Vehicle driving steering assistance method, device, vehicle and storage medium

Abstract

This application discloses a vehicle steering assistance method, device, vehicle, and storage medium. The method comprises: collecting road data ahead of the vehicle; identifying the relative position between the vehicle and lane markings based on the road data, and obtaining the distance and current direction of travel between the vehicle and at least one preceding vehicle or obstacle; calculating the vehicle's steering risk factor based on the relative position, distance, current direction, and actual speed; and generating a steering reference indicator to the driver based on the steering risk factor. This ensures vehicle safety and comfort when implementing different steering strategies in different road scenarios.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle driving steering assistance method, device and vehicle. Background Art

[0002] At present, as the level of intelligent driving gradually increases, the road conditions and vehicle speeds supported by autonomous driving are also gradually increasing. Therefore, the requirements for steering systems and control methods are more stringent. For example, different steering strategies need to be implemented in different road scenarios, and the steering function and performance (safety and comfort) need to meet the requirements of different road conditions.

[0003] CN112977444A discloses a lane keeping advanced assisted driving control method, which specifically discloses determining a preview point based on the detection status of the lane line, calculating the center lane line based on the preview points of the two lane lines, and controlling the distance between the vehicle and the center lane line to be 0 as the control target. This solution lacks flexibility and uses the same solution for steering processing in different driving conditions, which can easily cause changes in the steering wheel control configuration, resulting in a poor driving experience, or extremely high performance requirements for the steering system, resulting in a significant increase in cost. Summary of the Invention

[0004] The present application provides a vehicle driving steering assistance method, device and vehicle to ensure the safety and comfort of the vehicle when executing different steering strategies in different road scenarios.

[0005] A first embodiment of the present application provides a vehicle driving steering assistance method, comprising the following steps:

[0006] Collect road data in front of the vehicle;

[0007] Identifying the relative position between the vehicle and the lane line based on the road data, and obtaining the distance and current travel direction between the vehicle and at least one preceding vehicle or obstacle; and

[0008] The turning risk coefficient of the vehicle is calculated according to the relative position, the distance, the current driving direction and the actual vehicle speed, and a turning reference index for prompting the driver is generated according to the turning risk coefficient.

[0009] Optionally, identifying the relative position between the vehicle and the lane line based on the road data, and obtaining the distance between the vehicle and at least one preceding vehicle or obstacle and the current driving direction, includes:

[0010] Processing the image information of the road data to obtain a position offset and an offset angle of the vehicle relative to the lane in which it is located;

[0011] The travel angle, relative speed, and distance to the at least one preceding vehicle or obstacle are calculated based on the position offset and the offset angle.

[0012] Optionally, the calculating the turning risk coefficient of the vehicle according to the relative position, the distance, the current driving direction and the actual speed includes:

[0013] Obtaining a vehicle speed signal of the vehicle from a CAN (Controller Area Network) network;

[0014] Calculating a current speed of the vehicle based on a motor speed and a transmission ratio of the drive motor;

[0015] Identify the actual speed of the vehicle according to the vehicle speed signal and the current vehicle speed:

[0016] When the speed calculated from the motor speed is below the first threshold, the speed calculated from the motor speed is used as the actual speed. When the speed calculated from the motor speed is above the first threshold, the difference between the two speeds is compared. If the difference does not exceed the threshold curve, the ABS speed signal is used as the actual speed. If the difference exceeds the threshold curve, the speed calculated from the motor speed is used. This is because at higher speeds, the motor speed, while less accurate, offers better stability. The first threshold is an arbitrary point set on the threshold curve.

[0017] In the threshold curve, the difference threshold increases as the vehicle speed increases.

[0018] The threshold curve is determined based on the vehicle speed and the deviation characteristics of the two speed sensors. It is used to determine the correctness of the vehicle speed. The difference between the two speeds is used as the judgment condition. Therefore, the speed difference needs to be appropriately amplified as the vehicle speed increases. The various thresholds that increase with the increase in vehicle speed are the threshold curve.

