Method and device for determining rugged road type and related equipment

Abstract

The invention discloses a method and device for determining a rugged road type and related equipment, and relates to the technical field of vehicles. The method comprises the steps that under the condition that the vehicle runs on a target road, multiple ground clearances detected by the vehicle are obtained, and the multiple ground clearances are the ground clearances detected by radars below outer rearview mirrors of the vehicle in multiple periods; according to the plurality of terrain clearances, calculating height variance values of the vehicle in the plurality of periods; in a plurality of preset road surface rugged types, the road surface rugged type corresponding to the height variance value is determined as the road surface rugged type of the target road, and different road surface rugged types correspond to different variance intervals. According to the embodiment of the invention, the rugged road detection of the low-end vehicle can be met.

Description

Technical Field

[0001] The present application belongs to the field of vehicle technology, and in particular, relates to a method and device for determining the type of road roughness, and related equipment. Background Art

[0002] When a vehicle is driving on a rough road, it will cause bumps and shakes, affecting the stability of the vehicle and increasing the risk of rollover or loss of control. In order to ensure smooth and safe driving, the vehicle's suspension system and driving mode are generally adjusted by identifying the roughness of the road. However, the hardware computing power and storage capacity of low-end vehicles are currently limited, and it is impossible to detect the roughness of the road. Summary of the invention

[0003] The embodiments of the present application provide a method, device and related equipment for determining the type of road roughness, which can meet the requirements of road roughness detection for low-end vehicles.

[0004] In a first aspect, an embodiment of the present application provides a method for determining a road roughness type, the method comprising:

[0005] When the vehicle is traveling on a target road, obtaining a plurality of ground clearances detected by the vehicle, wherein the plurality of ground clearances are ground clearances detected by a radar below an exterior rearview mirror of the vehicle in a plurality of cycles;

[0006] Calculating, according to the plurality of ground clearance heights, a height variance value of the vehicle in the plurality of cycles;

[0007] Among the preset multiple road surface roughness types, the road surface roughness type corresponding to the height variance value is determined as the road surface roughness type of the target road, and different road surface roughness types correspond to different variance intervals.

[0008] In a second aspect, an embodiment of the present application provides a device for determining a road roughness type, the device comprising:

[0009] an acquisition module, configured to acquire, when the vehicle is traveling on a target road, a plurality of ground clearances detected by the vehicle, the plurality of ground clearances being ground clearances detected by a radar below an exterior rearview mirror of the vehicle in a plurality of cycles;

[0010] A calculation module, configured to calculate a height variance value of the vehicle within the multiple periods according to the multiple ground clearance heights;

[0011] The determination module is used to determine the road surface roughness type corresponding to the height variance value as the road surface roughness type of the target road from among a plurality of preset road surface roughness types, and different road surface roughness types correspond to different variance intervals.

[0012] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the method for determining the type of rough road as described in any one of the above items is implemented.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the method for determining the type of road roughness as described in any one of the above items is implemented.

[0014] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining the type of road roughness as described in any one of the above items.

[0015] In a sixth aspect, an embodiment of the present application provides a vehicle, comprising at least one of the following:

[0016] Means for determining the type of road roughness as described above;

[0017] Electronic devices as described above;

[0018] The computer readable storage medium as described above;

[0019] A computer program product as described above.

[0020] The method, device and related equipment for determining the road roughness type of the embodiment of the present application can obtain multiple ground clearance heights detected by the vehicle when the vehicle is traveling on the target road, and the multiple ground clearance heights are the ground clearance heights detected by the radar below the vehicle's exterior rearview mirror in multiple cycles; calculate the height variance values ​​of the vehicle in multiple cycles based on the multiple ground clearance heights; determine the road roughness type corresponding to the height variance value as the road roughness type of the target road among the preset multiple road roughness types, and different road roughness types correspond to different variance intervals. In this way, in the embodiment of the present application, the height variance value can be calculated based on the ground clearance height detected by the radar below the vehicle's exterior rearview mirror in multiple cycles. Since the variance intervals of different road roughness types are different, the road roughness type of the target road can be accurately identified. The present application has no requirements on the computing power and storage capacity of the vehicle hardware, and can meet the road roughness detection of low-end vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1 is a flowchart of a method for determining a road roughness type provided in an embodiment of the present application;

