Automatic driving method, device and storage medium of vehicle

Abstract

This application provides an autonomous driving method, device, and storage medium for a vehicle, relating to the field of intelligent driving technology. The method includes: determining the radius of curvature of the road where the vehicle is located and the vehicle's hand torque; the hand torque is the rotational torque acting on the vehicle's steering wheel; determining the road type based on the radius of curvature, wherein the road type is either a curved road or a straight road; determining the vehicle's driving state based on the road type, radius of curvature, and hand torque; the driving state is either a takeover state or an autonomous driving state. The solution of this application improves the accuracy of determining the vehicle's driving state.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to an autonomous driving method, device and storage medium for a vehicle. Background Technology

[0002] In intelligent driving assistance systems, vehicles can achieve autonomous driving through lateral motion control. In scenarios where the driver actively takes over steering wheel control, the vehicle needs to determine the driver's intention to take over steering wheel control and then disengage the lateral motion control function.

[0003] In related technologies, during the autonomous driving process, the hand torque at the current moment can be determined. If the hand torque is greater than or equal to a preset hand torque threshold, the duration for which the hand torque is greater than or equal to the preset hand torque threshold can be determined. If the duration is greater than or equal to a preset duration threshold, it can be determined that the driver has the intention to actively take over the steering wheel control, thereby disengaging the lateral motion control function.

[0004] However, the accuracy of determining the driver's intention to take over the steering wheel using the above methods is low, resulting in lower vehicle safety. Summary of the Invention

[0005] This application provides an autonomous driving method, device, and storage medium for vehicles to improve the accuracy of determining the driving state of a vehicle.

[0006] In a first aspect, embodiments of this application provide an autonomous driving method for a vehicle, comprising:

[0007] Determine the radius of curvature of the road where the vehicle is located and the vehicle's hand torque; hand torque is the torque exerted on the vehicle's steering wheel.

[0008] The road type is determined based on the radius of curvature; the road type is either a curved road or a straight road.

[0009] The driving status of the vehicle is determined based on the road type, radius of curvature, and hand torque; the driving status is either takeover mode or automatic driving mode.

[0010] In some embodiments, determining the driving state of the vehicle includes:

[0011] When the road type is straight, the driving state is determined based on the hand torque;

[0012] When the road type is a curve, the driving state is determined based on the radius of curvature and hand torque.

[0013] In some embodiments, determining the driving state based on hand torque includes:

[0014] The hand torque level of the vehicle at the current moment is determined based on the hand torque.

[0015] Determine the driving status based on the hand torque level.

[0016] In some embodiments, determining the hand torque level of the vehicle at the current moment based on the hand torque includes:

[0017] Determine the threshold range within which the hand torque falls;

[0018] The level corresponding to the threshold range is determined as the hand torque level.

[0019] In some embodiments, determining the driving state based on the hand torque level includes:

[0020] When the hand torque level is greater than or equal to a preset threshold, determine the duration of the hand torque level, and determine the driving state based on the duration and the hand torque level.

[0021] If the hand torque level is less than the preset threshold, the driving state is determined to be automatic driving state.

[0022] In some embodiments, determining the driving state based on duration and hand torque level includes:

[0023] Based on the mapping relationship between hand torque level and duration threshold, and the hand torque level, determine the duration threshold corresponding to the hand torque level;

[0024] The driving status is determined based on the duration and duration threshold.

[0025] In some embodiments, determining the driving state based on duration and duration threshold includes:

[0026] If the duration is greater than or equal to the duration threshold, the driving state is determined to be a takeover state;

[0027] If the duration is less than the duration threshold, the driving state is determined to be autonomous driving state.

[0028] In some embodiments, determining the driving state based on the radius of curvature and hand torque includes:

[0029] The threshold adjustment coefficient is determined based on the radius of curvature.

[0030] The driving state is determined based on the threshold adjustment coefficient and hand torque.

[0031] In some embodiments, determining the threshold adjustment coefficient includes:

[0032] Determine the curvature range corresponding to the radius of curvature within multiple preset curvature ranges;

[0033] The threshold adjustment coefficient is determined based on the mapping relationship between the curvature range and the adjustment coefficient, as well as the curvature range.

[0034] In some embodiments, determining the driving state based on a threshold adjustment coefficient and hand torque includes:

[0035] The hand torque level of the vehicle at the current moment is determined based on the hand torque and the threshold adjustment coefficient;

[0036] Determine the driving status based on the hand torque level.

[0037] In some embodiments, determining the hand torque level of the vehicle at the current moment based on the hand torque and a threshold adjustment coefficient includes:

[0038] Multiple preset threshold ranges are adjusted based on threshold adjustment coefficients to determine multiple adjustment threshold ranges;

[0039] Determine the threshold range where the hand torque falls among multiple adjustment threshold ranges;

[0040] The level corresponding to the threshold range is determined as the hand torque level.