[0019] The present invention calculates the vehicle speed by integrating the wheel speed signal of the ABS, the vehicle speed signal and the motor speed, which can ensure the correctness of the vehicle speed and improve the speed accuracy, thereby improving the safety of automatic driving.

[0020] Optionally, calculating the turning risk coefficient of the vehicle according to the relative position, the distance, the current driving direction and the actual vehicle speed includes:

[0021] The steering risk coefficient is calculated using a risk assessment function based on the position offset, the offset angle, the driving angle, the relative speed, the distance, and the actual vehicle speed.

[0022] Optionally, it also includes:

[0023] The target steering sensitivity of the vehicle is matched according to the steering reference index, so as to control the steering speed of the vehicle using the target steering sensitivity. A second embodiment of the present application provides a driving steering assist device for a vehicle, comprising:

[0024] A collection module, used to collect road data in front of the vehicle;

[0025] an acquisition module, configured to identify the relative position between the vehicle and the lane line based on the road data, and acquire the distance between the vehicle and at least one preceding vehicle or obstacle and the current direction of travel; and

[0026] A generating module is used to calculate the turning risk coefficient of the vehicle according to the relative position, the distance, the current driving direction and the actual vehicle speed, and to generate a turning reference index to prompt the driver according to the turning risk coefficient.

[0027] Optionally, the acquisition module includes:

[0028] a processing unit, configured to process the image information of the road data to obtain a position offset and an angle of the vehicle relative to the lane in which the vehicle is located;

[0029] A calculation unit is used to calculate the travel angle, relative speed and distance to the at least one preceding vehicle or obstacle based on the position offset and the angle.

[0030] Optionally, the generating module includes:

[0031] an acquiring unit, configured to acquire a speed signal of the vehicle from a CAN network;

[0032] a first calculation unit, configured to calculate a current speed of the vehicle according to a motor speed and a transmission ratio of the drive motor;

[0033] An identification unit is used to identify the actual speed of the vehicle based on the vehicle speed signal and the current vehicle speed.

[0034] Optionally, the generating module further includes:

[0035] The second calculation unit is configured to calculate the steering risk coefficient using a risk assessment function based on the position offset, the angle, the driving angle, the relative speed, the distance, and the actual vehicle speed.

[0036] Optionally, it also includes:

[0037] A control module is configured to match a target steering sensitivity of the vehicle according to the steering reference index, so as to control a steering speed of the vehicle using the target steering sensitivity.

[0038] A third embodiment of the present application provides a vehicle, which includes the above-mentioned vehicle driving steering assistance device.

[0039] In this way, the road data in front of the vehicle can be collected, and the relative position between the vehicle and the lane line can be identified based on the road data, and the distance and current driving direction between the vehicle and at least one vehicle or obstacle in front can be obtained. The steering risk coefficient of the vehicle can be calculated based on the relative position, distance, current driving direction and actual speed, and a steering reference indicator can be generated to prompt the driver based on the steering risk coefficient to ensure the safety and comfort of the vehicle when executing different steering strategies in different road scenarios.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. Optimized steering control algorithm. This invention uses "six variables" (position offset, offset angle, current vehicle's driving angle relative to the vehicle ahead or obstacle, relative speed and distance, and current vehicle's actual speed) to derive the steering risk factor. Based on these variables, the steering risk factor is calculated. For operating conditions with high risk factors, steering sensitivity can be improved, resulting in faster steering when the risk factor is high. The control lead can be increased based on the steering risk factor, allowing for early avoidance of certain dangerous operating conditions, reducing the probability of risk occurrence and improving lane keeping safety.

[0042] 2. It avoids high-frequency control of the steering system, and avoids the discomfort of steering jitter and high-frequency changes. For traditional technical solutions that do not adopt the present invention, the steering system needs to maintain a highly sensitive state at all times to meet the demand for rapid steering response. It needs to be very sensitive to changes in the control angle variables, which will cause problems with high-frequency control and even cause jitter. The present invention calculates the steering risk coefficient based on various variables. When the steering risk coefficient is not high, the control of the steering target can have a lower sensitivity, and the lack of high-frequency control will not affect safety.