[0023] Figure 2 is a schematic diagram of the detection area of ​​the ultrasonic radar provided in an embodiment of the present application;

[0024] Figure 3 is a schematic diagram of the distances from the ground to the left and right rearview mirrors of a vehicle provided in an embodiment of the present application;

[0025] Figure 4 is a schematic diagram of the structure of a device for determining a road roughness type provided in an embodiment of the present application;

[0026] Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0028] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0029] When a vehicle is driving on a rough road, it will cause bumps and shakes, affecting the stability of the vehicle and increasing the risk of rollover or loss of control. In order to ensure smooth and safe driving, the vehicle's suspension system and driving mode are generally adjusted by identifying the roughness of the road. However, the hardware computing power and storage capacity of low-end vehicles are currently limited, and it is impossible to detect the roughness of the road.

[0030] In addition, since wading poses a potential threat to the safety of vehicles and passengers, in order to avoid problems such as water intrusion into the engine and electrical system short circuit caused by wading too deep, existing vehicles can improve driving safety through the on-board water depth detection system. The on-board water depth detection system uses an ultrasonic radar installed under the exterior rearview mirror to detect whether the current vehicle is wading.

[0031] In order to solve the technical problem that existing low-end vehicles are unable to detect road roughness, the radar of the vehicle-mounted water depth detection system in the embodiment of the present application can be reused to detect the ruggedness of non-water-wading roads in addition to detecting the water depth on the water surface (water-wading road surface).

[0032] In this regard, the embodiment of the present application provides a method, device and related equipment for determining the type of road roughness. The method for determining the type of road roughness provided by the embodiment of the present application is first introduced below.

[0033] Figure 1 FIG. 1 is a flow chart showing a method for determining a road roughness type according to an embodiment of the present application. Figure 1 As shown, a method for determining the type of road roughness may include the following steps S101 to S103:

[0034] S101. When a vehicle is traveling on a target road, obtaining a plurality of ground clearances detected by the vehicle, where the plurality of ground clearances are ground clearances detected by a radar below an exterior rearview mirror of the vehicle in a plurality of cycles;

[0035] S102, calculating the height variance values ​​of the vehicle in multiple cycles according to the multiple ground clearance heights;

[0036] S103. Determine the road surface roughness type corresponding to the height variance value among a plurality of preset road surface roughness types as the road surface roughness type of the target road, and different road surface roughness types correspond to different variance intervals.

[0037] The method for determining the road roughness type in the embodiment of the present application can obtain multiple ground clearance heights detected by the vehicle when the vehicle is traveling on the target road, and the multiple ground clearance heights are the ground clearance heights detected by the radar below the vehicle's exterior rearview mirror in multiple cycles; calculate the height variance values ​​of the vehicle in multiple cycles based on the multiple ground clearance heights; and determine the road roughness type corresponding to the height variance value as the road roughness type of the target road among the preset multiple road roughness types, and different road roughness types correspond to different variance intervals. In this way, in the embodiment of the present application, the height variance value can be calculated based on the ground clearance height detected by the radar below the vehicle's exterior rearview mirror in multiple cycles. Since the variance intervals of different road roughness types are different, the road roughness type of the target road can be accurately identified. The present application has no requirements on the computing power and storage capacity of the vehicle hardware, and can meet the road roughness detection of low-end vehicles.

[0038] In S101, the target road may be a road that needs to be detected for ruggedness.

[0039] The above-mentioned multiple ground clearances may be ground clearances detected by a radar under the vehicle's exterior rearview mirrors in multiple cycles. The exterior rearview mirrors may include a left exterior rearview mirror and a right exterior rearview mirror. The above-mentioned radar may be a radar for detecting the distance from the exterior rearview mirror to the road surface, and may preferably be an ultrasonic radar, an infrared radar, or other radar with lower cost and resolution.