[0041] In some embodiments, determining the road type based on the radius of curvature includes:

[0042] If the radius of curvature is greater than or equal to the curvature threshold, the road type is determined to be a straight road type;

[0043] If the radius of curvature is less than the curvature threshold, the road type is determined to be a curve type.

[0044] Secondly, embodiments of this application provide an autonomous driving device for a vehicle, the device comprising:

[0045] The first determining module is used to determine the radius of curvature of the road where the vehicle is located and the hand torque of the vehicle; the hand torque is the torque exerted on the steering wheel of the vehicle.

[0046] The second determining module is used to determine the road type based on the radius of curvature, which is either a curve or a straight road.

[0047] The processing module is used to determine the vehicle's driving status based on road type, radius of curvature, and hand torque; the driving status is either a takeover state or an autonomous driving state.

[0048] In some embodiments, the processing module is specifically used for:

[0049] When the road type is straight, the driving state is determined based on the hand torque;

[0050] When the road type is a curve, the driving state is determined based on the radius of curvature and hand torque.

[0051] In some embodiments, the processing module is specifically used for:

[0052] The hand torque level of the vehicle at the current moment is determined based on the hand torque.

[0053] Determine the driving status based on the hand torque level.

[0054] In some embodiments, the processing module is specifically used for:

[0055] Determine the threshold range within which the hand torque falls;

[0056] The level corresponding to the threshold range is determined as the hand torque level.

[0057] In some embodiments, the processing module is specifically used for:

[0058] When the hand torque level is greater than or equal to a preset threshold, determine the duration of the hand torque level, and determine the driving state based on the duration and the hand torque level.

[0059] If the hand torque level is less than the preset threshold, the driving state is determined to be automatic driving state.

[0060] In some embodiments, the processing module is specifically used for:

[0061] Based on the mapping relationship between hand torque level and duration threshold, and the hand torque level, determine the duration threshold corresponding to the hand torque level;

[0062] The driving status is determined based on the duration and duration threshold.

[0063] In some embodiments, the processing module is specifically used for:

[0064] If the duration is greater than or equal to the duration threshold, the driving state is determined to be a takeover state;

[0065] If the duration is less than the duration threshold, the driving state is determined to be autonomous driving state.

[0066] In some embodiments, the processing module is specifically used for:

[0067] The threshold adjustment coefficient is determined based on the radius of curvature.

[0068] The driving state is determined based on the threshold adjustment coefficient and hand torque.

[0069] In some embodiments, the processing module is specifically used for:

[0070] Determine the curvature range corresponding to the radius of curvature within multiple preset curvature ranges;

[0071] The threshold adjustment coefficient is determined based on the mapping relationship between the curvature range and the adjustment coefficient, as well as the curvature range.

[0072] In some embodiments, the processing module is specifically used for:

[0073] The hand torque level of the vehicle at the current moment is determined based on the hand torque and the threshold adjustment coefficient;

[0074] Determine the driving status based on the hand torque level.

[0075] In some embodiments, the processing module is specifically used for:

[0076] Multiple preset threshold ranges are adjusted based on threshold adjustment coefficients to determine multiple adjustment threshold ranges;

[0077] Determine the threshold range where the hand torque falls among multiple adjustment threshold ranges;

[0078] The level corresponding to the threshold range is determined as the hand torque level.

[0079] In some embodiments, the second determining module is specifically used for:

[0080] If the radius of curvature is greater than or equal to the curvature threshold, the road type is determined to be a straight road type;

[0081] If the radius of curvature is less than the curvature threshold, the road type is determined to be a curve type.

[0082] Thirdly, embodiments of this application provide an autonomous driving device for a vehicle, comprising:

[0083] At least one processor; and

[0084] A memory that is communicatively connected to at least one processor; wherein,

[0085] The memory stores instructions that can be executed by at least one processor to cause the at least one processor to perform the autonomous driving method of the vehicle involved in the first aspect and any possible implementation.

[0086] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement an autonomous driving method for a vehicle as described in the first aspect and any possible implementation.

[0087] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the autonomous driving method for a vehicle as described in the first aspect and any possible implementation.

