Method for recognizing a vehicle scene and method for determining a vehicle speed

Abstract

The embodiments of the present invention provide a method for identifying a vehicle scene and a method for determining a vehicle speed, and belong to the field of vehicles. The vehicle includes driving wheels and non-driving wheels, and the method for identifying a vehicle scene includes: obtaining a first wheel speed of the driving wheels and a second wheel speed of the non-driving wheels; performing a preliminary identification of the current operating scene corresponding to the vehicle based on the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current operating scene, wherein the preliminary identification result includes an abnormal road scene; when it is determined that the preliminary identification result is an abnormal road scene, obtaining the current acceleration of the driving wheel; and performing a final identification of the current operating scene based on the current acceleration to obtain a final identification result of the current operating scene. The embodiments of the present invention can reduce hardware costs.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a method for identifying a vehicle scene and a method for determining a vehicle speed. Background Art

[0002] In the prior art, vehicles (for example, autonomous vehicles) can usually be driven in a variety of different working conditions. If the working conditions are distinguished by road conditions, for example, they can include normal road conditions or abnormal road conditions (for example, slippery road conditions). Identifying the working condition in which the vehicle is currently located is crucial for the safe driving of the vehicle itself. Taking autonomous vehicles as an example, if the autonomous vehicle cannot accurately identify the specific working condition in which it is currently located, it may seriously threaten the autonomous driving safety of the autonomous vehicle. At present, vehicles can detect the road surface through lidar, high-definition cameras, etc. to identify the road conditions and then identify the working condition in which the vehicle is currently located. However, this method has the problem of high hardware cost. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide a method for identifying a vehicle scene, a method for determining a vehicle speed, a processor, an apparatus for identifying a vehicle scene, an apparatus for determining a vehicle speed, and a vehicle, so as to solve the problems existing in the prior art.

[0004] To achieve the above-mentioned object, a first aspect of an embodiment of the present invention provides a method for identifying a vehicle scene, wherein the vehicle includes driving wheels and non-driving wheels, and the method includes:

[0005] Obtain a first wheel speed of a driving wheel and a second wheel speed of a non-driving wheel;

[0006] Preliminarily identifying a current operating scenario corresponding to the vehicle based on the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current operating scenario, wherein the preliminary identification result includes an abnormal road surface scenario;

[0007] When it is determined that the preliminary recognition result is an abnormal road scene, obtaining the current acceleration of the driving wheel;

[0008] The current working condition scene is finally identified according to the current acceleration to obtain the final identification result of the current working condition scene.

[0009] In an embodiment of the present invention, the preliminary recognition result also includes a normal road scene; the current operating condition scene of the vehicle is preliminarily recognized based on the first wheel speed and the second wheel speed to obtain a preliminary recognition result of the current operating condition scene, including: comparing the first wheel speed with the second wheel speed; when the difference between the first wheel speed and the second wheel speed is less than or equal to a preset wheel speed difference, determining that the preliminary recognition result is a normal road scene; when the difference between the first wheel speed and the second wheel speed is greater than the preset wheel speed difference, determining that the preliminary recognition result is an abnormal road scene.

[0010] In an embodiment of the present invention, the final recognition result includes a road slippage scenario; the current operating condition scenario is finally recognized based on the current acceleration to obtain the final recognition result of the current operating condition scenario, including: comparing the current acceleration with the preset vehicle acceleration; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is within the preset acceleration difference range, determining that the final recognition result is a road slippage scenario.

[0011] In an embodiment of the present invention, the current working condition scene is finally identified according to the current acceleration to obtain a final identification result of the current working condition scene, including: the current working condition scene is finally identified according to the current acceleration and the second wheel speed to obtain a final identification result of the current working condition scene.

[0012] In an embodiment of the present invention, the final recognition result includes a vehicle suspension scenario and a rotating hub test scenario; the current operating condition scenario is finally recognized based on the current acceleration and the second wheel speed to obtain a final recognition result of the current operating condition scenario, including: comparing the current acceleration with the preset vehicle acceleration, and comparing the second wheel speed with the preset wheel speed threshold; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is greater than the upper limit threshold of the preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a vehicle suspension scenario; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is less than the lower limit threshold of the preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a rotating hub test scenario.

[0013] In an embodiment of the present invention, the method further includes: obtaining the duration length of the current working condition scenario; and determining that the duration length is greater than a preset time length.

[0014] In the embodiment of the present invention, the preset wheel speed difference has a value range of 2 to 6 km / h.

[0015] In the embodiment of the present invention, the upper threshold value of the preset acceleration difference range is in the range of 1.2 to 1.8 m / s. 2 The lower threshold value of the preset acceleration difference range is in the range of 0.2 to 0.5 m / s. 2 .

[0016] In the embodiment of the present invention, the preset wheel speed threshold value has a value range of 0.1 to 1 km / h.

[0017] In the embodiment of the present invention, the preset time length ranges from 1 to 4 seconds.

[0018] A second aspect of an embodiment of the present invention provides a method for determining a vehicle speed, wherein the vehicle includes a driving wheel and a non-driving wheel, and the method includes:

[0019] Identifying a current operating scenario corresponding to the vehicle, wherein the current operating scenario is identified and determined according to the above-mentioned method for identifying vehicle scenarios;

[0020] Obtaining a first wheel speed of a driving wheel and / or a second wheel speed of a non-driving wheel;

[0021] The current vehicle speed corresponding to the current operating scenario is determined according to the current operating scenario, the first wheel speed and / or the second wheel speed.

[0022] In an embodiment of the present invention, the current operating condition scenario includes a normal road scenario, a road slip scenario, a vehicle suspension scenario and a hub test scenario; the current vehicle speed corresponding to the current operating condition scenario is determined according to the current operating condition scenario, the first wheel speed and / or the second wheel speed, including: when the current operating condition scenario is a normal road scenario, determining the average of the first wheel speed and the second wheel speed to obtain the current vehicle speed; when the current operating condition scenario is a road slip scenario, determining the second wheel speed as the current vehicle speed; when the current operating condition scenario is a vehicle suspension scenario, determining the first wheel speed as the current vehicle speed; when the current operating condition scenario is a hub test scenario, determining the first wheel speed as the current vehicle speed.

[0023] In an embodiment of the present invention, the method further includes: performing filtering and smoothing processing on the current vehicle speed to obtain a processed current vehicle speed.

[0024] In an embodiment of the present invention, filtering and smoothing processing is performed on the current vehicle speed to obtain the processed current vehicle speed, including: obtaining a filter coefficient corresponding to the current operating scenario, wherein the filter coefficient is less than 1; filtering and smoothing processing is performed on the current vehicle speed based on the filter coefficient to obtain the processed current vehicle speed.

[0025] In an embodiment of the present invention, the current vehicle speed is filtered and smoothed based on the filter coefficient to obtain the processed current vehicle speed, including: obtaining the previous vehicle speed corresponding to the previous operating scenario; and determining the processed current vehicle speed based on the current vehicle speed, the previous vehicle speed and the filter coefficient.

[0026] In an embodiment of the present invention, the processed current vehicle speed is determined based on the current vehicle speed, the previous vehicle speed and the filter coefficient, including: determining the speed difference between the current vehicle speed and the previous vehicle speed; determining the product value of the speed difference and the filter coefficient; and adding the product value to the previous vehicle speed to obtain the processed current vehicle speed.

[0027] In an embodiment of the present invention, the filter coefficients include a first filter coefficient corresponding to a vehicle suspension scenario, a second filter coefficient corresponding to a road slip scenario, a third filter coefficient corresponding to a normal road scenario, and a fourth filter coefficient corresponding to a hub test scenario. The value range of the first filter coefficient includes 0.4 to 0.6, the value range of the second filter coefficient includes 0.05 to 0.15, and the value ranges of the third filter coefficient and the fourth filter coefficient include 0.2 to 0.3.