[0040] The above-mentioned acquisition of multiple ground clearances detected by the vehicle may, for example, be acquisition of multiple ground clearances detected by a radar under a left exterior rearview mirror or a right exterior rearview mirror in multiple cycles. Alternatively, it may be acquisition of multiple first heights detected by a radar under a left exterior rearview mirror in multiple cycles; acquisition of multiple second heights detected by a radar under a right exterior rearview mirror in multiple cycles; the multiple ground clearances include multiple first heights and multiple second heights.

[0041] In S102, the height variance value can be used to reflect the fluctuation of the height above the ground in multiple cycles when the vehicle is traveling on the target road. If it is on a flat road, the distance fluctuation is small; if it is on a rough road, the distance fluctuation is large; that is, the fluctuation of the height above the ground is related to the roughness of the ground.

[0042] The above-mentioned calculation of the height variance value of the vehicle in multiple cycles according to the multiple ground clearance heights may be, for example, calculating the average of the multiple ground clearance heights; and calculating the first variance value according to the multiple first heights and the first average values;

[0043] Alternatively, it may be that a first mean of multiple first heights is calculated; a first variance value is calculated based on the multiple first heights and the first mean; a second mean of multiple second heights is calculated; a second variance value is calculated based on the multiple second heights and the second mean; and the first variance value and the second variance value are respectively multiplied by corresponding weight coefficients, and the sum is calculated to obtain the height variance value of the vehicle in multiple periods.

[0044] In S103, the above-mentioned multiple road roughness types may include a flat road type, a low-roughness type, a medium-roughness type, and a high-roughness type. In the embodiment of the present application, the multiple road roughness types are not limited to this, and can also be set according to actual needs of the user, which is not specifically limited here.

[0045] Different road roughness types correspond to different variance intervals. Specifically, the variance interval corresponding to the flat road type is (0-0.1]; the variance interval corresponding to the low rugged type is (0.1-0.5]; the variance interval corresponding to the medium rugged type is (0.5-1]; the variance interval corresponding to the high rugged type is greater than 1. Of course, in the embodiment of the present application, the variance intervals corresponding to the above-mentioned road roughness types are not limited to this, and can also be set according to the actual needs of the user, and are not specifically limited here.

[0046] The above-mentioned road surface ruggedness type corresponding to the height variance value among the preset multiple road surface ruggedness types is determined as the road surface ruggedness type of the target road. The variance interval corresponding to each road surface ruggedness type among the preset multiple road surface ruggedness types is obtained, and the multiple road surface ruggedness types include a flat road surface type, a low ruggedness type, a medium ruggedness type and a high ruggedness type; the road surface ruggedness type corresponding to the height variance value is determined as the road surface ruggedness type of the target road.

[0047] In some embodiments, the exterior rearview mirrors may include a left exterior rearview mirror and a right exterior rearview mirror;

[0048] The above S101 may specifically include:

[0049] Acquire multiple first heights detected by the radar below the left exterior rearview mirror in multiple cycles;

[0050] Acquire multiple second heights detected by the radar below the right exterior rearview mirror in multiple cycles;

[0051] The plurality of ground clearance heights includes a plurality of first heights and a plurality of second heights.

[0052] The above-mentioned first height may be the distance from the left exterior rearview mirror to the road surface detected by the radar below the left exterior rearview mirror within one cycle.

[0053] The above-mentioned second height can be the distance from the right exterior rearview mirror to the road surface detected by the radar below the right exterior rearview mirror within one cycle.

[0054] In an embodiment of the present application, the exterior rearview mirror includes a left exterior rearview mirror and a right exterior rearview mirror, so that the multiple ground clearance heights include multiple first heights detected by the radar below the left exterior rearview mirror in multiple cycles, and multiple second heights detected by the radar below the right exterior rearview mirror in multiple cycles. The heights on the left and right sides of the vehicle can complement each other, reduce visual blind spots, and improve the accuracy of road roughness detection.