[0088] The autonomous driving method, device, and storage medium for vehicles provided in this application differentiate between straight and curved roads by considering the road curvature radius, and comprehensively determine the vehicle's driving state by combining road type and steering wheel torque. This improves the accuracy of recognizing driver intervention intentions and vehicle driving states, reduces misjudgments caused by a single judgment standard, and thus lowers the risk of abnormal start-stop of the vehicle's lateral motion control function. Therefore, the autonomous driving method for vehicles provided in this application improves the safety and operational stability of vehicles during operation. Attached Figure Description

[0089] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0090] Figure 1 This is a schematic diagram illustrating the applicable scenarios provided in the embodiments of this application;

[0091] Figure 2 A flowchart illustrating an autonomous driving method for a vehicle provided in an embodiment of this application;

[0092] Figure 3 A schematic diagram of a process for determining driving status provided in an embodiment of this application;

[0093] Figure 4 A schematic diagram illustrating the determination of driving status as provided in an embodiment of this application;

[0094] Figure 5 A schematic diagram of the structure of an autonomous driving device for a vehicle provided in an embodiment of this application;

[0095] Figure 6 This is a schematic diagram of the structure of an autonomous driving device for a vehicle provided in an embodiment of this application.

[0096] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0097] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0098] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0099] To facilitate understanding, the following will be combined with... Figure 1 The application scenarios applicable to the embodiments of this application will be briefly described below.

[0100] Figure 1 This is a schematic diagram illustrating the applicable scenarios provided in the embodiments of this application, such as... Figure 1 As shown, the vehicle includes a vehicle 11, which is equipped with a steering wheel 12 and a smart camera 13, and the vehicle 11 is a vehicle with autonomous driving capabilities.

[0101] In practical applications, during autonomous driving, vehicle 11 can determine the radius of curvature of the road where it is currently located via intelligent camera 13. Vehicle 11 can also determine the steering torque applied by the driver on steering wheel 12, i.e., the hand torque of vehicle 11. Vehicle 11 determines its driving state as either a takeover state or an autonomous driving state based on the hand torque and the radius of curvature. A takeover state refers to the driver's intention to take over driving vehicle 11, while an autonomous driving state refers to the driver's lack of intention to take over driving vehicle 11.

[0102] It should be noted that, Figure 1 This is merely an example to illustrate a system architecture diagram, and is not a limitation on system architecture diagrams.

[0103] In intelligent driving assistance systems, vehicles can achieve autonomous driving through the lateral motion control functions of advanced driver assistance systems, including lane centering assist. In scenarios where the driver actively takes over steering wheel control, the vehicle needs to determine the driver's intention to take over steering wheel control and then disengage the lateral motion control function.

[0104] In related technologies, during autonomous driving, the vehicle can determine the current hand torque. Hand torque refers to the torque received by the vehicle's steering wheel. When the hand torque is greater than or equal to a preset hand torque threshold, the vehicle determines the duration for which the hand torque is greater than or equal to the preset hand torque threshold. If this duration is greater than or equal to a preset duration threshold, the vehicle determines the driving state to be in a takeover state. When the hand torque is less than the preset hand torque threshold, or the duration is less than the preset duration threshold, the vehicle determines the driving state to be in an autonomous driving state.

[0105] However, in the process of determining the vehicle's driving status as described above, the preset hand torque threshold and preset duration threshold were determined by staff based on experience, which may result in the preset hand torque threshold and / or preset duration threshold being too low. For example, if the preset hand torque threshold is too low, the vehicle may misinterpret the driving status as a takeover state when the driver only slightly grips the steering wheel (e.g., due to tension causing fluctuations in hand torque).

[0106] Similarly, there may be issues with preset hand torque thresholds and / or preset duration thresholds being too high. For example, if the preset hand torque threshold is too high, the driver may find it difficult to take control of the steering wheel with normal force. Thus, in situations requiring active intervention (such as emergency obstacle avoidance), the vehicle may not be able to promptly determine that the driving status is in a takeover state.

[0107] In summary, the aforementioned methods of determining driving status can lead to misjudgments or failure to respond in a timely manner, causing the vehicle to prematurely exit autonomous driving mode or fail to respond promptly to the driver's takeover intentions, resulting in lower vehicle safety during operation.

[0108] To address the aforementioned technical issues, in this embodiment, the vehicle distinguishes between straight and curved roads based on the road curvature radius, and comprehensively determines the vehicle's driving state by combining road type and steering wheel torque. This improves the accuracy of recognizing driver intervention intentions and vehicle driving states, reduces misjudgments caused by a single judgment criterion, and thus lowers the risk of abnormal start-stop of the vehicle's lateral motion control function. Therefore, the autonomous driving method provided in this application improves the safety and operational stability of the vehicle during operation.

[0109] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0110] Figure 2 This is a flowchart illustrating an autonomous driving method for a vehicle provided in an embodiment of this application. Please refer to [link / reference]. Figure 2 The method may include the following steps:

[0111] S21. Determine the radius of curvature of the road where the vehicle is located and the hand torque of the vehicle; the hand torque is the torque exerted on the steering wheel of the vehicle.

[0112] The vehicle is a motor vehicle equipped with advanced driver assistance systems such as lane centering assist and autonomous driving lateral motion control functions. In some embodiments, the vehicle is equipped with hardware components such as a reverse wheel and image acquisition devices.