[0028] In an embodiment of the present invention, obtaining the first wheel speed of the driving wheel and / or the second wheel speed of the non-driving wheel includes: when there are multiple driving wheels, determining an average of the wheel speeds of the multiple driving wheels as the first wheel speed; and / or when there are multiple non-driving wheels, determining an average of the wheel speeds of the multiple non-driving wheels as the second wheel speed.

[0029] A third aspect of an embodiment of the present invention provides a processor configured to execute the above-mentioned method for identifying a vehicle scene or the above-mentioned method for determining a vehicle speed.

[0030] A fourth aspect of an embodiment of the present invention provides a device for identifying a vehicle scene, wherein the vehicle includes a driving wheel and a non-driving wheel, and the device includes:

[0031] A wheel speed acquisition module, configured to acquire a first wheel speed of a driving wheel and a second wheel speed of a non-driving wheel;

[0032] a preliminary recognition module, configured to perform preliminary recognition of a current operating scenario corresponding to the vehicle based on the first wheel speed and the second wheel speed, to obtain a preliminary recognition result of the current operating scenario, wherein the preliminary recognition result includes an abnormal road surface scenario;

[0033] An acceleration acquisition module, configured to acquire the current acceleration of the driving wheel when the preliminary recognition result is determined to be an abnormal road scene;

[0034] The final recognition module is used to perform final recognition of the current working condition scene according to the current acceleration to obtain the final recognition result of the current working condition scene.

[0035] A fifth aspect of an embodiment of the present invention provides a device for determining a vehicle speed, wherein the vehicle includes a driving wheel and a non-driving wheel, and the device includes:

[0036] A scene recognition module, configured to recognize a current operating scene corresponding to the vehicle, wherein the current operating scene is determined according to the above-mentioned method for recognizing vehicle scenes;

[0037] a wheel speed acquisition module, configured to acquire a first wheel speed of a driving wheel and / or a second wheel speed of a non-driving wheel;

[0038] The vehicle speed determination module is used to determine the current vehicle speed corresponding to the current operating scenario based on the current operating scenario, the first wheel speed and / or the second wheel speed.

[0039] A sixth aspect of an embodiment of the present invention provides a vehicle, the vehicle including drive wheels and non-drive wheels, the vehicle including: the above-mentioned device for identifying vehicle scenes or the above-mentioned device for determining vehicle speed.

[0040] The above technical solution obtains the first wheel speed of the driving wheel and the second wheel speed of the non-driving wheel, and preliminarily identifies the current working condition scene corresponding to the vehicle based on the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current working condition scene. When it is determined that the preliminary identification result is an abnormal road scene, the current acceleration of the driving wheel is further obtained, and the current working condition scene is finally identified based on the current acceleration to obtain a final identification result of the current working condition scene. The above technical solution can realize the identification of the working condition scene without the need for additional hardware equipment, thereby reducing hardware costs. The working condition scene is preliminarily identified based on the wheel speeds of the driving wheel and the non-driving wheel. When the initial identification result is an abnormal road scene, the working condition scene is finally identified based on the current acceleration of the driving wheel, thereby determining the specific type of the abnormal road scene and improving the accuracy of the working condition scene identification.

[0041] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0043] Figure 1 The following schematically shows a flow chart of a method for identifying a vehicle scene in an embodiment of the present invention;

[0044] Figure 2 The following schematically shows a flow chart of a method for determining vehicle speed according to an embodiment of the present invention;

[0045] Figure 3 Schematically shows a logic diagram of a method for determining vehicle speed in a preferred embodiment of the present invention;

[0046] Figure 4 The following schematically shows a structural block diagram of an apparatus for identifying vehicle scenes according to an embodiment of the present invention;

[0047] Figure 5 The following schematically shows a structural block diagram of a device for identifying vehicle scenes in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0049] Figure 1 The following schematically shows a flow chart of a method for identifying a vehicle scene in one embodiment of the present invention. Figure 1 As shown, in an embodiment of the present invention, a method for identifying a vehicle scene is provided. The vehicle includes driving wheels and non-driving wheels. Taking the method applied to a processor as an example, the method may include the following steps:

[0050] Step S102: Acquire a first wheel speed of a driving wheel and a second wheel speed of a non-driving wheel.

[0051] Step S104 , preliminarily identifying the current operating scenario corresponding to the vehicle according to the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current operating scenario, wherein the preliminary identification result includes an abnormal road scenario.

[0052] Step S106 : When it is determined that the preliminary recognition result is an abnormal road scene, the current acceleration of the driving wheel is obtained.

[0053] Step S108 , performing final recognition on the current working condition scene according to the current acceleration to obtain a final recognition result of the current working condition scene.

[0054] It can be understood that the first wheel speed is the rotational speed of the driving wheel, and the second wheel speed is the rotational speed of the non-driving wheel. The specific values ​​of the first wheel speed and the second wheel speed can be detected by corresponding wheel speed detection equipment (such as wheel speed sensors). The current working condition scenario is the driving condition or driving condition in which the vehicle is currently located. Furthermore, different working condition scenarios can be divided according to road conditions. The preliminary recognition result is the preliminary judgment result of the working condition scenario in which the vehicle is currently located, and may include abnormal road surface scenarios. The abnormal road surface scenario is a scenario in which the contact surface of the wheel is an abnormal road surface, and its specific types may include multiple types, such as road slip scenarios or other test driving scenarios. The final recognition result is the final judgment result of the working condition scenario in which the vehicle is currently located. For example, when the preliminary recognition result is an abnormal road surface scenario, the final recognition result may be a specific type of abnormal road surface scenario, such as a road slip scenario or other test driving scenarios.

[0055] Specifically, the processor can obtain the first wheel speed of the driving wheel and the second wheel speed of the non-driving wheel. For example, the first wheel speed of the driving wheel can be obtained by the first wheel speed sensor, and the second wheel speed of the non-driving wheel can be obtained by the second wheel speed sensor. Then, the current working condition scene corresponding to the vehicle can be preliminarily identified according to the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current working condition scene. For example, the processor can compare the first wheel speed and the second wheel speed. When there is a certain difference between the first wheel speed and the second wheel speed, it can be determined that the current working condition scene corresponding to the vehicle is an abnormal road scene. Further, after determining that the preliminary identification result is an abnormal road scene, it is preliminarily determined that the vehicle After the corresponding current operating condition scene is an abnormal road scene, the processor can obtain the current acceleration of the driving wheel, for example, it can obtain the current acceleration of the driving wheel detected by the acceleration sensor, and thus finally identify the current operating condition scene according to the current acceleration to obtain the final identification result of the current operating condition scene. For example, the processor can determine the acceleration level corresponding to the current acceleration of the driving wheel (which may include medium, high, and low), and based on the pre-stored correspondence between the acceleration level and the specific type of abnormal road scene, determine the specific type of the abnormal road scene according to the acceleration level corresponding to the current acceleration of the driving wheel, that is, the final identification result of the current operating condition scene.

[0056] The above method for identifying vehicle scenes obtains a first wheel speed of the driving wheel and a second wheel speed of the non-driving wheel, and performs a preliminary identification of the current working condition scene corresponding to the vehicle based on the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current working condition scene. When it is determined that the preliminary identification result is an abnormal road scene, the current acceleration of the driving wheel is further obtained, and the current working condition scene is finally identified based on the current acceleration to obtain a final identification result of the current working condition scene. The above technical solution can realize the identification of working condition scenes without the need for additional hardware equipment, thereby reducing hardware costs. The working condition scene is preliminarily identified based on the wheel speeds of the driving wheel and the non-driving wheel. When the initial identification result is an abnormal road scene, the working condition scene is finally identified based on the current acceleration of the driving wheel, thereby determining the specific type of the abnormal road scene and improving the accuracy of working condition scene identification.

