Man-machine co-driving control method and device and vehicle

Abstract

The present disclosure relates to the technical field of assisted driving, and particularly relates to a man-machine co-driving control method and device and a vehicle. The present disclosure predicts the user's intention to take over based on the steering wheel control parameters, obtains the corresponding intelligent driving control coefficient, and makes the intelligent driving control coefficient participate in generating the target control parameters for controlling the vehicle steering system, so that the control degree of the intelligent driving steering request parameter output by the intelligent driving in the target control parameters meets the user's intention to take over, solving the problem of the intelligent driving system and the driver competing for the steering wheel, while considering safety, comfort and compliance, and realizing torque intelligent distribution of man-machine co-driving through the cooperation of the upper and lower computers, and improving the flexibility of intelligent driving.

Description

Technical Field

[0001] This disclosure relates to the field of driver assistance technology, and in particular to a human-machine co-driving control method, device and vehicle. Background Technology

[0002] With the continuous development of technology, intelligent driving functions are being applied to more and more vehicles. Intelligent driving functions can intelligently control the vehicle's steering system based on road conditions in the direction of travel, allowing the vehicle to travel along lane lines or a predetermined route. Current regulations, for safety reasons, do not allow the driver to take their hands off the steering wheel for fully autonomous driving with intelligent driving functions; therefore, there will be instances where the driver and driver assistance systems jointly intervene in the vehicle's steering system.

[0003] To avoid excessive resistance between the driver and the intelligent driving function in controlling the steering system, a takeover threshold is usually set. When the driver applies torque to the steering wheel exceeding the takeover threshold, the intelligent driving function automatically disengages and switches to manual driving mode. However, the appropriateness of the takeover threshold setting directly affects the driver's driving experience. If the takeover threshold is set too low, the intelligent driving function will disengage too quickly in an emergency, failing to effectively utilize active safety features. If the takeover threshold is set too high, it will make it difficult for the driver to take over, failing to meet the driver's expectations and causing a sharp decrease in steering wheel feel when the intelligent driving function disengages.

[0004] Therefore, existing intelligent driving systems have relatively rigid and inflexible control over the steering system. Summary of the Invention

[0005] To address the aforementioned technical problems, this disclosure provides a human-machine co-driving control method, device, and vehicle to improve the flexibility of intelligent driving.

[0006] In a first aspect, embodiments of this disclosure provide a human-machine co-driving control method, including:

[0007] Obtain the user's steering wheel control parameters;

[0008] The host computer makes a decision on the user's takeover intention based on the steering wheel control parameters, and obtains the intelligent driving control coefficient corresponding to the user's takeover intention. The intelligent driving control coefficient is inversely proportional to the intensity of the user's takeover intention.

[0009] The host computer obtains intelligent driving steering request parameters based on road condition information;

[0010] Send the intelligent driving control coefficients and intelligent driving steering request parameters to the lower-level machine;

[0011] The lower-level control unit compensates for the steering wheel control parameters based on the intelligent driving control coefficients and the intelligent driving steering request parameters to obtain the target control parameters;

[0012] The lower-level computer controls the vehicle steering system to perform steering actions based on the target control parameters.

[0013] In some embodiments, the steering wheel control parameters include manual torque, and the host computer makes a user takeover intention decision based on the steering wheel control parameters to obtain the intelligent driving control coefficient corresponding to the user takeover intention, including:

[0014] When the manual torque is greater than the minimum value of the preset torque range and less than the maximum value of the preset torque range, the manual torque is normalized based on the preset torque range to obtain the intelligent driving control coefficient; or...

[0015] When the manual torque is less than or equal to the lowest value of the preset torque range, the intelligent driving control coefficient is determined to be the preset maximum coefficient; or...

[0016] When the manual torque is greater than or equal to the highest value of the preset torque range, the intelligent driving control coefficient is determined to be the preset minimum coefficient.

[0017] In some embodiments, the steering wheel control parameters include steering wheel speed. When the hand torque is less than or equal to the lowest value of a preset torque range, the intelligent driving control coefficient is determined to be a preset maximum coefficient, including:

[0018] The coefficient increment rate is calculated based on the steering wheel speed, the preset speed threshold, and the preset increment step size.

[0019] When the manual torque jumps from the preset torque range to less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient increment rate until the intelligent driving control coefficient reaches the preset maximum coefficient, or the manual torque is greater than the minimum value of the preset torque range.

[0020] In some embodiments, the steering wheel control parameters include steering wheel speed. When the hand torque is greater than or equal to the highest value of a preset torque range, the intelligent driving control coefficient is determined to be a preset minimum coefficient, including:

[0021] The coefficient decay rate is calculated based on the steering wheel speed, the preset speed threshold, and the preset decay step size.

[0022] When the manual torque jumps from the preset torque range to a value greater than or equal to the maximum value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient decay rate until the intelligent driving control coefficient reaches the preset minimum coefficient, or the manual torque is less than the maximum value of the preset torque range.

[0023] In some embodiments,

[0024] When the manual torque changes from the preset torque range to a value greater than or equal to the highest value of the preset torque range, the host computer controls the target control parameter at the current moment as the intelligent driving steering request parameter.

[0025] In some embodiments, the steering wheel control parameters include hand torque, and the lower control unit compensates for the steering wheel control parameters based on the intelligent driving control coefficient and the intelligent driving steering request parameters to obtain target control parameters, including:

[0026] The intelligent driving assistance parameters are obtained by multiplying the intelligent driving control coefficient and the intelligent driving steering request parameter.

[0027] The target control parameters are obtained by calculating the sum of the intelligent driving assistance parameters and the manual torque.

[0028] In some embodiments, controlling the vehicle steering system to perform steering actions via a lower-level computer based on the target control parameters includes:

[0029] When the intelligent driving control coefficient is less than a preset coefficient threshold, the integral output contribution is determined based on the intelligent driving control coefficient, and the integral output contribution is proportional to the intelligent driving control coefficient.

[0030] The integral output contribution of the target control parameters to the vehicle steering system is limited based on the integral output contribution.