[0055] In some embodiments, the above S102 may specifically include:

[0056] Calculate a first average of the plurality of first heights;

[0057] Calculate a first variance value according to the multiple first heights and the first means;

[0058] Calculate a second mean of the plurality of second heights;

[0059] Calculate a second variance value according to the plurality of second heights and second means;

[0060] The first variance value and the second variance value are multiplied by the corresponding weight coefficients respectively, and the sum is calculated to obtain the height variance values ​​of the vehicle in multiple cycles.

[0061] The calculation of the first average of the plurality of first heights may be performed, for example, by calculating the first average of the plurality of first heights according to the following formula:

[0062] AL N =(HL1+HL2+…+HL N ) / N

[0063] Among them, HL1, HL2, HL3, …, HL N is the multiple first heights of N cycles, AL N is the first mean.

[0064] The first variance value is calculated based on the multiple first heights and the first mean. Exemplarily, the first variance value can be calculated based on the multiple first heights and the first mean according to the following formula:

[0065]

[0066] Among them, δL N is the first variance value, HL i is the i-th first height among the multiple first heights, AL N is the first mean.

[0067] The above calculation of the second mean of the plurality of second heights may be performed, for example, by calculating the second mean of the plurality of second heights according to the following formula:

[0068] AL R =(HR1+HR2+…+HR N ) / N

[0069] Among them, HR1, HR2, HR3, …, HR N For N cycles of multiple second heights, AR N is the second mean.

[0070] The second variance value is calculated based on the multiple second heights and the second mean. For example, the second variance value can be calculated based on the multiple second heights and the second mean according to the following formula:

[0071]

[0072] Among them, δR N is the second variance value, HR i is the i-th second height among the plurality of second heights, AR N is the second mean.

[0073] The first variance value may correspond to the first weight coefficient, and the second variance value may correspond to the second weight coefficient. Assuming that the ground clearances on the left and right sides have the same weight coefficients for the entire vehicle, that is, the first weight coefficient and the second weight coefficient are both 50%. Of course, in the embodiment of the present application, the actual values ​​of the first weight coefficient and the second weight coefficient may also be set according to the actual conditions of the ground clearances on the left and right sides for the entire vehicle.

[0074] The first variance value and the second variance value are respectively multiplied by the corresponding weight coefficients, and the sum is obtained to obtain the height variance value of the vehicle in multiple cycles. For example, when the first weight coefficient and the second weight coefficient corresponding to the first variance value and the second variance value are the same, the mean of the first variance value and the second variance value is determined as the height variance value, that is,

[0075] In an embodiment of the present application, a first variance value is obtained by calculating based on multiple first heights, and a second variance value is obtained by calculating based on multiple second heights, and the first variance value and the second variance value are respectively multiplied by corresponding weight coefficients, and the height variance value of the vehicle in multiple periods is obtained by summing up. The first height and the second height on the left and right sides of the vehicle can be fused to reduce the error of unilateral radar collection, obtain an accurate height variance value, and further improve the accuracy of road roughness detection.

[0076] In some embodiments, the above S103 may specifically include:

[0077] Obtaining a variance interval corresponding to each road surface ruggedness type among a plurality of preset road surface ruggedness types, wherein the plurality of road surface ruggedness types include a flat road surface type, a low ruggedness type, a medium ruggedness type, and a high ruggedness type;

[0078] The road surface roughness type corresponding to the height variance value is determined as the road surface roughness type of the target road.

[0079] The above-mentioned multiple road roughness types may include a flat road type, a low-rugged type, a medium-rugged type, and a high-rugged type. Among them, a flat road type may refer to a flat road surface with almost no obvious ups and downs or potholes. A low-rugged type may refer to a road surface with certain ups and downs, but the ups and downs are small, and the vehicle will feel a slight bump when driving. A medium-rugged type may refer to a road surface with large ups and downs, and the vehicle will feel obvious bumps when driving, but it can still drive normally. A high-rugged type may refer to a road surface with very obvious ups and downs, and the vehicle will feel a strong bump when driving, which may affect driving safety.