[0113] The radius of curvature is a geometric parameter used to quantify the curvature of a road. The unit of radius of curvature can be meters (m), kilometers (km), etc. The radius of curvature can be represented by a positive integer value; a larger radius of curvature indicates a straighter road, and a smaller radius of curvature indicates a more curved road.

[0114] Hand torque is the torque generated by the force applied by the driver to the steering wheel of a vehicle. The unit of hand torque is Newton-meter (Nm). Hand torque can be expressed as a value greater than or equal to 0, and a larger hand torque indicates a greater force applied by the driver to the steering wheel; a smaller hand torque indicates a less force applied by the driver to the steering wheel. The steering wheel is the control component of the vehicle's steering system, allowing the driver to change the vehicle's direction by turning the steering wheel. A steering wheel torque sensor is deployed on the steering wheel to collect the torque applied by the driver.

[0115] In some embodiments, a vehicle can acquire the road surface conditions of the road where it is located through an image acquisition device, and determine the radius of curvature of the road where the vehicle is located based on the road surface conditions.

[0116] The vehicle can acquire the torque applied to the steering wheel by the driver through a steering wheel torque sensor and determine this torque as hand torque. Optionally, after acquiring the hand torque through the steering wheel torque sensor, the vehicle can filter the hand torque using a low-pass filter to obtain the filtered hand torque.

[0117] S22. Determine the road type based on the radius of curvature. The road type is either a curved road or a straight road.

[0118] Road types are classifications based on the geometric alignment characteristics of roads, used to indicate whether a road is straight or curved. In some embodiments, a road type can be a curved road type or a straight road type. A curved road type refers to a section of road with a noticeable curve, therefore, a curved road has a smaller radius of curvature. A straight road type refers to a section of road that maintains a largely straight shape without significant curves, therefore, a straight road has a larger radius of curvature.

[0119] In some embodiments, the vehicle determines the road type as follows: if the radius of curvature is greater than or equal to a curvature threshold, the road type is determined to be a straight road; if the radius of curvature is less than the curvature threshold, the road type is determined to be a curved road.

[0120] If the radius of curvature is greater than or equal to the curvature threshold, it means that the road the vehicle is currently on is straight with no obvious curves, and is a straight road condition. Therefore, the vehicle is identified as a straight road.

[0121] If the radius of curvature is less than the curvature threshold, it indicates that the road the vehicle is currently on has a significant curve and is a curved road. Therefore, the vehicle determines the road type to be a straight road.

[0122] S23. Determine the vehicle's driving status based on road type, radius of curvature, and hand torque; the driving status is either takeover mode or automatic driving mode.

[0123] Driving state refers to the vehicle's control ownership status as determined during autonomous driving. In some embodiments, the driving state is either a takeover state or an autonomous driving state. A takeover state occurs when the vehicle determines that the driver intends to actively control the vehicle, and the driver has actually taken over steering control. In this case, the vehicle can disengage its lateral motion control function, and the driver takes over vehicle control. An autonomous driving state occurs when the driver merely holds the steering wheel normally without any intention to actively control the vehicle. In this case, the vehicle continues to drive automatically based on the lateral motion control function.

[0124] In some embodiments, when the road type is a straight road, the vehicle can classify the hand torque and determine the driving state by combining the torque level with the corresponding duration threshold. When the road type is a curved road, the vehicle can calculate a threshold correction coefficient using the radius of curvature, dynamically adjust the hand torque determination threshold according to the threshold correction coefficient, and then determine the driving state by following the rules of classification and duration verification.

[0125] exist Figure 2 In the illustrated embodiment, the vehicle distinguishes between straight and curved roads based on the road curvature radius, and comprehensively determines the vehicle's driving state by combining road type and steering wheel torque. This improves the accuracy of recognizing the driver's intention to take over and the vehicle's driving state, reduces misjudgments caused by a single judgment standard, and thus lowers the risk of abnormal start-stop of the vehicle's lateral motion control function. Therefore, the autonomous driving method for vehicles provided in this application improves the safety and operational stability of the vehicle during driving.

[0126] exist Figure 2 Based on the illustrated embodiment, the following, in conjunction with Figure 3 The process of determining the driving state of a vehicle in the embodiments of this application will be further described.

[0127] Figure 3 For a flowchart illustrating the process of determining driving status provided in this application embodiment, please refer to [link / reference]. Figure 3 The method may include the following steps:

[0128] S31. When the road type is a straight road, determine the driving state based on the hand torque.

[0129] In some embodiments, the vehicle determines its driving state based on hand torque in the following manner: determining the hand torque level of the vehicle at the current moment based on hand torque; determining the driving state based on the hand torque level.

[0130] The method for determining the hand torque level of a vehicle is as follows: determine the threshold range in which the hand torque falls; determine the level corresponding to the threshold range as the hand torque level.