[0057] In one embodiment, the preliminary recognition result also includes a normal road scene; the current operating condition scene of the vehicle is preliminarily recognized based on the first wheel speed and the second wheel speed to obtain a preliminary recognition result of the current operating condition scene, including: comparing the first wheel speed with the second wheel speed; when the difference between the first wheel speed and the second wheel speed is less than or equal to a preset wheel speed difference, determining that the preliminary recognition result is a normal road scene; when the difference between the first wheel speed and the second wheel speed is greater than the preset wheel speed difference, determining that the preliminary recognition result is an abnormal road scene.

[0058] It will be understood that the normal road scenario refers to a scenario where the wheel contact surface is a normal road surface. The preset wheel speed difference is a preset threshold difference between a first wheel speed of the driving wheel and a second wheel speed of the non-driving wheel, for example, 3 km / h. It will be understood that the first wheel speed is typically greater than or equal to the second wheel speed.

[0059] Specifically, the processor can compare the first wheel speed with the second wheel speed. When the difference between the first wheel speed and the second wheel speed is less than or equal to the preset wheel speed difference, the processor can determine that the preliminary recognition result of the vehicle's current operating condition scene is a normal road scene. Conversely, when the difference between the first wheel speed and the second wheel speed is greater than the preset wheel speed difference, the processor can determine that the preliminary recognition result of the vehicle's current operating condition scene is an abnormal road scene.

[0060] In an embodiment of the present application, by setting a preset wheel speed difference and comparing the difference between the first wheel speed and the second wheel speed with the preset wheel speed difference, normal road scenes and abnormal road scenes can be identified and distinguished based on the comparison results, thereby improving the accuracy of the preliminary recognition results.

[0061] In one embodiment, the final recognition result includes a road slippage scenario; the current operating condition scenario is finally recognized based on the current acceleration to obtain the final recognition result of the current operating condition scenario, including: comparing the current acceleration with the preset vehicle acceleration; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is within the preset acceleration difference range, determining that the final recognition result is a road slippage scenario.

[0062] It is understood that the road slippery scene is a driving scene with a slippery road. The preset vehicle acceleration is a preset vehicle acceleration. It is understood that the current acceleration and the preset vehicle acceleration can be positive or negative, for example, the acceleration under braking is negative. The preset acceleration difference range is the range of the difference between the preset drive wheel acceleration and the preset vehicle acceleration, for example, 0.4m / s 2 ~1.4m / s 2 .

[0063] Specifically, the processor can compare the current acceleration with the preset vehicle acceleration, and when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is within the preset acceleration difference range, it can be determined that the specific type of the abnormal road scene is a road slip scene, that is, the final recognition result of the working condition scene is a road slip scene.

[0064] In an embodiment of the present application, by setting a preset vehicle acceleration and a preset acceleration difference range, and comparing the absolute value of the difference between the current acceleration of the drive wheel and the preset vehicle acceleration with the preset acceleration difference range, it is possible to determine whether the specific type of the abnormal road scene is a road slipping scene, thereby improving the accuracy of the road slipping scene judgment results.

[0065] In one embodiment, finally identifying the current working condition scene according to the current acceleration to obtain a final identification result of the current working condition scene includes: finally identifying the current working condition scene according to the current acceleration and the second wheel speed to obtain a final identification result of the current working condition scene.

[0066] Specifically, the processor can finally identify the current working condition scene based on the current acceleration of the driving wheel and the second wheel speed of the non-driving wheel to obtain the final recognition result of the current working condition scene. For example, the processor can input the current acceleration of the driving wheel and the second wheel speed of the non-driving wheel into a pre-trained working condition scene recognition model to obtain the final recognition result of the working condition scene output by the model.

[0067] In an embodiment of the present application, in addition to finally identifying the current operating condition scenario based on the current acceleration of the driving wheel, the second wheel speed of the non-driving wheel can also be introduced, that is, the vehicle's operating condition scenario is finally identified based on the current acceleration of the driving wheel and the second wheel speed of the non-driving wheel, further improving the accuracy of operating condition scenario identification.

[0068] In one embodiment, the final recognition result includes a vehicle suspension scenario and a rotating hub test scenario; the current operating condition scenario is finally recognized based on the current acceleration and the second wheel speed to obtain a final recognition result of the current operating condition scenario, including: comparing the current acceleration with the preset vehicle acceleration, and comparing the second wheel speed with the preset wheel speed threshold; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is greater than the upper limit threshold of the preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a vehicle suspension scenario; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is less than the lower limit threshold of the preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a rotating hub test scenario.

[0069] It can be understood that the vehicle suspension scenario is a driving scenario in which the vehicle is suspended in the air, and the hub test scenario is a test driving scenario in which the vehicle's drive wheels are located on the hub and the non-drive wheels are located on the ground. The preset vehicle acceleration is the vehicle acceleration calculated in real time based on vehicle information (power source output torque, vehicle weight, road slope, etc.) and the vehicle dynamics formula, wherein the vehicle dynamics formula is a prior art and will not be described here. The preset acceleration difference range is the range interval of the difference between the preset drive wheel acceleration and the preset vehicle acceleration, for example 0.4m / s 2 ~1.4m / s 2 The preset wheel speed threshold is a preset smaller wheel speed threshold, for example, 0.5 km / h. The preset acceleration difference range may include an upper threshold and a lower threshold.

[0070] Specifically, the processor may compare the current acceleration with a preset vehicle acceleration, and compare the second wheel speed of the non-driven wheel with a preset wheel speed threshold, to determine the absolute value of the difference between the current acceleration and the preset vehicle acceleration. If the absolute value of the difference between the current acceleration and the preset vehicle acceleration is greater than an upper threshold of a preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a vehicle suspension scenario. If the absolute value of the difference between the current acceleration and the preset vehicle acceleration is less than a lower threshold of a preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a rotating hub test scenario. It can be understood that the similarity between the vehicle suspension scenario and the rotating hub test scenario is that the second wheel speed of the non-driven wheel is less than the preset wheel speed threshold, and the difference is that the current acceleration of the driving wheel corresponding to the vehicle suspension scenario is greater than the upper threshold of the preset acceleration difference range, while the current acceleration of the driving wheel corresponding to the rotating hub test scenario is less than the lower threshold of the preset acceleration difference range. That is, the current acceleration of the driving wheel corresponding to the vehicle suspension scenario is relatively large, and the current acceleration of the driving wheel corresponding to the rotating hub test scenario is relatively small.

[0071] In an embodiment of the present application, by comparing the current acceleration of the driving wheel with the preset vehicle acceleration and comparing the second wheel speed of the non-driving wheel with the preset wheel speed threshold, the vehicle suspension scenario and the hub rotation test scenario can be identified based on the two sets of comparison results, thereby improving the fineness of the division of abnormal road scenes and further improving the accuracy of the vehicle's working condition scenario.

[0072] In one embodiment, the method for identifying a vehicle scene further includes: obtaining a duration of the current operating scene; and determining that the duration is greater than a preset time length.

[0073] It is understood that the duration of the current operating scenario is the cumulative time length that the vehicle maintains the current operating scenario. The preset time length is the duration length of the vehicle operating scenario that is preset, for example, 2 seconds.

[0074] Specifically, the processor can obtain the duration of the current operating scenario, that is, the cumulative duration of the vehicle in a certain operating scenario, and compare the duration with a preset time length to determine that the duration is greater than the preset time length. It is understandable that the comparison and judgment process of the duration with the preset time length can occur during the preliminary identification of the operating scenario, or during the final identification of the operating scenario, or can occur simultaneously during the preliminary identification and final identification of the operating scenario. For example, if the difference between the first wheel speed and the second wheel speed is greater than the preset wheel speed difference and the duration is greater than the preset time length, the preliminary identification result is determined to be an abnormal road surface scenario; if the absolute value of the difference between the current acceleration of the driving wheel and the preset vehicle acceleration is within the preset acceleration difference range and the duration is greater than the preset time length, the final identification result is determined to be a road slippage scenario. The same applies to other operating scenarios.