[0043] 3. While optimizing control effectiveness, this technology reduces the precision requirements for the steering system for autonomous driving, lowering the technical and cost thresholds for supported vehicle models. Conventional solutions that do not employ this invention require the steering system to remain highly sensitive at all times to meet the demand for rapid steering response. This requires extreme sensitivity to changes in the control angle variable. This sensitivity requires the ability to recognize and execute control even for minute steering angles, which demands even higher precision.

[0044] The present invention calculates a steering risk factor based on various variables. When the steering risk factor is low, the steering target can be controlled with low sensitivity, thus eliminating the need for particularly high precision. However, when the steering risk factor is high, a relatively large steering angle is required, thus also eliminating the need for particularly high precision. Therefore, the present invention uses the steering risk factor to differentiate operating conditions, avoiding the need for extremely high precision in the steering mechanism.

[0045] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0047] Figure 1 This is a flowchart of a driving steering assistance method provided according to an embodiment of the present application;

[0048] Figure 2 is a block diagram of a driving steering assistance system according to an embodiment of the present application;

[0049] Figure 3 is a flowchart of a driving steering assistance method according to one embodiment of the present application;

[0050] Figure 4 2 is an exemplary diagram of a driving steering assist device according to an embodiment of the present application. Implementation Method

[0051] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0052] The following describes the vehicle driving steering assistance method, device and vehicle of the embodiment of the present application with reference to the accompanying drawings. In response to the problem of vehicle safety and comfort when executing different steering strategies in different road scenarios mentioned in the background technology center above, the present application provides a vehicle driving steering assistance method, in which the road data in front of the vehicle can be collected, and the relative position between the vehicle and the lane line can be identified based on the road data, and the distance and current driving direction between the vehicle and at least one vehicle or obstacle in front can be obtained, and the steering risk coefficient of the vehicle can be calculated based on the relative position, distance, current driving direction and actual vehicle speed, and a steering reference indicator to prompt the driver can be generated based on the steering risk coefficient, so as to ensure the safety and comfort of the vehicle when executing different steering strategies in different road scenarios. Example

[0053] Figure 1 A flowchart of a vehicle driving steering assistance method provided in an embodiment of the present application.

[0054] In this embodiment, Figure 2 As shown, Figure 2 This is a block diagram of a system involved in a vehicle steering assistance method according to an embodiment of the present application. The system includes: an intelligent driving domain controller (ADU), a front high-definition camera, a front millimeter-wave radar, an anti-lock braking system (ABS), a motor controller (MCU), and an electronic power steering control module (EPS). The intelligent driving domain controller is connected to the vehicle through a hard line ( Figure 2 The front high-definition camera and the front millimeter-wave radar are connected to the intelligent driving domain controller through CAN ( Figure 2 The system (shown by the dashed lines) is connected to the anti-lock braking system (ABS), motor controller (MCU), and electric steering (EPS). This system utilizes an intelligent driving domain controller as its core module. It determines the current driving state based on information from sensors and other modules and controls the steering gear via CAN to execute steering.

[0055] like Figure 1 As shown, the vehicle driving steering assistance method includes the following steps:

[0056] In step S101 , road data in front of the vehicle is collected.

[0057] Specifically, the embodiment of the present application can collect road data in front of the vehicle through a front high-definition camera.

[0058] In step S102, the relative position between the vehicle and the lane line is identified based on the road data, and the distance between the vehicle and at least one vehicle ahead or obstacle and the current driving direction are obtained.

[0059] Optionally, in some embodiments, the relative position between the vehicle and the lane line is identified based on the road data, and the distance between the vehicle and at least one vehicle ahead or obstacle and the current driving direction are obtained, including: processing the image information of the road data to obtain the position offset and angle of the vehicle relative to the lane; and calculating the driving angle, relative speed and distance to at least one vehicle ahead or obstacle based on the position offset and angle.