[0131] The vehicle can determine its driving state based on the hand torque level as follows: when the hand torque level is greater than or equal to a preset threshold, the duration of the hand torque level is determined, and the driving state is determined based on the duration and the hand torque level; when the hand torque level is less than the preset threshold, the driving state is determined to be an automatic driving state.

[0132] Hand torque rating refers to the range of torque thresholds for different hand torque levels. Different hand torque ratings correspond to different torque threshold ranges, and the higher the hand torque rating, the larger the hand torque threshold range, indicating that the driver's intention to operate the vehicle is more obvious.

[0133] The threshold range is a pre-defined numerical interval used to divide the magnitude of hand torque. Each threshold range corresponds to a hand torque level. The preset threshold is a boundary value set for the hand torque level, used to distinguish between two situations: the driver is holding the steering wheel normally and there is an intention to take over the steering wheel.

[0134] Duration refers to the cumulative duration during which the vehicle detects that the current hand torque level remains unchanged. It is used to distinguish between instantaneous hand torque fluctuations and continuous active operations, preventing accidental small steering movements by the driver from being misinterpreted as an intention to take over the steering wheel.

[0135] For each threshold range among multiple threshold ranges, if the minimum value of the threshold range is less than or equal to the hand torque, and the maximum value of the threshold range is greater than the hand torque, then the threshold range is determined as the threshold range in which the hand torque is located, and the level corresponding to the threshold range is determined as the hand torque level.

[0136] If the hand torque level is greater than or equal to a preset threshold, it indicates that the driver may intend to take over the steering wheel. To avoid instantaneous fluctuations in hand torque caused by the driver's occasional slight steering, the vehicle can further determine the duration of the hand torque level and determine the driving state based on the duration and hand torque level.

[0137] The vehicle's driving status can be determined based on duration and hand torque level as follows: Based on the mapping relationship between hand torque level and duration threshold, and the hand torque level, determine the duration threshold corresponding to the hand torque level; determine the driving status based on the duration and duration threshold.

[0138] For example, suppose the mapping relationship between hand torque level and duration threshold is as shown in Table 1:

[0139] Table 1

[0140]

[0141] Assuming the hand torque is 3.2 Nm, the vehicle's hand torque level is determined to be 3, and the duration threshold is determined to be 150 ms.

[0142] In some embodiments, the vehicle determines the driving state based on the duration and a duration threshold as follows: if the duration is greater than or equal to the duration threshold, the driving state is determined to be a takeover state; if the duration is less than the duration threshold, the driving state is determined to be an autonomous driving state.

[0143] If the duration is greater than or equal to a duration threshold, it indicates that the steering operation corresponding to the hand torque from the driver's perspective is not an instantaneous disturbance, but rather reflects a sustained intention to actively drive the vehicle. Therefore, in this situation, the vehicle can be determined to be in a takeover state.

[0144] If the duration is less than the threshold, it indicates that the current torque change is only a temporary, occasional steering adjustment or torque fluctuation, and the driver has no intention of actively driving the vehicle. Therefore, in this case, the vehicle can be determined to be in an autonomous driving state.

[0145] Specifically, it can be combined with Figure 4 To understand. Figure 4 This is a schematic diagram illustrating the determination of driving status according to an embodiment of this application. Figure 4 As shown, the threshold ranges include 1.5Nm ≤ hand torque < 2.0Nm, 2.0Nm ≤ hand torque < 2.5Nm, 2.5Nm ≤ hand torque < 3.0Nm, 3.0Nm ≤ hand torque < 3.5Nm, and 3.5Nm ≤ hand torque. Specifically, the hand torque level corresponding to the threshold range of 1.5Nm ≤ hand torque < 2.0Nm is Level 1, the threshold range of 2.0Nm ≤ hand torque < 2.5Nm is Level 2, the threshold range of 2.5Nm ≤ hand torque < 3.0Nm is Level 3, the threshold range of 3.0Nm ≤ hand torque < 3.5Nm is Level 4, and the threshold range of 3.5Nm ≤ hand torque is Level 5.

[0146] Furthermore, the duration threshold for Level 1 is 250ms, for Level 2 it is 200ms, for Level 3 it is 150ms, for Level 4 it is 100ms, and for Level 5 it is 50ms.

[0147] In addition, the vehicle is equipped with timers A, B, C, D and E. Timer A is used to determine the duration of Level 1, timer B is used to determine the duration of Level 2, timer C is used to determine the duration of Level 3, timer D is used to determine the duration of Level 4 and timer E is used to determine the duration of Level 5.

[0148] Assuming the vehicle's hand torque is 2.8 Nm, the threshold range for hand torque is 2.5 Nm ≤ hand torque < 3.0 Nm. Therefore, the vehicle determines the hand torque level to be level 3. The vehicle determines the duration of hand torque level 3 to be 160 ms via timer C. Therefore, the vehicle determines the driving state to be in a takeover state (160 ms > 150 ms).