[0075] In an embodiment of the present application, during the process of preliminary identification and / or final identification of the current operating condition scene, determining that the current operating condition scene of the vehicle lasts for a certain period of time, that is, determining that the duration of the current operating condition scene is greater than a preset time length, can reduce the sensitivity of the scene recognition function. If it is too sensitive, the operating condition scene may experience unexpected jumps.

[0076] In one embodiment, the preset wheel speed difference ranges from 2 to 6 km / h.

[0077] In one embodiment, the upper threshold value of the preset acceleration difference range is in the range of 1.2 to 1.8 m / s. 2 The lower threshold value of the preset acceleration difference range is in the range of 0.2 to 0.5 m / s. 2 .

[0078] In one embodiment, the preset wheel speed threshold value ranges from 0.1 to 1 km / h.

[0079] In one embodiment, the preset time length ranges from 1 to 4 seconds.

[0080] Figure 2 The flowchart of the method for determining the vehicle speed in one embodiment of the present invention is shown schematically. Figure 2 As shown, in an embodiment of the present invention, a method for determining a vehicle speed is provided. The vehicle includes a driving wheel and a non-driving wheel. The method is described by taking the application of the method to a processor as an example. The method may include the following steps:

[0081] Step S202 : Identify the current operating scenario corresponding to the vehicle, wherein the current operating scenario is identified and determined according to the method for identifying the vehicle scenario in the above embodiment.

[0082] Step S204: acquiring a first wheel speed of the driving wheel and / or a second wheel speed of the non-driving wheel.

[0083] Step S206 , determining the current vehicle speed corresponding to the current operating scenario according to the current operating scenario, the first wheel speed and / or the second wheel speed.

[0084] Specifically, the processor can identify the current operating scenario corresponding to the vehicle according to the method for identifying vehicle scenarios in the above-mentioned embodiment, and then obtain the first wheel speed of the driving wheel and / or the second wheel speed of the non-driving wheel, so as to determine the current vehicle speed corresponding to the current operating scenario according to the current operating scenario, the first wheel speed and / or the second wheel speed. It can be understood that different operating scenarios may not necessarily have the same corresponding vehicle speed determination process. For example, the processor can determine the corresponding vehicle speed determination strategy according to the current operating scenario based on the correspondence between the pre-stored operating scenario and the vehicle speed determination strategy. The vehicle speed determination strategy may include determining the current vehicle speed corresponding to the current operating scenario according to the first wheel speed and / or the second wheel speed.

[0085] The above-mentioned method for determining vehicle speed automatically identifies the current operating scenario corresponding to the vehicle, and switches the vehicle speed determination method that matches the current operating scenario according to the identification result of the current operating scenario, that is, obtains the first wheel speed of the driving wheel and / or the second wheel speed of the non-driving wheel, and determines the current vehicle speed corresponding to the current operating scenario according to the current operating scenario, the first wheel speed and / or the second wheel speed. This can realize automatic and accurate calculation of the vehicle speed in different operating scenarios, and determines the vehicle speed in combination with the operating scenario, the first wheel speed and / or the second wheel speed, thereby improving the accuracy of the vehicle speed.

[0086] In one embodiment, the current operating condition scenario includes a normal road scenario, a road slip scenario, a vehicle suspension scenario, and a hub test scenario; the current vehicle speed corresponding to the current operating condition scenario is determined based on the current operating condition scenario, the first wheel speed, and / or the second wheel speed, including: when the current operating condition scenario is a normal road scenario, determining the average of the first wheel speed and the second wheel speed to obtain the current vehicle speed; when the current operating condition scenario is a road slip scenario, determining the second wheel speed as the current vehicle speed; when the current operating condition scenario is a vehicle suspension scenario, determining the first wheel speed as the current vehicle speed; when the current operating condition scenario is a hub test scenario, determining the first wheel speed as the current vehicle speed.

[0087] Specifically, when identifying the current operating condition as a normal road scene, the processor can determine the average of the first wheel speed and the second wheel speed to obtain the current vehicle speed. When identifying the current operating condition as a road slippage scene, the processor can determine the second wheel speed as the current vehicle speed. When identifying the current operating condition as a vehicle suspension scene, the processor can determine the first wheel speed as the current vehicle speed. When identifying the current operating condition as a hub test scene, the processor can determine the first wheel speed as the current vehicle speed. It can be understood that in normal road scenarios, the first wheel speed of the driving wheel and the second wheel speed of the non-driving wheel are basically the same, so the average of the first wheel speed and the second wheel speed can be determined as the current speed of the vehicle; in road slip scenarios, since the driving wheel will slip, the driving wheel will do some useless work, while the non-driving wheel will not slip, and the first wheel speed of the driving wheel is greater than the second wheel speed of the non-driving wheel. The second wheel speed of the non-driving wheel is the current speed of the vehicle, which is closer to the speed issued by the controller, that is, the expected speed of the vehicle; in vehicle suspension scenarios and rotating hub test scenarios, since the second wheel speed of the non-driving wheel is too small and close to zero, the first wheel speed of the driving wheel can be taken as the current speed of the vehicle. It is worth noting that the actual speed of the vehicle in the two working conditions of the vehicle suspension scenario and the rotating hub test scenario is zero. The speed calculated in these two working conditions refers to the speed value issued by the controller, that is, the expected speed of the vehicle.

[0088] In the embodiment of the present application, the vehicle speed calculation method can be changed according to the switching of working conditions, thereby improving the accuracy of the vehicle speed.

[0089] In one embodiment, the method for determining the vehicle speed further includes: performing filtering and smoothing processing on the current vehicle speed to obtain a processed current vehicle speed.

[0090] It is understandable that the vehicle speed calculation method changes according to the switching of the working condition scenario. There may be a step in the vehicle speed calculation value before and after the working condition scenario switches, which has a significant impact on the algorithm decision of the relevant controller. Therefore, it is necessary to filter and smooth the vehicle speed when the scene switches, that is, to filter and smooth the current vehicle speed to obtain the processed current vehicle speed.

[0091] In one embodiment, filtering and smoothing the current vehicle speed to obtain the processed current vehicle speed includes: obtaining a filter coefficient corresponding to the current operating scenario, wherein the filter coefficient is less than 1; and filtering and smoothing the current vehicle speed based on the filter coefficient to obtain the processed current vehicle speed.

[0092] It is understandable that the acceleration and deceleration capabilities of vehicles in different working scenarios are different, and the filter coefficients of their vehicle speeds need to match them. Therefore, the filter coefficients corresponding to different working scenarios can be pre-set.

[0093] Specifically, the processor can obtain a filter coefficient corresponding to the current operating scenario, where the filter coefficient is less than 1, and perform filtering and smoothing processing on the current vehicle speed based on the filter coefficient to obtain the processed current vehicle speed.

[0094] In the embodiment of the present application, different filter coefficients are set for each operating scenario, so as to fully cover the special requirements of each operating scenario.

[0095] In one embodiment, the current vehicle speed is filtered and smoothed based on the filter coefficient to obtain the processed current vehicle speed, including: obtaining the previous vehicle speed corresponding to the previous operating scenario; and determining the processed current vehicle speed based on the current vehicle speed, the previous vehicle speed, and the filter coefficient.

[0096] It can be understood that the previous vehicle speed is the vehicle speed corresponding to the previous operating scenario different from the current operating scenario.

[0097] Specifically, the processor may obtain the previous vehicle speed corresponding to the previous operating scenario, and determine the processed current vehicle speed based on the current vehicle speed, the previous vehicle speed, and the filter coefficient.