[0031] In some embodiments, the method further includes:

[0032] When the intelligent driving function unexpectedly exits, obtain the intelligent driving control coefficient at the moment before the unexpected exit of the intelligent driving function;

[0033] Determine the intelligent driving transition speed based on the vehicle's driving style mode;

[0034] The host computer controls the intelligent driving control coefficient based on the intelligent driving transition speed, decreasing the output of the intelligent driving control coefficient at the moment before the intelligent driving function unexpectedly exits, until the intelligent driving control coefficient reaches the preset minimum coefficient.

[0035] Secondly, embodiments of this disclosure provide a human-machine co-driving control device, comprising:

[0036] The acquisition module is used to acquire the user's steering wheel control parameters.

[0037] The first control module is used to control the host computer to make a user takeover intention decision based on the steering wheel control parameters, and obtain the intelligent driving control coefficient corresponding to the user takeover intention. The intelligent driving control coefficient is inversely proportional to the intensity of the user takeover intention.

[0038] The second control module is used to control the host computer to obtain intelligent driving steering request parameters based on road condition information;

[0039] The sending module is used to send the intelligent driving control coefficients and intelligent driving steering request parameters to the lower-level machine;

[0040] The third control module is used to control the lower-level machine to compensate the steering wheel control parameters based on the intelligent driving control coefficient and the intelligent driving steering request parameters to obtain the target control parameters;

[0041] The fourth control module is used to control the vehicle steering system to perform steering actions via a lower-level computer based on the target control parameters.

[0042] Thirdly, embodiments of this disclosure provide a vehicle, including:

[0043] Memory;

[0044] processor;

[0045] The memory stores executable program code, and the processor is used to call and execute the executable program code to perform the method as described in the first aspect.

[0046] The human-machine co-driving control method, device, and vehicle provided in this disclosure predict the user's takeover intention based on steering wheel control parameters to obtain corresponding intelligent driving control coefficients. These intelligent driving control coefficients are then used to generate the target control parameters for the final control of the vehicle's steering system. This ensures that the control degree of the intelligent driving steering request parameters output by the intelligent driving system in the target control parameters matches the user's takeover intention, thus solving the problem of the intelligent driving system and the driver competing for the steering wheel. It also takes into account safety, comfort, and compliance. Combined with upper and lower computer collaboration, it achieves intelligent torque distribution in human-machine co-driving, improving the flexibility of intelligent driving. Attached Figure Description

[0047] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0048] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic diagram of a vehicle system architecture;

[0050] Figure 2This is a schematic diagram of a human-machine co-driving system.

[0051] Figure 3 A flowchart of the human-machine co-driving control method provided in this embodiment of the disclosure;

[0052] Figure 4 A schematic diagram of a vehicle control system provided in an embodiment of this disclosure;

[0053] Figure 5 This is a schematic diagram of the host computer algorithm provided in an embodiment of this disclosure;

[0054] Figure 6 This is a schematic diagram of the lower-level machine algorithm provided in the embodiments of this disclosure;

[0055] Figure 7 This is a schematic diagram of the structure of the human-machine co-driving control device provided in the embodiments of this disclosure;

[0056] Figure 8 This is a schematic diagram of the structure of a vehicle provided in an embodiment of the present disclosure;

[0057] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0058] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0059] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0060] The intelligent driving system, as the host computer, is the overall device for assisted driving of automobiles to realize a series of longitudinal movements and lateral controls. It sends control commands to each component system in real time, and corrects its own control commands by monitoring the operating status of each component system, so as to achieve the purpose of closed-loop control of vehicle body posture and movement. Figure 1 This is a schematic diagram of a vehicle system architecture, such as Figure 1 As shown, the main performance components of the intelligent driving system are connected to the steering system, power system, and braking system. The steering system mainly assists the intelligent driving system in controlling lateral functions, while the power system and braking system mainly assist the intelligent driving system in achieving longitudinal movement. The two networks of lateral control and longitudinal movement are connected through the network communication system provided by the gateway.

[0061] Due to relevant regulations and safety considerations, the driver is not allowed to take off the steering wheel and drive the vehicle automatically during the assisted driving stage. This results in the phenomenon of the driver and the intelligent driving system jointly intervening in the steering system, which involves whether the steering is smooth or meets the driver's psychological expectations when the driver takes over the steering.

[0062] Figure 2 This is a schematic diagram of a human-machine co-driving system. (Example) Figure 2 As shown, the power steering assist obtained by the driver through hand force and the power steering assist obtained by the intelligent driving system through control commands are two separate links, resulting in two phenomena: First, to allow the driver easy to take over, the intelligent driving system sets a lower fixed hand force threshold for disengagement. In emergencies, the intelligent driving system cannot effectively perform its active safety functions, leading to user complaints. Second, when the intelligent driving system sets a higher fixed hand force threshold, the driver finds it difficult to take over, which does not meet the driver's expectations, resulting in a phenomenon where the intelligent driving system seems to seize control of the steering wheel, leading to a poor driving feel. Furthermore, regardless of which phenomenon occurs, the steering wheel feels heavy before the intelligent driving system disengages and light afterward, creating a strong sense of boundary for the driver and affecting the driving experience.

[0063] To address the aforementioned issues, this disclosure provides a human-machine co-driving control method, which will be described below with reference to specific embodiments.

[0064] Figure 3 This is a flowchart illustrating a human-machine co-driving control method provided in an embodiment of this disclosure. This method can be applied to, for example... Figure 4 In the vehicle control system shown. For example... Figure 4 As shown, the host computer 41 obtains the user's steering wheel control parameters (hand force, speed) through the in-vehicle communication network (CAN bus, gateway), and sends the corresponding decision results to the slave computer (steering controller 42) so that the steering controller controls the steering motor based on the decision results of the host computer, so that the vehicle performs steering actions.

[0065] It is understood that the human-machine co-driving control method provided in this disclosure can also be applied in other scenarios.

[0066] The following is about Figure 3 The human-machine co-driving control method shown is introduced below, and the specific steps of the method are as follows:

[0067] S301. Obtain the user's steering wheel control parameters.

[0068] Steering wheel control parameters refer to the physical quantities applied by the driver through the steering wheel, such as hand torque and steering wheel speed.

[0069] Optionally, the driver's hand torque can be obtained through the torque sensor of the steering wheel system, and the steering wheel speed can be collected through an angle encoder or Hall sensor.

[0070] After collecting the steering wheel control parameters, they are transmitted to the host computer in real time via the vehicle's CAN bus.