[0149] Assuming the vehicle's hand torque is 2.3 Nm, the threshold range for hand torque is 2.0 Nm ≤ hand torque < 2.5 Nm. Therefore, the vehicle determines the hand torque level to be Level 2. The vehicle determines the duration of hand torque level 2 to be 130 ms via timer B. Therefore, the vehicle determines the driving state to be in a takeover state (130 ms < 200 ms).

[0150] Optionally, the vehicle can determine multiple threshold ranges corresponding to the hand torque. For any threshold range, if the duration of the hand torque level corresponding to that threshold range is greater than or equal to a duration threshold, the vehicle determines the driving state to be in a takeover state. For each threshold range, if the duration of the hand torque level corresponding to that threshold range is less than a duration threshold, the vehicle determines the driving state to be in an autonomous driving state.

[0151] Among these, for each threshold range in the multiple threshold ranges, the threshold range is the threshold range in which the hand torque is located, or the maximum value of the threshold range is less than the hand torque.

[0152] S32. When the road type is a curve, determine the driving state based on the radius of curvature and hand torque.

[0153] In some embodiments, the vehicle determines its driving state based on the radius of curvature and hand torque as follows: a threshold adjustment coefficient is determined based on the radius of curvature; the driving state is then determined based on the threshold adjustment coefficient and hand torque.

[0154] The method for determining the threshold adjustment coefficient based on the radius of curvature of a vehicle can be as follows: determine the curvature range corresponding to the radius of curvature within multiple preset curvature ranges; determine the threshold adjustment coefficient based on the mapping relationship between the curvature range and the adjustment coefficient, as well as the curvature range.

[0155] The vehicle's driving status can be determined based on the threshold adjustment coefficient and the hand torque as follows: determine the hand torque level of the vehicle at the current moment based on the hand torque and the threshold adjustment coefficient; determine the driving status based on the hand torque level.

[0156] The threshold adjustment coefficient is used to adjust the threshold range corresponding to the hand torque level, thereby adapting to the objective situation that the steering torque naturally increases when the driver is cornering, and avoiding misjudgment of the state due to differences in road conditions. In some embodiments, the larger the curvature range, the larger the corresponding threshold adjustment coefficient.

[0157] The preset curvature range is a predefined range of curvature radius values ​​used to distinguish roads with different degrees of curvature.

[0158] For example, suppose that multiple preset curvature ranges include curvature radius < 1000m, 1000m ≤ curvature radius < 3000m, and 3000m ≤ curvature radius < 5000m. The mapping relationship between the curvature range and the adjustment coefficient is shown in Table 2.

[0159] Table 2

[0160]

[0161] Assuming a radius of curvature of 2500m, the vehicle determines the curvature range corresponding to the radius of curvature within multiple preset curvature ranges to be 1000m ≤ radius of curvature < 3000m. Therefore, based on the mapping relationship between the curvature range and the adjustment coefficient, and the curvature range itself, the vehicle determines the threshold adjustment coefficient to be 1.5.

[0162] In some embodiments, the vehicle determines its hand torque level at the current moment based on the hand torque and the threshold adjustment coefficient as follows: adjusting multiple preset threshold ranges according to the threshold adjustment coefficient to determine multiple adjustment threshold ranges; determining the threshold range in which the hand torque is located among the multiple adjustment threshold ranges; and determining the level corresponding to the threshold range as the hand torque level.

[0163] The threshold range adjustment is the threshold interval obtained by adjusting the preset threshold range based on the threshold adjustment coefficient.

[0164] For each preset threshold range, the vehicle can determine the minimum value of the adjustable threshold range by multiplying the minimum value of the preset threshold range by the threshold adjustment coefficient; and determine the maximum value of the adjustable threshold range by multiplying the maximum value of the preset threshold range by the threshold adjustment coefficient.

[0165] For example, assuming the preset threshold range is 1000m ≤ radius of curvature < 3000m and the threshold adjustment coefficient is 1.2, then the vehicle's determined adjustment threshold range is 1200m ≤ radius of curvature < 3600m.

[0166] The method by which the vehicle determines the threshold range of hand torque among multiple adjustment threshold ranges and determines the level corresponding to the threshold range as the hand torque level is the same as the method by which the vehicle determines the threshold range of hand torque among multiple preset threshold ranges and determines the level corresponding to the threshold range as the hand torque level, and will not be elaborated here.

[0167] For an explanation of how a vehicle determines its driving status based on the level of hand torque, please refer to [link / reference]. Figure 3 S301 in the illustrated embodiment will not be described in detail here.

