquisition time point.

7. The method according to claim 5, characterized in that The controlling the vehicle according to the road surface risk level of the road depression further comprises: If the road surface risk level at the road depression is a second risk level, the vehicle is controlled to stop; the risk level of the second risk level is higher than the first risk level.

8. The method according to claim 1, characterized in that Determining the road surface recognition result of the vehicle lane according to the relative distance change rule includes: Determine the road surface height characteristics corresponding to the relative distance variation law; A road surface recognition result corresponding to the road surface height feature is obtained as the road surface recognition result of the own vehicle lane.

9. A vehicle control device, characterized in that: For vehicles equipped with radar, including: an acquisition module, for acquiring, for each of a plurality of acquisition time points during the driving process of the vehicle, a straight-line distance between a reflection point of a radar signal of the radar at the acquisition time point and the vehicle as a measurement distance corresponding to the acquisition time point; the reflection point is a road surface point in front of the vehicle in the self-vehicle lane in which the vehicle is traveling and reflects the radar signal; along the driving direction of the vehicle, the reflection point corresponding to the latter of any two adjacent acquisition time points is in front of the reflection point corresponding to the former acquisition time point; A first determination module is used to determine a change rule of the relative distance between the radar and the reflection point according to the measurement angle and the measurement distance of the radar at each acquisition time point; A second determination module is used to determine a road surface recognition result of the vehicle lane according to the relative distance change rule; the road surface recognition result is used to indicate whether there is a road surface depression in front of the vehicle in the vehicle lane; A control module is used to control the vehicle according to the road surface recognition result.

10. A vehicle, characterized in that: include: one or more processors; Memory; One or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are configured to execute the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program code executable by a processor, and when the program code is executed by the processor, the processor executes the method according to any one of claims 1 to 8.

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