[0071] S302. The host computer makes a user takeover intention decision based on the steering wheel control parameters and obtains the intelligent driving control coefficient corresponding to the user takeover intention. The intelligent driving control coefficient is inversely proportional to the intensity of the user takeover intention.

[0072] The host computer, acting as the decision-making layer for intelligent driving functions, determines the user's intention to take over steering control based on steering wheel control parameters and outputs intelligent driving control coefficients. Specifically, the host computer judges whether the driver intends to take over steering control based on the steering wheel control parameters, measures the strength of the user's intention to take over based on the steering wheel control parameters, and then outputs the corresponding intelligent driving control coefficients.

[0073] The user's intention to take over depends on the magnitude of the steering wheel control parameters. For example, a higher hand torque indicates a stronger intention to take over, while a lower hand torque indicates a weaker intention. And / or, a higher steering wheel speed indicates a stronger intention to take over, while a lower steering wheel speed indicates a weaker intention.

[0074] The intelligent driving control coefficient determines the degree of influence of the intelligent driving steering request parameters output by the intelligent driving system on the final steering control of the steering system. The higher the intelligent driving control coefficient, the greater the influence of the intelligent driving steering request parameters on the final steering control of the steering system; correspondingly, the lower the intelligent driving control coefficient, the lower the influence of the intelligent driving steering request parameters on the final steering control of the steering system.

[0075] Based on the correspondence between user takeover intention and intelligent driving control coefficient, the stronger the user takeover intention, the lower the influence of intelligent driving steering request parameters on the final steering control of the steering system, and the more obvious the effect of manual steering control by the user. Conversely, the weaker the user takeover intention, the higher the influence of intelligent driving steering request parameters on the final steering control of the steering system, and the more obvious the steering control effect of the intelligent driving system.

[0076] Optionally, the intelligent driving control coefficient can be any number between 0 and 1. When the intelligent driving control coefficient is 0, it means that the intelligent driving control is inactive and the steering is completely controlled manually by the user. When the intelligent driving control coefficient is 1, it means that the steering is completely controlled by the intelligent driving system.

[0077] S303: The host computer obtains intelligent driving steering request parameters based on road condition information.

[0078] When a smart driving steering request is made, the host computer calculates the steering control parameters based on road condition information, which are used to control the steering system to achieve the target steering angle or target torque.

[0079] The system acquires road condition information about the vehicle's environment through environmental perception devices such as cameras and lidar. The host computer then generates corresponding lateral control commands based on this information, such as parameters like the target steering angle, and converts them into physical quantities compatible with the slave computer, such as specific control parameters like motor current and torque.

[0080] S304. Send the intelligent driving control coefficient and intelligent driving steering request parameters to the lower-level machine.

[0081] The lower-level machine is the execution layer of the intelligent driving function, and it executes specific control actions based on the decision results of the upper-level machine.

[0082] In this step, the host computer sends the intelligent driving control coefficients and intelligent driving steering requests to the steering controller, which acts as the lower-level computer, through the vehicle communication network.

[0083] S305. The lower-level control unit compensates for the steering wheel control parameters based on the intelligent driving control coefficient and the intelligent driving steering request parameters to obtain the target control parameters.

[0084] The lower-level computer compensates for the hand torque based on the intelligent driving control coefficient and the intelligent driving steering request parameters, and generates the final target control parameters, such as torque or current, to be applied to the steering motor.

[0085] Specifically, the intelligent driving control coefficient and the intelligent driving steering request parameter are multiplied to obtain the intelligent driving assistance parameter; the intelligent driving assistance parameter and the manual torque are summed to obtain the target control parameter.

[0086] The specific calculation formula is as follows:

[0087] F final =F hands +F machine ×Factor

[0088] Among them, F final For the target control parameter, F hands For the hand torque in the steering wheel control parameters, F machine The intelligent driving steering request parameters are output by the intelligent driving system (host computer), and Factor is the intelligent driving control coefficient.

[0089] The product of the intelligent driving control coefficient and the intelligent driving steering request parameter determines the control amount of the intelligent driving system for the target control parameter. This is then superimposed with the manual torque of the steering wheel controlled by the user to obtain the final target control parameter for controlling the steering system.

[0090] S306. The lower-level computer controls the vehicle steering system to perform steering actions based on the target control parameters.

[0091] The lower-level computer controls the torque or current of the steering motor according to the target control parameters, so that the vehicle can complete the steering action that meets the user's intention.

[0092] This embodiment of the disclosure obtains the user's steering wheel control parameters; controls the host computer to make a user takeover intention decision based on the steering wheel control parameters, and obtains the intelligent driving control coefficient corresponding to the user takeover intention. The intelligent driving control coefficient is inversely proportional to the intensity of the user takeover intention; controls the host computer to obtain intelligent driving steering request parameters based on road condition information; sends the intelligent driving control coefficient and intelligent driving steering request parameters to the slave computer; controls the slave computer to compensate the steering wheel control parameters based on the intelligent driving control coefficient and intelligent driving steering request parameters to obtain target control parameters; and controls the vehicle steering system to perform steering actions based on the target control parameters. By predicting the user takeover intention based on the steering wheel control parameters, the corresponding intelligent driving control coefficient is obtained, and the intelligent driving control coefficient participates in generating the final target control parameters for controlling the vehicle steering system. This ensures that the control degree of the intelligent driving steering request parameters output by the intelligent driving system in the target control parameters matches the user's takeover intention, solving the problem of the intelligent driving system competing with the driver for the steering wheel. It also takes into account safety, comfort, and compliance. Combined with the collaboration between the host and slave computers, it achieves intelligent torque distribution for human-machine co-driving, improving the flexibility of intelligent driving.

[0093] Meanwhile, the embodiments of this disclosure quantify the driver's intention to take over as an intelligent driving control coefficient. By utilizing the continuity of the intelligent driving control coefficient, sudden changes in steering wheel feel are avoided when switching between pure manual driving and intelligent driving, thus achieving seamless switching of driving modes and reducing the driver's sense of control boundaries.

[0094] Based on the above embodiments, the steering wheel control parameters include the hand torque. The host computer makes a user takeover intention decision based on the steering wheel control parameters and obtains the intelligent driving control coefficient corresponding to the user takeover intention. This includes: when the hand torque is greater than the minimum value of the preset torque range and less than the maximum value of the preset torque range, the hand torque is normalized based on the preset torque range to obtain the intelligent driving control coefficient.