[0080] In an embodiment of the present application, multiple road surface ruggedness types include a flat road surface type, a low ruggedness type, a medium ruggedness type, and a high ruggedness type. By obtaining the variance interval corresponding to each road surface ruggedness type among the preset multiple road surface ruggedness types, a standardized classification can be provided, and the height variance value can be matched with the variance interval corresponding to the preset multiple road surface ruggedness types. The road surface ruggedness type of the target road can be accurately determined to reduce misjudgment and uncertainty.

[0081] In some embodiments, the above-mentioned obtaining the variance interval corresponding to each road surface roughness type among the preset multiple road surface roughness types may specifically include:

[0082] Obtaining a sample set of each road surface ruggedness type among a plurality of preset road surface ruggedness types, the sample set including a plurality of samples of the road surface ruggedness type and a height variance value corresponding to each sample;

[0083] Determine a boundary threshold corresponding to each road surface roughness type according to the height variance values ​​corresponding to multiple samples of each road surface roughness type, each boundary threshold being the maximum height variance value in the sample set of each road surface roughness type;

[0084] According to the boundary thresholds corresponding to the multiple road surface roughness types, the variance interval corresponding to each road surface roughness type is determined.

[0085] The sample set may include multiple samples of road roughness types and height variance values ​​corresponding to each sample, and different samples may correspond to different height variance values.

[0086] The above-mentioned boundary thresholds may be the maximum height variance value in the sample set of each road roughness type.

[0087] In the embodiment of the present application, since the sample set includes multiple samples of road surface ruggedness types and the height variance values ​​corresponding to each sample, it has a strong generalization ability, so that through the sample set of each road surface ruggedness type among the preset multiple road surface ruggedness types, the boundary threshold corresponding to each road surface ruggedness type can be accurately determined, and the variance interval corresponding to each road surface ruggedness type can be further accurately obtained, thereby improving the accuracy of road surface ruggedness detection.

[0088] In order to facilitate the understanding of the method for determining the road roughness type in the embodiment of the present application, the actual application process of the method for determining the road roughness type is described as follows:

[0089] like Figure 2 As shown in the figure, the black part is the detection area of ​​the wading ultrasonic radar. When the vehicle is driving on the road, the ultrasonic radars installed on the left and right rearview mirrors detect the distance from the rearview mirror to the ground. If it is on a flat road, the distance fluctuates less; if it is on a rugged road, the distance fluctuates more; the detection distance is related to the ruggedness of the ground. Therefore, the ruggedness of the road can be inferred based on the discreteness of the detected distance.

[0090] The present application provides a method for determining a road roughness type, which may include the following steps:

[0091] (1) System operation during vehicle driving

[0092] During the driving process, the wading ultrasonic radar system continues to work. The ultrasonic radar installed under the left and right rearview mirrors of the vehicle continues to emit ultrasonic signals towards the ground in a direct measurement manner and receives ground reflected waves. The detection cycle can be set to T.

[0093] (2) Detection of the distance between the rearview mirror and the ground

[0094] Because of the ruggedness of the road, the distance between the current vehicle's left and right rearview mirrors and the ground will continue to change. It is necessary to record the current distance between the vehicle's left and right rearview mirrors and the ground (i.e. the above-mentioned ground clearance) according to the real-time road environment. Figure 3 As shown, they are recorded as HL and HR (i.e. the first height and the second height mentioned above) respectively. HL and HR change with a period of T.

[0095] (3) Calculate the variance of the rearview mirror's distance from the ground

[0096] The number of calculation items of the rearview mirror ground distance variance is set to N, that is, the ground distance variance is calculated once every N cycles (i.e., the above multiple cycles). Then, in these N cycles, the rearview mirror ground distance of the vehicle is:

[0097] Left: HL1, HL2, HL3, …, HL N(equivalent to the above-mentioned multiple first heights);

[0098] Right side: HR1, HR2, HR3, …, HR N (equivalent to the above-mentioned multiple second heights).