[0168] exist Figure 3 In the illustrated embodiment, the vehicle employs multi-level thresholds to classify hand torque levels and combines these levels with duration and corresponding duration thresholds to comprehensively determine the driving state. This allows the vehicle to accurately distinguish between different operating conditions such as normal grip, slight steering, and active operation, thereby avoiding misjudgments caused by instantaneous torque fluctuations. Furthermore, for curved roads, the vehicle introduces a curvature radius matching threshold adjustment coefficient to dynamically adjust the torque judgment range, adapting to the objective changes in driver steering effort under different curved road conditions. This enables differentiated judgment for straight roads and curves, further improving the accuracy of driving state recognition, thereby ensuring reliable vehicle operation during autonomous driving and enhancing vehicle safety.

[0169] Figure 5 This is a schematic diagram of the structure of an autonomous driving device for a vehicle provided in an embodiment of this application. Please refer to... Figure 5 The vehicle's autonomous driving device 50 may include:

[0170] The first determining module 51 is used to determine the radius of curvature of the road where the vehicle is located and the hand torque of the vehicle; the hand torque is the rotational torque of the steering wheel of the vehicle.

[0171] The second determining module 52 is used to determine the road type of the road based on the radius of curvature, wherein the road type is either a curve type or a straight road type.

[0172] The processing module 53 is used to determine the driving state of the vehicle based on the road type, radius of curvature, and hand torque; the driving state is either a takeover state or an automatic driving state.

[0173] In some embodiments, the processing module 53 is specifically used for:

[0174] When the road type is straight, the driving state is determined based on the hand torque;

[0175] When the road type is a curve, the driving state is determined based on the radius of curvature and hand torque.

[0176] In some embodiments, the processing module 53 is specifically used for:

[0177] The hand torque level of the vehicle at the current moment is determined based on the hand torque.

[0178] Determine the driving status based on the hand torque level.

[0179] In some embodiments, the processing module 53 is specifically used for:

[0180] Determine the threshold range within which the hand torque falls;

[0181] The level corresponding to the threshold range is determined as the hand torque level.

[0182] In some embodiments, the processing module 53 is specifically used for:

[0183] When the hand torque level is greater than or equal to a preset threshold, determine the duration of the hand torque level, and determine the driving state based on the duration and the hand torque level.

[0184] If the hand torque level is less than the preset threshold, the driving state is determined to be automatic driving state.

[0185] In some embodiments, the processing module 53 is specifically used for:

[0186] Based on the mapping relationship between hand torque level and duration threshold, and the hand torque level, determine the duration threshold corresponding to the hand torque level;

[0187] The driving status is determined based on the duration and duration threshold.

[0188] In some embodiments, the processing module 53 is specifically used for:

[0189] If the duration is greater than or equal to the duration threshold, the driving state is determined to be a takeover state;

[0190] If the duration is less than the duration threshold, the driving state is determined to be autonomous driving state.

[0191] In some embodiments, the processing module 53 is specifically used for:

[0192] The threshold adjustment coefficient is determined based on the radius of curvature.

[0193] The driving state is determined based on the threshold adjustment coefficient and hand torque.

[0194] In some embodiments, the processing module 53 is specifically used for:

[0195] Determine the curvature range corresponding to the radius of curvature within multiple preset curvature ranges;

[0196] The threshold adjustment coefficient is determined based on the mapping relationship between the curvature range and the adjustment coefficient, as well as the curvature range.

[0197] In some embodiments, the processing module 53 is specifically used for:

[0198] The hand torque level of the vehicle at the current moment is determined based on the hand torque and the threshold adjustment coefficient;

[0199] Determine the driving status based on the hand torque level.

[0200] In some embodiments, the processing module 53 is specifically used for:

[0201] Multiple preset threshold ranges are adjusted based on threshold adjustment coefficients to determine multiple adjustment threshold ranges;

[0202] Determine the threshold range where the hand torque falls among multiple adjustment threshold ranges;

[0203] The level corresponding to the threshold range is determined as the hand torque level.

[0204] In some embodiments, the second determining module 52 is specifically used for:

[0205] If the radius of curvature is greater than or equal to the curvature threshold, the road type is determined to be a straight road type;

[0206] If the radius of curvature is less than the curvature threshold, the road type is determined to be a curve type.

[0207] The autonomous driving device 50 for vehicles provided in this application embodiment can execute the technical solutions in the above method embodiments. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0208] Figure 6 This is a structural schematic diagram of an autonomous driving device for a vehicle provided in an embodiment of this application. Figure 6 As shown, the autonomous driving device 60 of the vehicle may include: a memory 61 and at least one processor 62. Exemplarily, the memory 61 and the at least one processor 62 are interconnected via a bus 63.

[0209] Memory 61 is used to store program instructions;

[0210] At least one processor 62 is used to execute program instructions stored in the memory to cause the vehicle's autonomous driving device 60 to perform the vehicle's autonomous driving method in the above method embodiments.