[0095] Hand torque refers to the steering torque applied by the driver's hands to the steering wheel, reflecting the strength of the driver's intention to intervene in the steering system. The larger the hand torque value, the stronger the driver's intention to take over.

[0096] The preset torque range includes a minimum value and a maximum value. The minimum value of the preset torque range is the lower limit of the torque required to trigger the human-machine co-driving mode; the maximum value of the preset torque range is the upper limit of the torque required to trigger the intelligent driving mode to exit.

[0097] When the manual torque is greater than the minimum value of the preset torque range but less than the maximum value of the preset torque range, the system operates in a state where manual driving and intelligent driving control coexist. The intelligent driving control coefficient is determined based on the magnitude of the manual torque. The specific formula for calculating the intelligent driving control coefficient is as follows:

[0098]

[0099] Among them, T hands For manual torque, T lowerthreshold T is the minimum value within the preset torque range. upperthreshold This is the highest value in the preset torque range.

[0100] This embodiment of the invention ensures a smooth driving feel by continuously changing the intelligent driving control coefficient as the driving torque varies within a preset torque range. For example, within the preset torque range, as the driver gradually increases the torque, the corresponding intelligent driving control coefficient gradually decreases, the intelligent driving control weight gradually decreases, and the steering wheel feel changes smoothly during this process.

[0101] In some embodiments, the host computer makes a user takeover intention decision based on the steering wheel control parameters and obtains the intelligent driving control coefficient corresponding to the user takeover intention. The method further includes: when the hand torque is less than or equal to the lowest value of the preset torque range, determining the intelligent driving control coefficient as the preset maximum coefficient; or when the hand torque is greater than or equal to the highest value of the preset torque range, determining the intelligent driving control coefficient as the preset minimum coefficient.

[0102] The preset maximum coefficient of the intelligent driving control coefficient is 1, which means that the intelligent driving system has complete control over the steering; the preset minimum coefficient of the intelligent driving control coefficient is 0, which means that the intelligent driving system completely exits control and the driver takes over control.

[0103] When the manual torque is less than or equal to the minimum value of the preset torque range, it indicates that the driver currently has almost no intention to control the vehicle, and the intelligent driving system completely controls the vehicle's steering. For example, in a high-speed cruise scenario, the intelligent driving system controls the vehicle to stay in the center of the lane, and the driver only lightly places their hands on the steering wheel without applying any steering force.

[0104] Based on this, when the hand torque is less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is determined to be the preset maximum coefficient, including: calculating the coefficient increment rate based on the steering wheel speed, the preset speed threshold, and the preset increment step size; when the hand torque jumps from the preset torque range to less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient increment rate until the intelligent driving control coefficient reaches the preset maximum coefficient, or the hand torque is greater than the minimum value of the preset torque range.

[0105] When the manual torque changes from being greater than the minimum value of the preset torque range to being less than or equal to the minimum value of the preset torque range, the steering will switch from joint control by the driver and the intelligent driving system to complete control by the intelligent driving system. During this process, to prevent the intelligent driving control coefficient from surging with the change in manual torque, the coefficient is gradually increased based on the coefficient increment rate until it reaches the preset maximum coefficient, or the manual torque exceeds the preset torque range again.

[0106] For example, when a user first activates the intelligent driving function, the manual torque may jump from the preset torque range to a value less than or equal to the lowest value of the preset torque range. Or, during intelligent driving, when a user controls the steering wheel to make a turn or other maneuvers and then immediately releases control of the steering wheel, the manual torque may jump from the preset torque range to a value less than or equal to the lowest value of the preset torque range.

[0107] The calculation process for the coefficient increment rate can be expressed as follows:

[0108]

[0109] Among them, Ramp up The rate of increase of the coefficient, step up To preset the incrementing step size, V speed V is the steering wheel speed at the moment the manual torque changes. threshold This is the preset speed threshold.

[0110] The preset increment step size determines the preset rate at which the intelligent driving control coefficient increases. Within the same time period, the larger the preset increment step size, the higher the preset rate at which the intelligent driving control coefficient increases, and the more the intelligent driving control coefficient increases. Conversely, the smaller the preset increment step size, the slower the preset rate at which the intelligent driving control coefficient increases, and the less the intelligent driving control coefficient increases.

[0111] The preset speed threshold is the threshold for exiting the intelligent driving function. During intelligent driving, intelligent driving will continue to be effective when the steering wheel speed is less than or equal to the preset speed threshold.

[0112] When the manual torque changes from the preset torque range to a value less than or equal to the minimum value of the preset torque range, the higher the steering wheel speed, the greater the rate of coefficient increase, the faster the intelligent driving control coefficient increases to the preset maximum coefficient, and the shorter the time required. This allows the system to quickly take over the vehicle when the user suddenly relinquishes effective control of the steering wheel. For example, if a driver suddenly stops applying steering force in autonomous driving mode due to fatigue, distraction, or other reasons, the steering wheel still retains a certain speed due to inertia. The intelligent driving system can then quickly take over the vehicle to prevent it from losing control.

[0113] Correspondingly, when the manual torque jumps from the preset torque range to less than or equal to the lowest value of the preset torque range, the lower the steering wheel speed, the smaller the coefficient increase rate, the slower the intelligent driving control coefficient increases to the preset maximum coefficient, and the longer the time, the smoother the transition from human-machine co-driving to fully intelligent driving state can be achieved in a relatively stable driving environment.

[0114] The intelligent driving control coefficient is output based on the gradually increasing rate of the above coefficients until it reaches the preset maximum coefficient, at which point it participates in vehicle steering control; or, the intelligent driving control coefficient is output based on the gradually increasing rate of the above coefficients. If the preset maximum coefficient has not yet been reached, and the manual torque is greater than the minimum value of the preset torque range, the intelligent driving control coefficient is output according to the strategy when the manual torque is within the preset torque range or greater than or equal to the maximum value of the preset torque range.