[0099] The average distance of the left vehicle from the ground (equivalent to the first mean above) is AL N =(HL1+HL2+…+HL N ) / N;

[0100] Then the variance value of the distance from the left vehicle to the ground (equivalent to the first variance value mentioned above)

[0101] Similarly, the average distance of the right vehicle from the ground (equivalent to the second mean above) is AR N =(HR1+HR2+…+HR N ) / N;

[0102] The variance value of the distance from the right vehicle to the ground (equivalent to the second variance value mentioned above)

[0103] Assuming that the ground clearance on the left and right sides has the same weight (equivalent to the above weight coefficient) for the whole vehicle, the overall ground clearance variance (equivalent to the above height variance value) is

[0104] (4) Calibration of road roughness boundary value

[0105] The road surface types are divided into 4 levels: flat road surface (L0), low ruggedness (L1), medium ruggedness (L2), and high ruggedness (L3) (that is, the above-mentioned multiple road surface ruggedness types include flat road surface type, low ruggedness type, medium ruggedness type and high ruggedness type):

[0106] Flat road surface (L0) 0<δ≤X1

[0107] Low ruggedness (L1) X1<δ≤X2

[0108] Moderate ruggedness (L2) X2<δ≤X3

[0109] Highly rough (L3) X3<δ (equivalent to the variance interval corresponding to each road surface roughness type among the above multiple road surface roughness types)

[0110] X 1， X 2， X3 corresponds to the boundary thresholds of several different types of ruggedness calibration.

[0111] For the road type to be sampled, four different road roughness levels are selected according to functional requirements. The sampling vehicles are driven on these four road surfaces respectively. According to steps (1), (2), and (3), the variance values ​​of the roughness levels of these four different road surfaces are calculated respectively. 0， δ 1， δ 2， δ3.

[0112] For each type of road to be sampled, multiple samples are selected as much as possible to expand the generalization ability of the system. The boundary values ​​of several roads with different ruggedness are the maximum variance values ​​of the sampled roads of the road type:

[0113] X1=MAX(δ0), X2=MAX(δ1), X3=MAX(δ2).

[0114] (5) Determination of road roughness

[0115] The vehicle is traveling on a road (i.e., the target road mentioned above). According to steps (1), (2), and (3), the roughness variance value δ of the current vehicle is calculated and compared with the various roughness threshold intervals calibrated in step (4) to obtain the final road roughness value (equivalent to the road surface roughness type of the target road mentioned above).

[0116] Based on the method for determining the road roughness type provided in the above embodiment, the present application also provides a specific implementation of a device for determining the road roughness type. Please refer to the following embodiment.

[0117] like Figure 4 As shown, the device 400 for determining the road roughness type provided in the embodiment of the present application may include the following modules: an acquisition module 401 , a calculation module 402 and a determination module 403 .

[0118] An acquisition module 401 is used to acquire multiple ground clearances detected by the vehicle when the vehicle is traveling on a target road, where the multiple ground clearances are ground clearances detected by a radar below an exterior rearview mirror of the vehicle in multiple cycles;

[0119] A calculation module 402 is used to calculate the height variance value of the vehicle in multiple cycles according to multiple ground clearance heights;

[0120] The determination module 403 is used to determine the road surface roughness type corresponding to the height variance value as the road surface roughness type of the target road from among the preset multiple road surface roughness types, and different road surface roughness types correspond to different variance intervals.

[0121] The device for determining the road roughness type in the embodiment of the present application can obtain multiple ground clearance heights detected by the vehicle when the vehicle is traveling on the target road, and the multiple ground clearance heights are the ground clearance heights detected by the radar below the vehicle's exterior rearview mirror in multiple cycles; calculate the height variance values ​​of the vehicle in multiple cycles based on the multiple ground clearance heights; and determine the road roughness type corresponding to the height variance value as the road roughness type of the target road among the preset multiple road roughness types, and different road roughness types correspond to different variance intervals. In this way, in the embodiment of the present application, the height variance value can be calculated based on the ground clearance height detected by the radar below the vehicle's exterior rearview mirror in multiple cycles. Since the variance intervals of different road roughness types are different, the road roughness type of the target road can be accurately identified. The present application has no requirements on the computing power and storage capacity of the vehicle hardware, and can meet the road roughness detection requirements of low-end vehicles.