[0211] Optionally, the aforementioned processor can be a central processing unit (CPU), a graphics processing unit (GPU), other general-purpose processors, a digital signal processor (DSP), or an application-specific integrated circuit (ASIC), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0212] The autonomous driving device 60 for vehicles provided in this application embodiment can execute the technical solutions in the above method embodiments. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0213] This application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the autonomous driving method for a vehicle as described in the above method embodiments.

[0214] This application provides a computer program product, including a computer program that, when executed by a processor, implements the autonomous driving method for vehicles involved in the above method embodiments.

[0215] This application provides a chip that stores a computer program. When the computer program is executed by the chip, it implements the autonomous driving method for vehicles described in the above method embodiments.

[0216] This application provides a chip module that stores a computer program. When the computer program is executed by the chip module, it implements the autonomous driving method for vehicles described in the above method embodiments.

[0217] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0218] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0219] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0220] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0221] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, Field Programmable Gate Array (FPGA), DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random-Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0222] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0223] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0224] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0225] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. An autonomous driving method for a vehicle, characterized in that, The method includes: Determine the radius of curvature of the road where the vehicle is located and the hand torque of the vehicle; the hand torque is the rotational torque on the steering wheel of the vehicle; The road type is determined based on the radius of curvature, and the road type is either a curved road or a straight road. The driving state of the vehicle is determined based on the road type, the radius of curvature, and the hand torque; the driving state is either a takeover state or an automatic driving state.

2. The method according to claim 1, characterized in that, Determining the driving status of the vehicle includes: When the road type is the straight road type, the driving state is determined based on the hand torque; When the road type is the curve type, the driving state is determined based on the radius of curvature and the hand torque.

3. The method according to claim 2, characterized in that, Determining the driving state based on the hand torque includes: The hand torque level of the vehicle at the current moment is determined based on the hand torque. The driving state is determined based on the stated hand torque level.

4. The method according to claim 3, characterized in that, Determining the hand torque level of the vehicle at the current moment based on the hand torque includes: Determine the threshold range within which the hand torque falls; The level corresponding to the threshold range is determined as the hand torque level.

5. The method according to claim 3 or 4, characterized in that, Determining the driving state based on the hand torque level includes: If the hand torque level is greater than or equal to a preset threshold, the duration of the hand torque level is determined, and the driving state is determined based on the duration and the hand torque level. If the hand torque level is less than the preset threshold, the driving state is determined to be an automatic driving state.

6. The method according to claim 5, characterized in that, Determining the driving state based on the duration and the hand torque level includes: Based on the mapping relationship between hand torque level and duration threshold, and the hand torque level, determine the duration threshold corresponding to the hand torque level; The driving state is determined based on the duration and the duration threshold.

7. The method according to claim 6, characterized in that, Determining the driving state based on the duration and the duration threshold includes: If the duration is greater than or equal to the duration threshold, the driving state is determined to be the takeover state; If the duration is less than the duration threshold, the driving state is determined to be the autonomous driving state.

8. The method according to any one of claims 2-4, characterized in that, Determining the driving state based on the radius of curvature and the hand torque includes: The threshold adjustment coefficient is determined based on the radius of curvature. The driving state is determined based on the threshold adjustment coefficient and the hand torque.

9. The method according to claim 8, characterized in that, Determine the threshold adjustment coefficient, including: Determine the curvature range corresponding to the radius of curvature within multiple preset curvature ranges; The threshold adjustment coefficient is determined based on the mapping relationship between the curvature range and the adjustment coefficient, as well as the curvature range.

10. The method according to claim 8, characterized in that, Determining the driving state based on the threshold adjustment coefficient and the hand torque includes: The hand torque level of the vehicle at the current moment is determined based on the hand torque and the threshold adjustment coefficient; The driving state is determined based on the hand torque level.

11. The method according to claim 10, characterized in that, Determining the hand torque level of the vehicle at the current moment based on the hand torque and the threshold adjustment coefficient includes: Multiple preset threshold ranges are adjusted according to the threshold adjustment coefficient to determine multiple adjustment threshold ranges; Determine the threshold range in which the hand torque falls among the plurality of adjustment threshold ranges; The level corresponding to the threshold range is determined as the hand torque level.

12. The method according to any one of claims 1-4, characterized in that, Determining the road type based on the radius of curvature includes: If the radius of curvature is greater than or equal to the curvature threshold, the road type is determined to be the straight road type; If the radius of curvature is less than the curvature threshold, the road type is determined to be the curve type.

13. An autonomous driving device for a vehicle, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to cause the at least one processor to perform the autonomous driving method of the vehicle according to any one of claims 1 to 12.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the autonomous driving method for the vehicle as described in any one of claims 1 to 12.

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