[0115] This embodiment of the present disclosure dynamically determines the growth rate of the intelligent driving control coefficient based on the steering wheel speed when the manual torque jumps from the lowest value of the preset torque range to the lowest value of the preset torque range. This allows for a smooth transition of steering control from human-machine co-driving to fully intelligent driving even when the manual torque changes. On the one hand, this avoids the risks caused by aggressive control, and on the other hand, it matches the driver's operating inertia, improving driving safety and comfort.

[0116] In other embodiments, the steering wheel control parameters include steering wheel rotation speed. When the hand torque is greater than or equal to the highest value of a preset torque range, the intelligent driving control coefficient is determined to be a preset minimum coefficient. This includes: calculating the coefficient decay rate based on the steering wheel rotation speed, a preset rotation speed threshold, and a preset decay step size; when the hand torque jumps from the preset torque range to a value greater than or equal to the highest value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient decay rate until the intelligent driving control coefficient reaches the preset minimum coefficient, or the hand torque is less than the highest value of the preset torque range.

[0117] When the manual torque jumps from the preset torque range to a value exceeding the maximum value of the preset torque range, it means that the driver has applied a large steering force to the steering wheel in a short period of time. It is necessary to disengage from intelligent driving in time and hand over steering control to the driver.

[0118] For example, while driving on a highway, if the driver suddenly turns the steering wheel due to an obstacle in front, the manual torque jumps from the preset torque range to a value exceeding the maximum value of the preset torque range, triggering a transfer of driving control.

[0119] The calculation process for the coefficient decay rate can be expressed as follows:

[0120]

[0121] Among them, Ramp downFor the coefficient decay rate, step down V is the preset decay step size. speed V is the steering wheel speed at the moment the manual torque changes. threshold This is the preset speed threshold.

[0122] The preset decay step size determines the preset rate of decay of the intelligent driving control coefficient. Within the same time period, the larger the preset decay step size, the higher the preset rate of decay of the intelligent driving control coefficient, and the more the intelligent driving control coefficient decays; correspondingly, the smaller the preset decay step size, the slower the preset rate of decay of the intelligent driving control coefficient, and the less the intelligent driving control coefficient decays.

[0123] When the manual torque jumps from the preset torque range to a value greater than or equal to the highest value of the preset torque range, the higher the steering wheel speed, the greater the coefficient decay rate, the faster the intelligent driving control coefficient decays to the preset minimum coefficient, and the shorter the time required. This allows for timely transfer of control when the user needs to control the vehicle's steering, facilitating quick takeover of the vehicle by the user.

[0124] Correspondingly, when the manual torque jumps from the preset torque range to a value greater than or equal to the maximum value of the preset torque range, the lower the steering wheel speed, the smaller the coefficient decay rate, and the slower the intelligent driving control coefficient decays to the preset minimum coefficient, and the longer it takes. When the steering wheel speed is relatively low, although the manual torque jumps from the preset torque range to a value greater than or equal to the maximum value of the preset torque range, the driver's operation is relatively smooth. In this case, reducing the decay rate of the intelligent driving control coefficient is beneficial for a smoother transition with the user's steering operation.

[0125] Furthermore, when the manual torque jumps from the preset torque range to a value greater than or equal to the highest value of the preset torque range, the host computer controls the target control parameter at the current moment as the intelligent driving steering request parameter.

[0126] When the manual torque jumps from the preset torque range to a value greater than or equal to the maximum value of the preset torque range, the intelligent driving system loses control over the vehicle's steering system. Directly removing the intelligent driving system's control over the vehicle's steering system would cause a sudden change in the steering wheel resistance felt by the driver, resulting in a noticeable sense of boundary. Therefore, when the manual torque jumps from the preset torque range to a value greater than or equal to the maximum value of the preset torque range, the intelligent driving steering request parameters output by the host computer follow the target control parameters of the slave computer at this time. This serves to temporarily "hold" the steering system, mitigating the sense of boundary in the driver's steering wheel feel caused by the intelligent driving system disengaging control.

[0127] Based on the above-mentioned coefficient decay rate, the intelligent driving control coefficient is output gradually until the intelligent driving control coefficient reaches the preset minimum coefficient, at which point the vehicle steering control is completely handed over to the user; or, based on the above-mentioned coefficient decay rate, the intelligent driving control coefficient is output gradually, and when the preset minimum coefficient has not yet been reached, the manual torque is less than the minimum value of the preset torque range, and the intelligent driving control coefficient is output according to the strategy when the manual torque is within the preset torque range or less than or equal to the minimum value of the preset torque range.

[0128] This embodiment of the present disclosure dynamically determines the decay rate of the intelligent driving control coefficient based on the steering wheel speed when the manual torque jumps from a preset torque range to a value greater than or equal to the highest value of the preset torque range. It adjusts the control transfer speed in real time according to the urgency of the driver's operation, avoiding the intelligent driving control from laging out. At the same time, it makes the resistance change perceived by the driver continuous and natural, avoiding the feeling of being stuck or out of control.

[0129] In some embodiments, controlling the vehicle steering system to perform steering actions via a lower-level computer based on the target control parameters includes: when the intelligent driving control coefficient is less than a preset coefficient threshold, determining an integral output contribution based on the intelligent driving control coefficient, wherein the integral output contribution is proportional to the intelligent driving control coefficient; and limiting the integral output of the target control parameters to the vehicle steering system according to the integral output contribution.

[0130] The integral output is the cumulative error term used in PID control to eliminate steady-state error. Because the driver's steering wheel movements cause a deviation between the intelligent driving steering request parameters output by the host computer and the intelligent driving assistance parameters responded by the slave computer, although the intelligent driving control coefficient decreases as the driver's hand torque increases, the increased deviation leads to an increase in the intelligent driving assistance parameters responded by the slave computer. Therefore, it is necessary to limit the integral output in the slave computer's PID controller and output the limited target control parameters to the steering motor to execute the steering action.

[0131] The dynamic adjustment of the integral output contribution directly affects the steady-state performance of the control system. When the intelligent driving control parameters are low, the integral action is suppressed to avoid output oscillation caused by error accumulation due to the partial disengagement of the intelligent driving function.

[0132] Specifically, when the intelligent driving control coefficient is less than the preset coefficient threshold, the lower the preset coefficient threshold, the lower the contribution of the integral output, so as to gradually reduce the control of the integral output on the vehicle steering system.

[0133] Optionally, the preset integration threshold is 0.95.