[0060] Specifically, the embodiment of the present application can analyze and process the image data collected in the above step S101 through the ADU, calculate the position offset and angle of the current vehicle relative to the lane it is in, and analyze the driving angle, relative speed and distance of the current vehicle relative to the vehicle in front or obstacle.

[0061] Furthermore, the embodiment of the present application can also collect data from the front millimeter-wave radar through the ADU to calculate the current vehicle's driving angle, relative speed, and distance relative to the vehicle or obstacle in front, and fuse it with the data from the camera's collected signal analysis to determine the current vehicle's driving angle, relative speed, and distance relative to the vehicle or obstacle in front.

[0062] In step S103, the vehicle's turning risk coefficient is calculated based on the relative position, distance, current driving direction and actual vehicle speed, and a turning reference index is generated to prompt the driver based on the turning risk coefficient.

[0063] As a possible implementation method, in some embodiments, the vehicle's turning risk coefficient is calculated based on the relative position, distance, current driving direction and actual speed, including: obtaining the vehicle's speed signal from the CAN network; calculating the vehicle's current speed based on the motor speed and transmission ratio of the drive motor; and identifying the vehicle's actual speed based on the speed signal and the current speed.

[0064] It should be understood that the ADU of the embodiment of the present application can obtain the ABS wheel speed signal and vehicle speed signal, as well as the motor speed of the MCU through CAN, calculate the vehicle speed based on the transmission ratio, and comprehensively judge the current actual vehicle speed from the ABS vehicle speed signal.

[0065] Furthermore, in some embodiments, calculating the vehicle's steering risk coefficient based on the relative position, distance, current driving direction and actual vehicle speed also includes: calculating the steering risk coefficient using a risk assessment function based on the position offset, angle, driving angle, relative speed and distance, and actual vehicle speed.

[0066] Specifically, the embodiment of the present application can create a risk assessment function and a risk assessment coefficient based on six variables as independent variables: the position offset X1 of the current vehicle relative to the lane, the offset angle X2, the driving angle X3 of the current vehicle relative to the vehicle in front or obstacle, the relative speed X4 and distance X5, and the actual speed X6 of the current vehicle. The coefficient value range is 0~1, where 0 means no risk and 1 means extreme risk.

[0067] In one embodiment, the following risk assessment factors may be established:

[0068] Z=K1(aX1+bX2)+K2(cX3+dX4+eX5)+K3X6

[0069] Among them, K1, K2, K3, a, b, c, d and e are setting parameters.

[0070] Furthermore, in some embodiments, the method further includes: matching a target steering sensitivity of the vehicle according to a steering reference index, so as to control a steering speed of the vehicle using the target steering sensitivity.

[0071] Adjust and calibrate the values of each parameter in the above-mentioned risk assessment coefficient, substitute different parameter values into the formula, and calculate different coefficient values. Different coefficient values correspond to different vehicle steering sensitivity requirements, which are comprehensively formulated based on the safety and comfort of autonomous driving.

[0072] Different hazard assessment coefficient values correspond to different vehicle steering sensitivity requirements. When the sensitivity requirement is high, the vehicle will turn quickly when the target angle and the actual angle reach the difference threshold. When the sensitivity requirement is low, the steering sensitivity and steering speed will be reduced when the target angle and the actual angle are lower than the difference threshold.

[0073] The difference threshold between the target turning angle and the actual turning angle is used as the judgment condition for quick steering. This threshold needs to be calibrated according to the needs of quick steering. Each manufacturer can set this threshold according to its own needs and preferences.

[0074] Therefore, the EPS can be controlled to execute steering according to the risk assessment coefficient. The more dangerous the situation is, the more sensitive the steering control and the faster the steering speed, which can better ensure safety; the safer the situation is, the slower the steering control and the more comfortable it can be.