[0098] In one embodiment, the processed current vehicle speed is determined based on the current vehicle speed, the previous vehicle speed and the filter coefficient, including: determining the speed difference between the current vehicle speed and the previous vehicle speed; determining the product value of the speed difference and the filter coefficient; and adding the product value to the previous vehicle speed to obtain the processed current vehicle speed.

[0099] In one embodiment, the filter coefficients include a first filter coefficient corresponding to a vehicle suspension scenario, a second filter coefficient corresponding to a road slip scenario, a third filter coefficient corresponding to a normal road scenario, and a fourth filter coefficient corresponding to a hub test scenario. The value range of the first filter coefficient includes 0.4 to 0.6, the value range of the second filter coefficient includes 0.05 to 0.15, and the value ranges of the third filter coefficient and the fourth filter coefficient include 0.2 to 0.3.

[0100] Understandably, in the vehicle suspension scenario, the driving resistance and inertia are the smallest, so the acceleration and deceleration that the vehicle can achieve are the largest and the changes are the most drastic. In order to accurately obtain the current vehicle speed, a larger first filter coefficient needs to be set, and it is recommended to be a value in the range of 0.4 to 0.6; in the road slippage scenario, the vehicle's acceleration ability is weak due to wheel slippage, and the vehicle speed changes most slowly, so its filter coefficient is the smallest, that is, the second filter coefficient can be set to a value in the range of 0.05 to 0.15; the vehicle acceleration and deceleration capabilities in the normal road scenario and the rotating hub test scenario are equivalent, and are between vehicle suspension and slippery road conditions, so the third filter coefficient and the fourth filter coefficient are set to a value in the range of 0.2 to 0.3.

[0101] In one embodiment, obtaining the first wheel speed of the driving wheel and / or the second wheel speed of the non-driving wheel includes: when there are multiple driving wheels, determining the average of the wheel speeds of the multiple driving wheels as the first wheel speed; and / or when there are multiple non-driving wheels, determining the average of the wheel speeds of the multiple non-driving wheels as the second wheel speed.

[0102] It can be understood that if there are multiple driving wheel speed signals, the driving wheel speed V dw (i.e. the first wheel speed) is the average of all driving wheel speeds, i.e. Among them, k is the number of driving wheel speed signals, V dw_k is the kth wheel speed signal; if there are multiple non-driving wheel speed signals, the non-driving wheel speed V ndｗ (i.e. the second wheel speed) is the average of all non-driving wheel speeds, i.e. Where, j is the number of non-driving wheel speed signals, V ｎdw_j is the jth wheel speed signal.

[0103] Vehicle speed is a key parameter for vehicle control. Accurate vehicle speed is a prerequisite for realizing basic vehicle functions and an important guarantee for vehicle power, economy and safety. Existing technologies either focus on multi-source signal fusion to improve the accuracy of vehicle speed calculation, or focus on vehicle speed calculation redundancy in failure mode to achieve vehicle functional safety, but do not involve vehicle speed calculation in different driving scenarios. In the actual development, production, testing and use of vehicles, the vehicle may be subjected to various driving scenarios such as suspended debugging, installed on a rotating hub test, driving on slippery roads and normal roads. Different vehicle speed calculation methods are required to obtain accurate vehicle speeds in different driving scenarios. Therefore, the existing technology lacks a vehicle speed calculation method for different driving scenarios (i.e., working condition scenarios). That is, the existing technology does not involve vehicle speed calculation in different driving scenarios such as suspended debugging, rotating hub testing, slippery roads and normal roads, and cannot cover the vehicle speed requirements in such scenarios. The vehicle speed calculation method based on scene recognition becomes the key to solving this problem.

[0104] Vehicle speed is a key parameter for vehicle control. Accurate vehicle speed is a prerequisite for achieving basic vehicle functions and an important guarantee for vehicle power, economy, and safety. During the actual vehicle development, production, testing, and use, there are many driving scenarios, including suspended debugging, rotating hub testing, driving on slippery roads, and driving on normal roads. Different scenarios have different requirements for the source of vehicle speed signals. For example, during suspended full-speed debugging and fixed rotating hub testing, the actual vehicle speed is 0, but in order to conduct normal testing, the drive wheel speed is used as the vehicle speed. When the vehicle is slipping, the non-drive wheel speed is used as the vehicle speed.

[0105] Existing technologies either focus on multi-source signal fusion to improve the accuracy of vehicle speed calculation, or focus on vehicle speed calculation redundancy under failure mode to achieve vehicle functional safety. They do not involve vehicle speed calculation in different driving scenarios such as suspension debugging, hub testing, slippery roads and normal roads, and cannot cover the vehicle speed requirements in such scenarios.

[0106] A specific embodiment of the present invention provides a method for determining vehicle speed that automatically identifies scenarios such as vehicle suspension, slippery roads, normal roads, and wheel-spinning tests. This method adapts the speed calculation method to changing scenarios, improving speed accuracy in all scenarios and ensuring the safety of debugging and testing. The method is divided into three modules: scenario recognition, speed calculation, and speed filtering.

[0107] 1. Scene Recognition

[0108] The characteristic of a suspended vehicle is that the actual vehicle speed is 0, the non-driven wheels are stationary, and the driving torque only needs to overcome the inertia of the rotating system. Therefore, the same power source output torque can obtain a much greater driving wheel acceleration than on a normal road.

[0109] The characteristic of the rotating hub test is that the vehicle's actual speed is 0, the non-driven wheels are stationary on the ground, and the driving wheels are placed on the rotating hub. The rotating hub simulates road driving resistance and applies it to the driving wheels. Therefore, the same power source output torque can obtain the driving wheel acceleration equivalent to normal road surface.

[0110] The characteristics of a slippery road surface are that the wheel speed of the non-driven wheels is significantly lower than the wheel speed of the driven wheels, or even zero, the adhesion of the slippery road surface is significantly lower than that of the normal road surface, and the driving wheel acceleration that can be obtained with the same power source output torque is between the vehicle suspended and the normal road surface.

[0111] The characteristics of normal road conditions are that the wheel speeds of the non-driven wheels and the driven wheels are basically the same, and the driving wheel acceleration obtained with the same power source output torque is comparable to that of the rotating hub test, and is significantly lower than that of slippery roads and suspended roads. The characteristics are summarized in Table 1:

[0112] Table 1 Comparison of characteristics of different scenarios

[0113] Scenario Non-driven wheel speed Drive wheel acceleration Vehicle suspended 3 0 high Hub Test 2 0 Low Slippery road 1 Lower than the drive wheel speed middle Normal road 0 Equivalent to the drive wheel speed Low

[0114] Note: The comparison of driving wheel acceleration in each scenario in the table is carried out under the same power source output torque.

[0115] Based on the above feature comparison, the scene recognition steps are formulated as follows:

[0116] The default scene is set according to the probability of occurrence of each scene. The default scene is set to normal road (S=0). If the absolute value of the difference between the driving wheel speed and the non-driving wheel speed is greater than a certain calibration value and lasts for a certain period of time ( Figure 3 Jump condition ①),

[0117] That is: |V dw -V ndw |>V diff _C and T diff >t diff _C

[0118] The current scene is determined to be an abnormal road surface (S=1, 2 or 3), and the process goes to step (2) for further judgment. dw is the driving wheel speed, V ndw is the non-driven wheel speed, V ｄｉｆｆ _C is the wheel speed difference threshold for determining abnormal road conditions, which can be calibrated according to actual conditions, for example, a value within the range of 2 to 6 km / h. ｄiff V ｄw -V ndw |>V diff _C is the accumulated time of the condition being met. It starts counting when the condition is met and is cleared when the condition is not met. diff _C is the cumulative time threshold for determining abnormal road conditions, which can be calibrated according to actual conditions and defaults to a value within the range of 1 to 4 seconds.

[0119] otherwise( Figure 3 Jump condition ②), keep the default scene (normal road S=0).