[0134] This embodiment of the present disclosure dynamically controls the integral output of the lower-level machine. When the intelligent driving control coefficient is high, the integral output participates in the control to a high degree, which can eliminate minor deviations during lane keeping. When the intelligent driving control coefficient decreases, it avoids the steering motor from over-adjusting due to excessively rapid error accumulation, thereby further improving the reliability of intelligent driving.

[0135] In some embodiments, the method further includes: when the intelligent driving function exits unexpectedly, obtaining the intelligent driving control coefficient at the moment before the unexpected exit; determining the intelligent driving transition speed according to the vehicle driving style mode; and controlling the host computer to decrease the intelligent driving control coefficient at the moment before the unexpected exit based on the intelligent driving transition speed until the intelligent driving control coefficient reaches a preset minimum coefficient.

[0136] Optional vehicle driving style modes include Comfort mode, Sport mode, and Light mode.

[0137] Unexpected disengagement of the intelligent driving function refers to the interruption of intelligent driving control from a point other than the driver's starting point. For example, the road conditions ahead are poor and no longer meet the requirements for intelligent driving; or the intelligent driving is interrupted due to sensor failure or other malfunctions.

[0138] When the intelligent driving function unexpectedly exits, the last valid intelligent driving control coefficient before the intelligent driving exit is acquired and recorded as the initial value for the transition phase.

[0139] Driving style modes are user-configurable, such as Comfort mode, Sport mode, and Light mode. In Comfort mode, the vehicle's steering is smooth and acceleration / deceleration is gentle; in Sport mode, the vehicle's steering is sensitive and responsive; and in Light mode, the vehicle's steering response is moderate.

[0140] The intelligent driving transition speed is the rate at which the intelligent driving control coefficient decreases from its initial value during the transition phase before intelligent driving exits to a preset minimum coefficient (usually 0).

[0141] For Comfort mode, the intelligent driving transition speed is set to low, such as the first transition speed; for Sport mode, the intelligent driving transition speed is set to high, such as the second transition speed; for Light mode, the intelligent driving transition speed is set to moderate, such as the third transition speed. That is, the first transition speed is lower than the third transition speed, and the third transition speed is lower than the second transition speed.

[0142] The lower-level machine executes the corresponding intelligent driving transition speed according to the preset vehicle driving style mode until the intelligent driving control coefficient is reduced to the preset minimum coefficient, then the intelligent driving output is completely turned off, and the steering system is fully controlled by the driver.

[0143] This embodiment of the invention achieves a safe and smooth reduction in the weight of the intelligent driving function when it unexpectedly exits by adjusting the transition speed according to the driving style. By matching the driving habits of different user groups through mode selection, it integrates user preferences with the driving control feel, avoids the problem of sudden changes in the intelligent driving control coefficient when the intelligent driving system unexpectedly exits, which would cause a break in the steering wheel feel, and further improves the driving experience.

[0144] Figure 5 This is a schematic diagram of the host computer algorithm provided in an embodiment of this disclosure. Figure 5 As shown, the host computer acquires steering wheel control parameters in real time, including hand torque and steering wheel speed. Based on the comparison of steering wheel control parameters with preset torque range and preset speed threshold, human-machine co-driving is performed when the hand torque is within the preset torque range. Based on the steering wheel control parameters, the intelligent driving control coefficient and intelligent driving steering request parameters are output to the lower computer (steering controller) in real time.

[0145] If the manual torque is not within the preset torque range, the intelligent driving system can fully control the vehicle steering and assign the intelligent driving control coefficient to the preset maximum coefficient. If, during human-machine co-driving, the collected steering wheel control parameters reach the intelligent driving system's exit condition, or the manual torque exceeds the preset torque range, the user must fully control the vehicle steering, cancel the handshake with the steering controller, assign the intelligent driving control coefficient to the preset minimum coefficient, and simultaneously control the intelligent driving steering request parameters output by the host computer to follow the target control parameters of the current slave computer.

[0146] The conditions for the intelligent driving system to exit include the manual torque being greater than a preset torque threshold and the steering wheel speed being greater than a preset speed threshold.

[0147] Figure 6 This is a schematic diagram of the lower-level machine algorithm provided in an embodiment of this disclosure. Figure 6 As shown, the system determines whether to enter human-machine co-driving mode based on the intelligent driving control coefficient sent by the host computer. When the intelligent driving control coefficient is at its preset maximum, it indicates that the vehicle is fully controlled by the intelligent driving system. When the intelligent driving control coefficient is between the preset maximum and minimum, it indicates that human-machine co-driving mode has been entered. When the intelligent driving control coefficient is at its preset minimum, the vehicle is controlled by the driver. When intelligent driving is not enabled, the default value of the intelligent driving control coefficient is the preset minimum. When intelligent driving is activated, the intelligent driving control coefficient increases from the preset minimum to the preset maximum according to the coefficient increment rate.

[0148] When the intelligent driving control coefficient is at the preset maximum coefficient, the lower-level machine fully responds to the intelligent driving steering request parameters of the upper-level machine.

[0149] When the intelligent driving control coefficient is not the preset maximum coefficient, if the upper and lower computers are in a handshake state, the lower computer compensates the steering wheel control parameters based on the intelligent driving control coefficient and the intelligent driving steering request parameters to obtain the target control parameters. Specifically, this includes: calculating the product of the intelligent driving control coefficient and the intelligent driving steering request parameters to obtain the intelligent driving assist parameters; calculating the sum of the intelligent driving assist parameters and the hand torque to obtain the target control parameters; and when the intelligent driving control coefficient is less than the preset coefficient threshold, limiting the integral output of the target control parameters to the vehicle steering system based on the integral output contribution. Finally, the limited target control parameters are input to the steering motor to realize the steering action.

[0150] If the upper and lower computers are not in a handshake state, the intelligent driving transition speed is determined according to the vehicle driving style mode, and the intelligent driving control coefficient is controlled to decrease until the intelligent driving control coefficient reaches the preset minimum coefficient, and the vehicle driving style mode is successfully transitioned to the preset mode.

[0151] This embodiment achieves smooth human-machine co-driving by closely cooperating with the upper and lower computers through algorithms. It improves the driver's driving experience by utilizing existing vehicle sensors without increasing hardware costs. At the same time, it combines multiple adjustable thresholds, which can be adjusted based on the actual vehicle conditions, further improving flexibility.