[0075] In order to enable those skilled in the art to further understand the vehicle driving steering assistance method of the embodiment of the present application, it is described in detail below with reference to specific embodiments.

[0076] like Figure 3 As shown, the vehicle driving steering assistance method includes the following steps:

[0077] S301, when the vehicle is driving normally, determine whether it has entered the intelligent driving state. If so, execute step S303, otherwise, execute step S302.

[0078] S302, shielding the intelligent steering control function to ensure manual driving safety, and jumping to step S301.

[0079] S303: Calculate the position offset and angle of the current vehicle relative to the lane it is in, and calculate the driving angle, relative speed, and distance of the current vehicle relative to the vehicle or obstacle in front. Then, comprehensively determine the actual vehicle speed based on the ABS and MCU feedback vehicle speed and motor speed.

[0080] Specifically, the ADU of the embodiment of the present application hardwires image data collected by the front high-definition camera for analysis and processing, and calculates the position offset and angle of the current vehicle relative to the lane it is in; the DU analyzes the driving angle, relative speed and distance of the vehicle relative to the vehicle or obstacle in front through the image of the front high-definition camera, and the ADU calculates the driving angle, relative speed and distance of the vehicle relative to the vehicle or obstacle in front through the signal of the front millimeter-wave radar, and integrates the data with the signal analysis collected by the camera, and comprehensively judges the driving angle, relative speed and distance of the vehicle relative to the vehicle or obstacle in front; the ADU obtains the ABS wheel speed signal and vehicle speed signal through CAN, obtains the motor speed of the MCU through CAN, calculates the vehicle speed according to the transmission ratio, and comprehensively judges the current actual vehicle speed.

[0081] S304: Calculate the risk assessment coefficient according to the risk assessment function.

[0082] S305: Adjust steering sensitivity and speed according to the risk assessment coefficient.

[0083] Therefore, based on the image data collected by the front high-definition camera, the direction and position of the vehicle relative to the road (that is, the angle between the vehicle and the lane line and the deviation of the vehicle from the lane line) are judged. The direction and distance of the vehicle relative to the vehicle in front are measured based on the millimeter-wave radar, and combined with the vehicle speed collected by ABS, an evaluation function for assessing steering hazard is created. This is used as an important reference indicator to guide steering, improve the intelligence level, comfort and safety of the steering system, and support the needs of various road conditions under high-level intelligent driving.

[0084] According to the vehicle driving steering assistance method proposed in the embodiment of the present application, road data in front of the vehicle can be collected, and the relative position between the vehicle and the lane line can be identified based on the road data, and the distance and current driving direction between the vehicle and at least one vehicle or obstacle in front can be obtained. The steering risk coefficient of the vehicle is calculated based on the relative position, distance, current driving direction and actual vehicle speed, and a steering reference indicator is generated to prompt the driver based on the steering risk coefficient, so as to ensure the safety and comfort of the vehicle when executing different steering strategies in different road scenarios. Example

[0085] A vehicle driving steering assist device according to an embodiment of the present application is described with reference to the accompanying drawings.

[0086] Figure 4 It is a block diagram of a driving steering assist device for a vehicle according to an embodiment of the present application.

[0087] like Figure 4 As shown, the vehicle driving steering assistance device 10 includes: a collection module 100 , an acquisition module 200 and a generation module 300 .

[0088] The acquisition module 100 is used to collect road data in front of the vehicle;

[0089] The acquisition module 200 is used to identify the relative position between the vehicle and the lane line based on the road data, and obtain the distance between the vehicle and at least one vehicle ahead or obstacle and the current driving direction; and

[0090] The generating module 300 is used to calculate the vehicle's steering risk coefficient based on the relative position, distance, current driving direction and actual vehicle speed, and to generate a steering reference indicator to prompt the driver based on the steering risk coefficient.