[0122] In some embodiments, the exterior rearview mirrors may include a left exterior rearview mirror and a right exterior rearview mirror;

[0123] The acquisition module 401 may specifically include:

[0124] A first acquisition unit, used for acquiring a plurality of first heights detected by the radar below the left exterior rearview mirror in a plurality of cycles;

[0125] A second acquisition unit is used to acquire a plurality of second heights detected by the radar below the right exterior rearview mirror in a plurality of cycles;

[0126] The plurality of ground clearance heights includes a plurality of first heights and a plurality of second heights.

[0127] In some embodiments, the calculation module 402 may specifically include:

[0128] A first calculation unit, used to calculate a first average of a plurality of first heights;

[0129] A second calculation unit, configured to calculate a first variance value according to the plurality of first heights and the first mean values;

[0130] A third calculation unit, used for calculating a second average of the plurality of second heights;

[0131] A fourth calculation unit, configured to calculate a second variance value according to the plurality of second heights and the second mean values;

[0132] The fifth calculation unit is used to multiply the first variance value and the second variance value by corresponding weight coefficients respectively, and sum them up to obtain the height variance values ​​of the vehicle in multiple periods.

[0133] In some embodiments, the determination module 403 may specifically include:

[0134] A third acquisition unit is used to acquire a variance interval corresponding to each road surface roughness type among a plurality of preset road surface roughness types, wherein the plurality of road surface roughness types include a flat road surface type, a low-roughness type, a medium-roughness type, and a high-roughness type;

[0135] The determination unit is used to determine the road surface roughness type corresponding to the height variance value as the road surface roughness type of the target road.

[0136] In some embodiments, the third acquisition unit may specifically include:

[0137] An acquisition subunit is used to acquire a sample set of each road surface roughness type among a plurality of preset road surface roughness types, wherein the sample set includes a plurality of samples of the road surface roughness type and a height variance value corresponding to each sample;

[0138] A first determination subunit is used to determine a boundary threshold corresponding to each road surface roughness type according to the height variance values ​​corresponding to a plurality of samples of each road surface roughness type, wherein each boundary threshold is a maximum height variance value in a sample set of each road surface roughness type;

[0139] The second determination subunit is used to determine the variance interval corresponding to each road surface roughness type according to the boundary thresholds corresponding to the multiple road surface roughness types.

[0140] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0141] The electronic device may include a processor 501 and a memory 502 storing computer program instructions.

[0142] Specifically, the processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0143] The memory 502 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 502 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory.

[0144] In certain embodiments, the memory 502 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0145] The processor 501 reads and executes the computer program instructions stored in the memory 502 to implement any one of the methods for determining the road roughness type in the above embodiments.

[0146] In one example, the electronic device may further include a communication interface 503 and a bus 510. Figure 5 As shown, the processor 501, the memory 502, and the communication interface 503 are connected via a bus 510 and communicate with each other.

[0147] The communication interface 503 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0148] Bus 510 includes hardware, software or both, and the parts of electronic equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 510 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0149] The electronic device can execute the method for determining the type of rough road in the embodiment of the present application, thereby realizing the combination Figure 1 and Figure 4 A method and device for determining the type of road roughness are described.

[0150] In addition, in combination with the method for determining the road roughness type in the above embodiment, the embodiment of the present application can provide a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the methods for determining the road roughness type in the above embodiment is implemented.

[0151] In combination with the method for determining the type of rough road in the above embodiments, an embodiment of the present application may provide a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes any of the methods for determining the type of rough road as described above.