[0152] Figure 7 This is a schematic diagram of the structure of the human-machine co-driving control device provided in this embodiment of the disclosure. The human-machine co-driving control device provided in this embodiment of the disclosure can execute the processing flow provided in the human-machine co-driving control method embodiment, such as... Figure 7 As shown, the human-machine co-driving control device 70 includes: an acquisition module 71, a first control module 72, a second control module 73, a sending module 74, a third control module 75, and a fourth control module 76. The acquisition module 71 is used to acquire the user's steering wheel control parameters. The first control module 72 is used to control the host computer to make a user takeover intention decision based on the steering wheel control parameters, and obtain the intelligent driving control coefficient corresponding to the user takeover intention. The intelligent driving control coefficient is inversely proportional to the intensity of the user takeover intention. The second control module 73 is used to control the host computer to obtain intelligent driving steering request parameters based on road condition information. The sending module 74 is used to send the intelligent driving control coefficient and the intelligent driving steering request parameters to the lower-level computer. The third control module 75 is used to control the lower-level computer to compensate the steering wheel control parameters based on the intelligent driving control coefficient and the intelligent driving steering request parameters, and obtain target control parameters. The fourth control module 76 is used to control the vehicle steering system to perform steering actions through the lower-level computer based on the target control parameters.

[0153] Optionally, the steering wheel control parameters include the hand torque. The first control module 72 is used to normalize the hand torque based on the preset torque range to obtain an intelligent driving control coefficient when the hand torque is greater than the minimum value of the preset torque range and less than the maximum value of the preset torque range; or, when the hand torque is less than or equal to the minimum value of the preset torque range, determine the intelligent driving control coefficient as a preset maximum coefficient; or, when the hand torque is greater than or equal to the maximum value of the preset torque range, determine the intelligent driving control coefficient as a preset minimum coefficient.

[0154] Optionally, the first control module 72 is further configured to calculate the coefficient increment speed based on the steering wheel speed, a preset speed threshold, and a preset increment step size; when the hand torque jumps from the preset torque range to less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient increment speed until the intelligent driving control coefficient reaches the preset maximum coefficient, or the hand torque is greater than the minimum value of the preset torque range.

[0155] Optionally, the first control module 72 is further configured to calculate the coefficient decay rate based on the steering wheel speed, a preset speed threshold, and a preset decay step size; when the hand torque jumps from the preset torque range to a value greater than or equal to the highest value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient decay rate until the intelligent driving control coefficient reaches the preset minimum coefficient, or the hand torque is less than the highest value of the preset torque range.

[0156] Optionally, the first control module 72 is further configured to control the host computer to use the target control parameter at the current moment as the intelligent driving steering request parameter when the manual torque jumps from the preset torque range to a value greater than or equal to the highest value of the preset torque range.

[0157] Optionally, the third control module 75 is used to calculate the product of the intelligent driving control coefficient and the intelligent driving steering request parameter to obtain the intelligent driving assistance parameter; and to calculate the sum of the intelligent driving assistance parameter and the manual torque to obtain the target control parameter.

[0158] Optionally, the fourth control module 76 is further configured to determine the integral output contribution based on the intelligent driving control coefficient when the intelligent driving control coefficient is less than a preset coefficient threshold, wherein the integral output contribution is proportional to the intelligent driving control coefficient; and to limit the integral output of the target control parameter to the vehicle steering system according to the integral output contribution.

[0159] Optionally, the human-machine co-driving control device 70 also includes a transition module 77, which is used to obtain the intelligent driving control coefficient at the moment before the intelligent driving function unexpectedly exits when the intelligent driving function unexpectedly exits; determine the intelligent driving transition speed according to the vehicle driving style mode; and control the host computer to decrease the intelligent driving control coefficient at the moment before the intelligent driving function unexpectedly exits based on the intelligent driving transition speed until the intelligent driving control coefficient reaches a preset minimum coefficient.

[0160] Figure 7 The human-machine co-driving control device shown in the embodiment can be used to execute the technical solution of the above method embodiment. Its implementation principle and technical effect are similar, and will not be repeated here.

[0161] Figure 8 This is a schematic diagram of the structure of a vehicle provided as an embodiment of this disclosure. For example, as shown... Figure 8 As shown, the vehicle 800 includes a memory 801 and a processor 802. The memory 801 stores executable program code 8011, and the processor 802 is used to call and execute the executable program code 8011 to perform the human-machine co-driving control method.

[0162] This embodiment can divide the vehicle into functional modules according to the above method example. For example, each function can be assigned to a separate module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0163] When each function is divided into its own modules, the vehicle may include: an acquisition module, a first control module, a second control module, a sending module, a third control module, and a fourth control module.

[0164] The vehicle provided in this embodiment is used to execute the above-described human-machine co-driving control method, and therefore can achieve the same effect as the above-described implementation method.

[0165] When using integrated units, the vehicle may include a processing module and a storage module. The processing module is used to control and manage the vehicle's actions. The storage module supports the vehicle in executing program code and data.

[0166] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits as disclosed in this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc., and the storage module may be a memory.

[0167] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. The electronic device provided in an embodiment of this disclosure can execute the processing flow provided in the human-machine co-driving control method embodiment, such as... Figure 9 As shown, the electronic device 90 includes: a memory 91, a processor 92, a computer program, and a communication interface 93; wherein the computer program is stored in the memory 91 and configured to be executed by the processor 92 using the human-machine co-driving control method described above.

[0168] The memory 91, as a non-transitory readable storage medium, can be used to store software programs, vehicle executable instructions, and modules, such as the program instructions / modules corresponding to the human-machine co-driving control method in this embodiment of the present disclosure. The processor 92 executes various functional applications and data processing of the server by running the software programs, instructions, and modules stored in the memory 91, thereby implementing the human-machine co-driving control method of the above-described method embodiment.

[0169] The memory 91 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on vehicle usage. Furthermore, the memory 91 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 91 may optionally include memory remotely located relative to the processor 92, and these remote memories can be connected to the terminal device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0170] This embodiment also provides a computer-readable storage medium (including but not limited to disk storage, CD-ROM, optical storage, etc.) storing computer program code. When the computer program code is run on a computer, the computer executes the above-mentioned related method steps to implement the human-machine co-driving control method provided in the above embodiment.