[0120] After entering the abnormal road scene, set the default scene to slippery road and calculate the driving wheel acceleration.

[0121] If the absolute value of the difference between the driving wheel acceleration and the theoretical vehicle acceleration is greater than the first calibration value and the non-driving wheel speed is less than a certain value and lasts for a certain period of time ( Figure 3 Jump condition ⑥). That is |a dw -a th |>a diff _1_C&V ndw <V dec _C&T diff_1 >t diff_ _C, it is determined that the current scene is that the vehicle is suspended in the air (S=3).

[0122] If the absolute value of the difference between the driving wheel acceleration and the theoretical vehicle acceleration is less than the second calibration value and the non-driving wheel speed is less than a certain value during the vehicle driving process, and it lasts for a certain period of time ( Figure 1 Jump condition ③). That is |a dw -a th | diff _2_C&V ndw <V dec _C&T diff_2 >t​diff_2 _C, then the current scene is determined to be a hub test (S=2).

[0123] otherwise( Figure 1 Jump conditions ④⑤), then keep the current scene as slippery road (S=1).

[0124] In the above formula, a dw is the driving wheel acceleration, a th is the theoretical vehicle acceleration. diff_1 、T diff_2 , starts timing when the corresponding condition is met, and clears to zero when the condition is not met diff _1_C, a diff _2_C are the acceleration difference judgment thresholds for vehicle suspension and rotating hub test scenarios, which can be calibrated according to actual conditions. It must be ensured that a diff _1_C>a diff _2_C. For example, a diff _1_C is a value within the range of 1.2 to 1.8 m / s2, a diff _2_C is a value within the range of 0.2 to 0.5 m / s2. diff_1 _C, t diff_2 _C are the cumulative time thresholds for vehicle suspension and wheel rotation test scenarios, which can be calibrated according to actual conditions and are set by default to a value within the range of 1 to 4 seconds. dec _C is the non-drive wheel speed detection threshold, which can be calibrated according to actual conditions and defaults to a value within the range of 0.1 to 1 km / h.

[0125] Driving wheel acceleration a dw The acquisition method is:

[0126] The wheel speed signal sent by ABS and ESC or the wheel speed signal collected by the wheel speed sensor is obtained by time derivative, that is,

[0127]

[0128] Theoretical vehicle acceleration a th The method to obtain is:

[0129] Calculate in real time based on vehicle information (power source output torque, vehicle weight, road slope, etc.) and vehicle dynamics formulas.

[0130]

[0131] Among them, V veh is the current vehicle speed, i is the transmission ratio of the transmission system, η is the powertrain efficiency, T mot is the output torque of the motor or engine, m vehis the vehicle mass, f is the rolling resistance coefficient, θ is the road slope, C D is the drag coefficient, A is the frontal area, ρ is the air density, and g is the acceleration due to gravity.

[0132] 2. Vehicle speed calculation

[0133] According to the scene recognition results, select the vehicle speed calculation method as follows: Figure 3 shown.

[0134] (1) Use the non-drive wheel speed V ndw and the driving wheel speed V dw The average value of the default speed V is used as the default speed V, that is, V=(V dw +V ndw ) / 2.

[0135] (2) If the current scene is a normal road, keep using the non-driving wheel speed V ndw and the driving wheel speed V dw The average value is taken as the vehicle speed V, that is, V=(V dw +V ndw ) / 2.

[0136] (3) If the current scene is a slippery road, use the non-driving wheel speed V ndw As the vehicle speed V, that is, V = V ndw .

[0137] (4) If the current scene is a vehicle suspended or rotating test, the driving wheel speed V dw As the vehicle speed V, that is, V = V dw .

[0138] (5) If there are multiple non-driven wheel speed signals, the non-driven wheel speed V ndw is the average of all non-driving wheel speeds, that is Where j is the number of non-driving wheel speed signals, V ndw_j is the jth wheel speed signal.

[0139] (6) If there are multiple driving wheel speed signals, the driving wheel speed V dw is the average of all driving wheel speeds, that is Among them, k is the number of driving wheel speed signals, V dw_k is the kth wheel speed signal.

[0140] Note: The wheel speeds in the technical solutions of the embodiments of this invention can be equivalently replaced or calculated using the transmission output shaft speed or motor speed. Any scenario based on transmission output shaft speed or motor speed and any vehicle speed calculation method also fall within the technical solutions of the embodiments of this invention.

[0141] 3. Vehicle speed filtering

[0142] The speed calculation method changes according to the scene switching. There may be a step in the speed calculation value before and after the scene switching, which has a significant impact on the algorithm decision of the relevant controller. Therefore, it is necessary to filter and smooth the speed during the scene switching. At the same time, the acceleration and deceleration capabilities of vehicles in different scenes are different, and their speed filtering coefficients need to match them. Therefore, the following speed filtering method is formulated, and the corresponding formula is: V = V old +(VV old )*K fi_s _C, where V is the current vehicle speed, V old is the vehicle speed corresponding to the previous calculation cycle, K fi_s _C is the first-order filter coefficient corresponding to scene switching, which can be calibrated according to actual conditions, such as K fi_1 _C represents the speed calculation filter coefficient corresponding to the slippery road scene. Therefore, the present invention can fully cover the special requirements of each scene by setting different filter coefficients for each scene.

[0143] In the vehicle suspension scenario, the vehicle has the smallest driving resistance and inertia, so the acceleration and deceleration that the vehicle can achieve are the largest and the changes are the most drastic. In order to accurately obtain the current vehicle speed, a larger filter coefficient needs to be set. K is recommended. fi_3 _C is a value in the range of 0.4 to 0.6; on slippery roads, the vehicle's acceleration ability is weak due to wheel slippage, and the vehicle speed changes the slowest, so its filtering coefficient is the smallest, K fi_1 _C is set to a value in the range of 0.05 to 0.15; the acceleration and deceleration capabilities of the vehicle on normal road and in the rotating hub test scenario are similar, and are between the vehicle suspended and the slippery road, so the filter coefficient K is set fi_0 _C=K fi_2 _C is a value within the range of 0.2 to 0.3.

[0144] Compared with the existing technology, the vehicle speed determination method proposed in the present invention can automatically identify four scenarios: normal road surface, slippery road surface, vehicle suspension and hub rotation test, and automatically switch the vehicle speed calculation method and vehicle speed filter coefficient that match the scenario according to the scene recognition result, thereby realizing automatic and accurate calculation of the vehicle speed in the four scenarios, solving the problem that the current mainstream vehicle speed calculation method that uses the speed of the non-driven wheel as the vehicle speed is difficult to support vehicle suspension debugging, hub rotation test and other testing tasks.

[0145] An embodiment of the present invention provides a processor configured to execute the method for identifying a vehicle scene according to the above embodiment or the method for determining a vehicle speed according to the above embodiment.

[0146] Figure 4 The following schematically shows a structural block diagram of an apparatus for identifying vehicle scenes in one embodiment of the present invention. Figure 4 As shown, in one embodiment, an embodiment of the present invention provides an apparatus 400 for identifying a vehicle scene, wherein the vehicle includes a driving wheel and a non-driving wheel, and the apparatus 400 includes:

[0147] The wheel speed acquisition module 410 is configured to acquire a first wheel speed of a driving wheel and a second wheel speed of a non-driving wheel.

[0148] The preliminary recognition module 420 is used to perform preliminary recognition of the current operating scene corresponding to the vehicle according to the first wheel speed and the second wheel speed to obtain a preliminary recognition result of the current operating scene, wherein the preliminary recognition result includes an abnormal road scene.

[0149] The acceleration acquisition module 430 is configured to acquire the current acceleration of the driving wheel when the preliminary recognition result is determined to be an abnormal road scene.

[0150] The final recognition module 440 is used to perform final recognition on the current working condition scene according to the current acceleration to obtain a final recognition result of the current working condition scene.