[0152] In combination with the method for determining the type of rough road in the above embodiment, the embodiment of the present application can provide a vehicle for implementation. The vehicle includes at least one of the following: the device for determining the type of rough road as described above; the electronic device as described above; the computer-readable storage medium as described above; the computer program product as described above.

[0153] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0154] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0155] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0156] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0157] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for determining the type of road roughness, characterized in that: include: When the vehicle is traveling on a target road, obtaining a plurality of ground clearances detected by the vehicle, wherein the plurality of ground clearances are ground clearances detected by a radar below an exterior rearview mirror of the vehicle in a plurality of cycles; Calculating, according to the plurality of ground clearance heights, a height variance value of the vehicle in the plurality of cycles; Among the preset multiple road surface roughness types, the road surface roughness type corresponding to the height variance value is determined as the road surface roughness type of the target road, and different road surface roughness types correspond to different variance intervals.

2. The method according to claim 1, characterized in that: The exterior rearview mirrors include a left exterior rearview mirror and a right exterior rearview mirror; The obtaining of a plurality of ground clearances detected by the vehicle comprises: Acquire multiple first heights detected by the radar below the left exterior rearview mirror in multiple cycles; Acquire a plurality of second heights detected by the radar below the right exterior rearview mirror in the plurality of cycles; The plurality of heights above the ground include the plurality of first heights and the plurality of second heights.

3. The method according to claim 2, characterized in that The step of calculating the height variance values ​​of the vehicle within the multiple periods according to the multiple ground clearance heights includes: Calculating a first average of the plurality of first heights; Calculate a first variance value according to the multiple first heights and the first mean value; Calculating a second average of the plurality of second heights; Calculate a second variance value according to the multiple second heights and the second mean; The first variance value and the second variance value are respectively multiplied by corresponding weight coefficients, and the sums are calculated to obtain the height variance values ​​of the vehicle in the multiple cycles.

4. The method according to claim 1, characterized in that The step of determining the road surface roughness type corresponding to the height variance value from among the preset plurality of road surface roughness types as the road surface roughness type of the target road comprises: Obtaining a variance interval corresponding to each of a plurality of preset road surface roughness types, wherein the plurality of road surface roughness types include a flat road surface type, a low-roughness type, a medium-roughness type, and a high-roughness type; The road surface roughness type corresponding to the height variance value is determined as the road surface roughness type of the target road.

5. The method according to claim 4, characterized in that The obtaining of the variance interval corresponding to each of the plurality of preset road roughness types comprises: Acquire a sample set of each of the plurality of preset road surface roughness types, the sample set comprising a plurality of samples of the road surface roughness type and a height variance value corresponding to each of the samples; Determine a boundary threshold corresponding to each of the road surface roughness types according to the height variance values ​​corresponding to the plurality of samples of each road surface roughness type, wherein each of the boundary thresholds is a maximum height variance value in a sample set of each road surface roughness type; According to the boundary thresholds corresponding to the multiple road surface roughness types, the variance interval corresponding to each of the road surface roughness types is determined.

6. A device for determining the type of road roughness, characterized in that: The device comprises: an acquisition module, configured to acquire, when the vehicle is traveling on a target road, a plurality of ground clearances detected by the vehicle, the plurality of ground clearances being ground clearances detected by a radar below an exterior rearview mirror of the vehicle in a plurality of cycles; A calculation module, configured to calculate a height variance value of the vehicle within the multiple periods according to the multiple ground clearance heights; The determination module is used to determine the road surface roughness type corresponding to the height variance value as the road surface roughness type of the target road from among a plurality of preset road surface roughness types, and different road surface roughness types correspond to different variance intervals.

7. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the method for determining the road roughness type as described in any one of claims 1-5 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining the road roughness type as described in any one of claims 1 to 5 is implemented.

9. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining the road roughness type as described in any one of claims 1-5.

10. A vehicle, characterized in that: Include at least one of the following: The device for determining the type of road roughness as claimed in claim 6; The electronic device as claimed in claim 7; The computer readable storage medium of claim 8; A computer program product as claimed in claim 9.

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