[0171] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to implement the human-machine co-driving control method provided in the above embodiment.

[0172] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0173] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0174] In the description of this disclosure, it should be understood that if the terms "upper", "lower", "front", "rear", "left" and "right" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the position or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure.

[0175] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0176] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0177] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

[0178] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0179] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0180] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. It should also be noted that 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 process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0181] The above are merely embodiments of this disclosure and are not intended to limit the scope of this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of the claims of this disclosure.

Claims

1. A human-machine co-driving control method, characterized in that, The method includes: Obtain the user's steering wheel control parameters; The host computer makes a decision on the user's takeover intention based on the steering wheel control parameters, and obtains the intelligent driving control coefficient corresponding to the user's takeover intention. The intelligent driving control coefficient is inversely proportional to the intensity of the user's takeover intention. The host computer obtains intelligent driving steering request parameters based on road condition information; Send the intelligent driving control coefficients and intelligent driving steering request parameters to the lower-level machine; The lower-level control unit compensates for the steering wheel control parameters based on the intelligent driving control coefficients and the intelligent driving steering request parameters to obtain the target control parameters; The lower-level computer controls the vehicle steering system to perform steering actions based on the target control parameters. The steering wheel control parameters include the manual torque. The host computer makes a user takeover intention decision based on the steering wheel control parameters and obtains the intelligent driving control coefficient corresponding to the user takeover intention, including: when the manual torque is less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is determined to be the preset maximum coefficient. The steering wheel control parameters include steering wheel speed. When the hand torque is less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is determined to be the preset maximum coefficient. This includes: calculating the coefficient increment rate based on the steering wheel speed, a preset speed threshold, and a preset increment step size; when the hand torque jumps from the preset torque range to less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient increment rate until the intelligent driving control coefficient reaches the preset maximum coefficient, or the hand torque is greater than the minimum value of the preset torque range.

2. The method according to claim 1, characterized in that, The host computer makes a user takeover intention decision based on the steering wheel control parameters, and obtains the intelligent driving control coefficients corresponding to the user takeover intention, including: When the manual torque is greater than the minimum value of the preset torque range and less than the maximum value of the preset torque range, the manual torque is normalized based on the preset torque range to obtain the intelligent driving control coefficient; or... When the manual torque is greater than or equal to the highest value of the preset torque range, the intelligent driving control coefficient is determined to be the preset minimum coefficient.

3. The method according to claim 2, characterized in that, The steering wheel control parameters include steering wheel speed. When the hand torque is greater than or equal to the highest value of the preset torque range, the intelligent driving control coefficient is determined to be the preset minimum coefficient, including: The coefficient decay rate is calculated based on the steering wheel speed, the preset speed threshold, and the preset decay step size. When the manual torque jumps from the preset torque range to a value greater than or equal to the maximum value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient decay rate until the intelligent driving control coefficient reaches the preset minimum coefficient, or the manual torque is less than the maximum value of the preset torque range.

4. The method according to claim 3, characterized in that, The method further includes: When the manual torque changes from the preset torque range to a value greater than or equal to the highest value of the preset torque range, the host computer controls the target control parameter at the current moment as the intelligent driving steering request parameter.

5. The method according to claim 1, characterized in that, The steering wheel control parameters include the hand torque. The lower-level control unit compensates for the steering wheel control parameters based on the intelligent driving control coefficient and the intelligent driving steering request parameters to obtain target control parameters, including: The intelligent driving assistance parameters are obtained by multiplying the intelligent driving control coefficient and the intelligent driving steering request parameter. The target control parameters are obtained by calculating the sum of the intelligent driving assistance parameters and the manual torque.

6. The method according to claim 1, characterized in that, The step of controlling the vehicle steering system to perform steering actions via a lower-level computer based on the target control parameters includes: When the intelligent driving control coefficient is less than a preset coefficient threshold, the integral output contribution is determined based on the intelligent driving control coefficient, and the integral output contribution is proportional to the intelligent driving control coefficient. The integral output contribution of the target control parameters to the vehicle steering system is limited based on the integral output contribution.

7. The method according to claim 1, characterized in that, The method further includes: When the intelligent driving function unexpectedly exits, obtain the intelligent driving control coefficient at the moment before the unexpected exit of the intelligent driving function; Determine the intelligent driving transition speed based on the vehicle's driving style mode; The host computer controls the intelligent driving control coefficient based on the intelligent driving transition speed, decreasing the output of the intelligent driving control coefficient at the moment before the intelligent driving function unexpectedly exits, until the intelligent driving control coefficient reaches the preset minimum coefficient.

8. A human-machine co-driving control device, characterized in that, include: The acquisition module is used to acquire the user's steering wheel control parameters. The first control module is used to control the host computer to make a user takeover intention decision based on the steering wheel control parameters, and obtain the intelligent driving control coefficient corresponding to the user takeover intention. The intelligent driving control coefficient is inversely proportional to the intensity of the user takeover intention. The second control module is used to control the host computer to obtain intelligent driving steering request parameters based on road condition information; The sending module is used to send the intelligent driving control coefficients and intelligent driving steering request parameters to the lower-level machine; The third control module is used to control the lower-level machine to compensate the steering wheel control parameters based on the intelligent driving control coefficient and the intelligent driving steering request parameters to obtain the target control parameters; The fourth control module is used to control the vehicle steering system to perform steering actions via a lower-level computer based on the target control parameters; The steering wheel control parameters include hand torque. The first control module is used to determine the intelligent driving control coefficient as the preset maximum coefficient when the hand torque is less than or equal to the minimum value of the preset torque range. The steering wheel control parameters include steering wheel speed. The first control module is specifically used to calculate the coefficient increment speed based on the steering wheel speed, a preset speed threshold, and a preset increment step. When the manual torque jumps from the preset torque range to less than or equal to the minimum value of the preset torque range, the intelligent driving control coefficient is output according to the coefficient increment rate until the intelligent driving control coefficient reaches the preset maximum coefficient, or the manual torque is greater than the minimum value of the preset torque range.

9. A vehicle, characterized in that, include: Memory; processor; The memory stores executable program code, and the processor is used to call and execute the executable program code to perform the method as described in any one of claims 1-7.

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