[0151] The above-mentioned device for identifying vehicle scenes obtains a first wheel speed of the driving wheel and a second wheel speed of the non-driving wheel, and performs a preliminary identification of the current working condition scene corresponding to the vehicle based on the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current working condition scene. When it is determined that the preliminary identification result is an abnormal road scene, the current acceleration of the driving wheel is further obtained, and the current working condition scene is finally identified based on the current acceleration to obtain a final identification result of the current working condition scene. The above-mentioned technical solution can realize the identification of working condition scenes without the need for additional hardware equipment, thereby reducing hardware costs. The working condition scene is preliminarily identified based on the wheel speeds of the driving wheel and the non-driving wheel. When the initial identification result is an abnormal road scene, the working condition scene is finally identified based on the current acceleration of the driving wheel, thereby determining the specific type of the abnormal road scene and improving the accuracy of working condition scene identification.

[0152] In one embodiment, the preliminary recognition result also includes a normal road scene; the preliminary recognition module 420 is also used to: compare the first wheel speed with the second wheel speed; when the difference between the first wheel speed and the second wheel speed is less than or equal to the preset wheel speed difference, determine that the preliminary recognition result is a normal road scene; when the difference between the first wheel speed and the second wheel speed is greater than the preset wheel speed difference, determine that the preliminary recognition result is an abnormal road scene.

[0153] In one embodiment, the final recognition result includes a road slippage scenario; the final recognition module 440 is also used to: compare the current acceleration with the preset vehicle acceleration; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is within the preset acceleration difference range, determine that the final recognition result is a road slippage scenario.

[0154] In one embodiment, the final recognition module 440 is further configured to perform final recognition on the current operating scenario according to the current acceleration and the second wheel speed to obtain a final recognition result of the current operating scenario.

[0155] In one embodiment, the final recognition result includes a vehicle suspension scenario and a rotating hub test scenario; the final recognition module 440 is also used to: compare the current acceleration with the preset vehicle acceleration, and compare the second wheel speed with the preset wheel speed threshold; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is greater than the upper limit threshold of the preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a vehicle suspension scenario; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is less than the lower limit threshold of the preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be a rotating hub test scenario.

[0156] In one embodiment, the apparatus 400 for identifying a vehicle scene further includes a duration determination module, configured to obtain the duration of the current operating scene; and determine whether the duration is greater than a preset time length.

[0157] In one embodiment, the preset wheel speed difference ranges from 2 to 6 km / h.

[0158] In one embodiment, the upper threshold value of the preset acceleration difference range is in the range of 1.2 to 1.8 m / s. 2 The lower threshold value of the preset acceleration difference range is in the range of 0.2 to 0.5 m / s. 2 .

[0159] In one embodiment, the preset wheel speed threshold value ranges from 0.1 to 1 km / h.

[0160] In one embodiment, the preset time length ranges from 1 to 4 seconds.

[0161] Figure 5 The following schematically shows a structural block diagram of an apparatus for identifying vehicle scenes in one embodiment of the present invention. Figure 5 As shown, in one embodiment, the present invention provides an apparatus 500 for determining a vehicle speed, wherein the vehicle includes a driving wheel and a non-driving wheel, and the apparatus 500 includes:

[0162] The scene recognition module 510 is used to identify the current operating scene corresponding to the vehicle, wherein the current operating scene is identified and determined according to the method for identifying the vehicle scene in the above embodiment.

[0163] The wheel speed acquisition module 520 is configured to acquire a first wheel speed of a driving wheel and / or a second wheel speed of a non-driving wheel.

[0164] The vehicle speed determination module 530 is configured to determine the current vehicle speed corresponding to the current operating scenario based on the current operating scenario, the first wheel speed, and / or the second wheel speed.

[0165] The above-mentioned device for determining vehicle speed automatically identifies the current operating scenario corresponding to the vehicle, and switches the vehicle speed determination method that matches the current operating scenario according to the identification result of the current operating scenario, that is, obtains the first wheel speed of the driving wheel and / or the second wheel speed of the non-driving wheel, and determines the current vehicle speed corresponding to the current operating scenario according to the current operating scenario, the first wheel speed and / or the second wheel speed. This can realize automatic and accurate calculation of the vehicle speed in different operating scenarios, and determines the vehicle speed in combination with the operating scenario, the first wheel speed and / or the second wheel speed, thereby improving the accuracy of the vehicle speed.

[0166] In one embodiment, the current operating condition scenario includes a normal road scenario, a road slip scenario, a vehicle suspension scenario, and a hub test scenario; the vehicle speed determination module 530 is also used to: when the current operating condition scenario is a normal road scenario, determine the average of the first wheel speed and the second wheel speed to obtain the current vehicle speed; when the current operating condition scenario is a road slip scenario, determine the second wheel speed as the current vehicle speed; when the current operating condition scenario is a vehicle suspension scenario, determine the first wheel speed as the current vehicle speed; when the current operating condition scenario is a hub test scenario, determine the first wheel speed as the current vehicle speed.

[0167] In one embodiment, the device 500 for determining the vehicle speed further includes a filtering module for performing filtering and smoothing processing on the current vehicle speed to obtain the processed current vehicle speed.

[0168] In one embodiment, the filtering module is further used to: obtain a filtering coefficient corresponding to the current operating scenario, wherein the filtering coefficient is less than 1; and perform filtering and smoothing processing on the current vehicle speed based on the filtering coefficient to obtain the processed current vehicle speed.

[0169] In one embodiment, the filtering module is further used to: obtain the previous vehicle speed corresponding to the previous operating scenario; and determine the processed current vehicle speed based on the current vehicle speed, the previous vehicle speed, and the filtering coefficient.

[0170] In one embodiment, the processed current vehicle speed is determined based on the current vehicle speed, the previous vehicle speed and the filter coefficient, including: determining the speed difference between the current vehicle speed and the previous vehicle speed; determining the product value of the speed difference and the filter coefficient; and adding the product value to the previous vehicle speed to obtain the processed current vehicle speed.

[0171] In one embodiment, the filter coefficients include a first filter coefficient corresponding to a vehicle suspension scenario, a second filter coefficient corresponding to a road slip scenario, a third filter coefficient corresponding to a normal road scenario, and a fourth filter coefficient corresponding to a hub test scenario. The value range of the first filter coefficient includes 0.4 to 0.6, the value range of the second filter coefficient includes 0.05 to 0.15, and the value ranges of the third filter coefficient and the fourth filter coefficient include 0.2 to 0.3.

[0172] In one embodiment, the wheel speed acquisition module 520 is further used to: when there are multiple drive wheels, determine the average of the wheel speeds of the multiple drive wheels as a first wheel speed; and / or when there are multiple non-drive wheels, determine the average of the wheel speeds of the multiple non-drive wheels as a second wheel speed.

[0173] An embodiment of the present invention provides a vehicle, including drive wheels and non-drive wheels, and the vehicle includes: the device for identifying a vehicle scene according to the above embodiment or the device for determining a vehicle speed according to the above embodiment.

[0174] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0175] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0176] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0177] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0178] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0179] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0180] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0181] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0182] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for identifying a vehicle scene, characterized in that: The vehicle includes driven wheels and non-driven wheels, and the method includes: Obtaining a first wheel speed of the driving wheel and a second wheel speed of the non-driving wheel; performing preliminary identification of a current operating scenario corresponding to the vehicle based on the first wheel speed and the second wheel speed to obtain a preliminary identification result of the current operating scenario, wherein the preliminary identification result includes an abnormal road surface scenario; When it is determined that the preliminary recognition result is the abnormal road scene, obtaining the current acceleration of the driving wheel; Performing a final recognition on the current operating scenario according to the current acceleration to obtain a final recognition result of the current operating scenario; The final recognition result includes a vehicle suspension scenario and a rotating hub test scenario; and the final recognition of the current operating scenario based on the current acceleration to obtain the final recognition result of the current operating scenario includes: comparing the current acceleration with a preset vehicle acceleration, and comparing the second wheel speed with a preset wheel speed threshold; When the absolute value of the difference between the current acceleration and the preset vehicle acceleration is greater than an upper threshold of a preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, determining that the final recognition result is the vehicle suspended scene; When the absolute value of the difference between the current acceleration and the preset vehicle acceleration is less than a lower limit threshold of a preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, the final recognition result is determined to be the rotating hub test scenario.