[0091] Optionally, in some embodiments, the acquisition module 200 includes:

[0092] a processing unit, configured to process image information of the road data to obtain a position offset and angle of the vehicle relative to the lane in which it is located;

[0093] A calculation unit is used to calculate the driving angle, relative speed and distance to at least one preceding vehicle or obstacle based on the position offset and the angle.

[0094] Optionally, in some embodiments, the generating module 300 includes:

[0095] An acquisition unit, used for acquiring a vehicle speed signal from a CAN network;

[0096] a first calculation unit, configured to calculate a current speed of the vehicle according to a motor speed and a transmission ratio of the drive motor;

[0097] The identification unit is used to identify the actual speed of the vehicle based on the vehicle speed signal and the current vehicle speed.

[0098] Optionally, in some embodiments, the generating module 300 further includes:

[0099] The second calculation unit is used to calculate the steering risk coefficient using a risk assessment function based on the position offset, angle, driving angle, relative speed and distance, and actual vehicle speed.

[0100] Optionally, in some embodiments, the method further includes:

[0101] The control module is used to match the target steering sensitivity of the vehicle according to the steering reference index, so as to control the steering speed of the vehicle using the target steering sensitivity.

[0102] It should be noted that the aforementioned explanation of the embodiment of the vehicle driving steering assistance method is also applicable to the vehicle driving steering assistance device of this embodiment, and will not be repeated here.

[0103] According to the vehicle driving steering assistance device proposed in the embodiment of the present application, road data in front of the vehicle can be collected, and the relative position between the vehicle and the lane line can be identified based on the road data, and the distance and current driving direction between the vehicle and at least one vehicle or obstacle in front can be obtained. The steering risk coefficient of the vehicle is calculated based on the relative position, distance, current driving direction and actual vehicle speed, and a steering reference indicator is generated to prompt the driver based on the steering risk coefficient, so as to ensure the safety and comfort of the vehicle when executing different steering strategies in different road scenarios. Example

[0104] In addition, an embodiment of the present application further provides a vehicle, comprising:

[0105] Steering system, used to drive the vehicle to steer;

[0106] one or more processors;

[0107] a memory for storing one or more programs;

[0108] When one or more programs are executed by one or more processors, the one or more processors implement the driving steering assistance method of embodiment 1.

[0109] According to the vehicle of the embodiment of the present application, it is possible to collect road data in front of the vehicle, identify the relative position between the vehicle and the lane line based on the road data, obtain the distance and current driving direction between the vehicle and at least one vehicle or obstacle in front, calculate the steering risk coefficient of the vehicle based on the relative position, distance, current driving direction and actual vehicle speed, and generate a steering reference indicator to prompt the driver based on the steering risk coefficient, so as to ensure the safety and comfort of the vehicle when executing different steering strategies in different road scenarios. Example

[0110] An embodiment of the present invention further provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the vehicle driving steering assistance method in embodiment 1.

[0111] In some embodiments, the storage medium stores computer-executable instructions, which are executed by one or more control processors, for example, by a processor in the vehicle of Example 3, so that the one or more processors can execute the driving steering assistance method in the above-mentioned Example 1.

[0112] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0113] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0114] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0115] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logical functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0116] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