2. The method according to claim 1, characterized in that The preliminary recognition result also includes a normal road scene; the preliminary recognition of the current operating condition scene of the vehicle based on the first wheel speed and the second wheel speed to obtain the preliminary recognition result of the current operating condition scene includes: comparing the first wheel speed to the second wheel speed; When the difference between the first wheel speed and the second wheel speed is less than or equal to a preset wheel speed difference, determining that the preliminary recognition result is the normal road scene; When the difference between the first wheel speed and the second wheel speed is greater than the preset wheel speed difference, the preliminary recognition result is determined to be the abnormal road scene.

3. The method according to claim 1, characterized in that The final recognition result includes a road slip scene; the final recognition of the current operating condition scene according to the current acceleration to obtain the final recognition result of the current operating condition scene includes: comparing the current acceleration with a preset vehicle acceleration; When the absolute value of the difference between the current acceleration and the preset vehicle acceleration is within a preset acceleration difference range, the final recognition result is determined to be the road slippage scenario.

4. The method according to claim 2 or 3, characterized in that The method further comprises: Obtaining the duration of the current operating scenario; It is determined that the duration is greater than a preset time length.

5. The method according to claim 2, characterized in that The preset wheel speed difference has a value range of 2 to 6 km / h.

6. The method according to claim 1 or 3, characterized in that The upper threshold value of the preset acceleration difference range is in the range of 1.2 to 1.8 m / s 2 The lower limit threshold of the preset acceleration difference range is in the range of 0.2~0.5 m / s 2 .

7. The method according to claim 1, characterized in that The preset wheel speed threshold value has a value range of 0.1-1 km / h.

8. The method according to claim 4, characterized in that The preset time length ranges from 1 to 4 seconds.

9. A method for determining vehicle speed, characterized in that The vehicle includes driven wheels and non-driven wheels, and the method includes: Identifying a current operating scenario corresponding to the vehicle, wherein the current operating scenario is identified and determined according to the method for identifying vehicle scenarios according to any one of claims 1 to 8; Acquiring a first wheel speed of the driving wheel and / or a second wheel speed of the non-driving wheel; The current vehicle speed corresponding to the current operating scenario is determined according to the current operating scenario, the first wheel speed and / or the second wheel speed.

10. The method according to claim 9, characterized in that The current operating condition scenario includes a normal road scenario, a slippery road scenario, a vehicle suspension scenario, and a wheel rotation test scenario; and determining the current vehicle speed corresponding to the current operating condition scenario according to the current operating condition scenario, the first wheel speed, and / or the second wheel speed includes: When the current operating condition is the normal road condition, determining an average of the first wheel speed and the second wheel speed to obtain the current vehicle speed; When the current operating condition is the road slippery condition, determining the second wheel speed as the current vehicle speed; When the current operating condition is the vehicle-in-the-air condition, determining the first wheel speed as the current vehicle speed; When the current operating condition scenario is the rotating hub test scenario, the first wheel speed is determined to be the current vehicle speed.

11. The method according to claim 10, characterized in that The method further comprises: The current vehicle speed is filtered and smoothed to obtain a processed current vehicle speed.

12. The method according to claim 11, characterized in that The filtering and smoothing process is performed on the current vehicle speed to obtain the processed current vehicle speed, including: Obtaining a filter coefficient corresponding to the current operating scenario, wherein the filter coefficient is less than 1; The current vehicle speed is filtered and smoothed based on the filter coefficient to obtain a processed current vehicle speed.

13. The method according to claim 12, characterized in that The filtering and smoothing process is performed on the current vehicle speed based on the filtering coefficient to obtain the processed current vehicle speed, including: Get the last vehicle speed corresponding to the last working scenario; The processed current vehicle speed is determined according to the current vehicle speed, the previous vehicle speed, and the filter coefficient.

14. The method according to claim 13, characterized in that The determining the processed current vehicle speed according to the current vehicle speed, the previous vehicle speed, and the filter coefficient includes: determining a speed difference between the current vehicle speed and the previous vehicle speed; determining a product value of the vehicle speed difference and the filter coefficient; The product value is added to the previous vehicle speed to obtain the processed current vehicle speed.

15. The method according to claim 12, characterized in that The filter coefficients include a first filter coefficient corresponding to the vehicle suspension scenario, a second filter coefficient corresponding to the road slip scenario, a third filter coefficient corresponding to the normal road scenario, and a fourth filter coefficient corresponding to the hub test scenario. The value range of the first filter coefficient includes 0.4~0.6, the value range of the second filter coefficient includes 0.05~0.15, and the value range of the third filter coefficient and the fourth filter coefficient includes 0.2~0.

3.

16. The method according to claim 11, characterized in that The obtaining of the first wheel speed of the driving wheel and / or the second wheel speed of the non-driving wheel includes: In the case where there are multiple driving wheels, determining an average of the wheel speeds of the multiple driving wheels as the first wheel speed; and / or When there are a plurality of non-driven wheels, an average of the wheel speeds of the plurality of non-driven wheels is determined as the second wheel speed.

17. A processor, characterized in that: The method is configured to perform the method for identifying a vehicle scene according to any one of claims 1 to 8 or the method for determining a vehicle speed according to any one of claims 9 to 16.

18. A device for identifying vehicle scenes, characterized in that: The vehicle includes driven wheels and non-driven wheels, and the device includes: a wheel speed acquisition module, configured to acquire a first wheel speed of the driving wheel and a second wheel speed of the non-driving wheel; a preliminary recognition module, configured to perform preliminary recognition of a current operating scenario corresponding to the vehicle based on the first wheel speed and the second wheel speed, to obtain a preliminary recognition result of the current operating scenario, wherein the preliminary recognition result includes an abnormal road surface scenario; an acceleration acquisition module, configured to acquire the current acceleration of the driving wheel when it is determined that the preliminary recognition result is the abnormal road scene; a final recognition module, configured to perform a final recognition on the current operating scenario according to the current acceleration to obtain a final recognition result of the current operating scenario; The final recognition result includes a vehicle suspension scenario and a rotating hub test scenario; the final recognition module (440) is further used to: compare the current acceleration with a preset vehicle acceleration, and compare the second wheel speed with a preset wheel speed threshold; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is greater than the upper limit threshold of a preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, determine that the final recognition result is the vehicle suspension scenario; when the absolute value of the difference between the current acceleration and the preset vehicle acceleration is less than the lower limit threshold of the preset acceleration difference range and the second wheel speed is less than the preset wheel speed threshold, determine that the final recognition result is the rotating hub test scenario.

19. A device for determining vehicle speed, characterized in that The vehicle includes driven wheels and non-driven wheels, and the device includes: A scene recognition module, configured to recognize a current operating scene corresponding to the vehicle, wherein the current operating scene is identified and determined according to the method for recognizing vehicle scenes according to any one of claims 1 to 8; a wheel speed acquisition module, configured to acquire a first wheel speed of the driving wheel and / or a second wheel speed of the non-driving wheel; A vehicle speed determination module is used to determine the current vehicle speed corresponding to the current operating scenario based on the current operating scenario, the first wheel speed and / or the second wheel speed.

20. A vehicle, characterized in that: The vehicle includes driven wheels and non-driven wheels, and the vehicle includes: The device for recognizing a vehicle scene according to claim 18 or the device for determining a vehicle speed according to claim 19.

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