Claims

1. A vehicle steering assist method, characterized in that: The following steps are involved: Collect road data in front of the vehicle; Identifying the relative position between the vehicle and a lane line based on the road data, and obtaining the distance and current travel direction between the vehicle and at least one preceding vehicle or obstacle; as well as Calculating a steering risk coefficient of the vehicle according to the relative position, the distance, the current driving direction, and the actual vehicle speed, and generating a steering reference indicator to prompt the driver according to the steering risk coefficient; The identifying the relative position between the vehicle and the lane line according to the road data, and obtaining the distance between the vehicle and at least one preceding vehicle or obstacle and the current traveling direction, includes: Processing the image information of the road data to obtain a position offset and an offset angle of the vehicle relative to the lane in which it is located; Calculating a travel angle, a relative speed, and the distance to the at least one preceding vehicle or obstacle based on the position offset and the offset angle; The calculating the turning risk coefficient of the vehicle according to the relative position, the distance, the current driving direction and the actual vehicle speed includes: Calculating the steering risk coefficient based on the position offset, the offset angle, the driving angle, the relative speed, the distance, and the actual vehicle speed; A risk assessment function is created based on six variables: the position offset of the current vehicle relative to the lane, the offset angle, the driving angle of the current vehicle relative to the vehicle in front or obstacle, the relative speed and distance, and the actual speed of the current vehicle. The steering risk coefficient is calculated using the created risk assessment function. The created risk assessment function is: Z=K1(aX1+bX2)+K2(cX3+dX4+eX5)+K3X6 Among them, Z is the turning risk factor; K1, K2, K3, a, b, c, d and e are setting parameters; X1 is the position offset of the current vehicle relative to the lane, X2 is the offset angle of the current vehicle relative to the lane, X3 is the driving angle of the current vehicle relative to the vehicle or obstacle in front, X4 is the relative speed of the current vehicle relative to the vehicle or obstacle in front, X5 is the distance of the current vehicle relative to the vehicle or obstacle in front, and X6 is the actual speed of the current vehicle.

2. The method according to claim 1, characterized in that The calculating the turning risk coefficient of the vehicle according to the relative position, the distance, the current driving direction and the actual vehicle speed includes: Obtaining an ABS vehicle speed signal of the vehicle from a CAN network; Calculating a current speed of the vehicle based on a motor speed and a transmission ratio of the drive motor; The actual vehicle speed is obtained based on the ABS vehicle speed signal and the current vehicle speed.

3. The method according to claim 1 or 2, characterized in that Also includes: A target steering sensitivity of the vehicle is matched according to the steering reference index, so as to control a steering speed of the vehicle using the target steering sensitivity.

4. A vehicle steering assist device, characterized in that: include: A collection module, used to collect road data in front of the vehicle; an acquisition module, configured to identify the relative position between the vehicle and the lane line based on the road data, and acquire the distance between the vehicle and at least one preceding vehicle or obstacle and the current traveling direction; as well as a generating module, configured to calculate a steering risk coefficient of the vehicle according to the relative position, the distance, the current driving direction, and the actual vehicle speed, and to generate a steering reference indicator to prompt the driver according to the steering risk coefficient; The acquisition module includes: a processing unit, configured to process the image information of the road data to obtain a position offset and an offset angle of the vehicle relative to the lane in which the vehicle is located; a calculation unit, configured to calculate a travel angle, a relative speed, and the distance to the at least one preceding vehicle or obstacle based on the position offset and the offset angle; The generation module includes: an acquiring unit, configured to acquire a speed signal of the vehicle from a CAN network; a first calculation unit, configured to calculate a current speed of the vehicle according to a motor speed and a transmission ratio of the drive motor; an identification unit, configured to identify an actual vehicle speed of the vehicle based on the vehicle speed signal and the current vehicle speed; The second calculation unit is configured to calculate the steering risk coefficient using a risk assessment function based on the position offset, the offset angle, the driving angle, the relative speed, the distance, and the actual vehicle speed; the risk assessment function created is: Z=K1(aX1+bX2)+K2(cX3+dX4+eX5)+K3X6 Among them, Z is the turning risk factor; K1, K2, K3, a, b, c, d and e are setting parameters; X1 is the position offset of the current vehicle relative to the lane, X2 is the offset angle of the current vehicle relative to the lane, X3 is the driving angle of the current vehicle relative to the vehicle or obstacle in front, X4 is the relative speed of the current vehicle relative to the vehicle or obstacle in front, X5 is the distance of the current vehicle relative to the vehicle or obstacle in front, and X6 is the actual speed of the current vehicle.

5. A vehicle, characterized in that: include: Steering system, used to drive the vehicle to steer; one or more processors; a memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the driving steering assistance method as claimed in claim 1 or 2.

6. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the driving steering assistance method according to claim 1 or 2 is implemented.

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