A human-machine co-driving control method and system based on steering wheel angle control

Abstract

The present invention provides a human-machine co-driving control method and system based on steering wheel angle control. The method comprises the following steps: in step S1, matching a base torque A according to the vehicle speed range; in step S2, issuing an angle control request to the EPS, obtaining the driver's hand torque B transmitted by the EPS, and adjusting the torque limit C in real time to equal the base torque A minus the driver's hand torque B; in step S3, obtaining a curve compensation torque D based on the curve radius and adding it to the torque limit C; in step S4, identifying the vehicle's lane change request based on the vehicle's turn signal status or the driver's lane change confirmation information, providing a lane change compensation torque F during the vehicle's lane change process and adding it to the torque limit C; and in step S5, calculating a comprehensive torque limit G and outputting it to the EPS for execution. By optimizing the control strategy, the present invention makes the system human-machine co-driving friendly, and the lateral control function is not easily exited after driver intervention.

Description

Technical Field

[0001] The present invention relates to the automotive field, and in particular to a human-machine co-driving control method and system based on steering wheel angle control. Background Art

[0002] As the pace of automotive intelligence accelerates, the adoption of advanced driver assistance systems (ADAS) has increased significantly. In particular, Level 2 intelligent driving features (such as Lane Keeping (LKA), Traffic Jam Assist (TJA), and Integrated Cruise Assist (ICA)) have become mainstream features in new models. These features utilize environmental and vehicle state sensing to achieve coordinated lateral (lane keeping) and longitudinal (adaptive cruise control) control. In theory, this allows the driver to maintain stable centering of the lane with only a slight effort on the steering wheel.

[0003] The core of current lateral assist functions relies on the integration of visual perception and electronic steering control. A camera mounted on the vehicle's windshield identifies lane markings and, based on a comprehensive assessment of the vehicle's posture, sends a control request to the Electronic Power Steering (EPS) system to maintain centering. In recent years, this control request signal has evolved from traditional torque control to angle control. However, angle control has inherent drawbacks in human-machine co-driving, resulting in a strong sense of friction and a stiff steering wheel. Furthermore, lateral control can easily be disabled if the driver intervenes and overrides the control. Summary of the Invention

[0004] In response to the defects in the prior art, the purpose of the present invention is to provide a human-machine co-driving control method and system based on steering wheel angle control, aiming to make the system human-machine co-driving friendly by optimizing the control strategy, and the lateral control function is not easy to exit after the driver intervenes.

[0005] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solution:

[0006] According to a first aspect of the present invention, a human-machine co-driving control method based on steering wheel angle control is provided, comprising the following steps:

[0007] In step S1, the vehicle speed information is acquired in real time, and the vehicle speed range is identified. The base torque A is matched according to the vehicle speed range and the real-time vehicle speed. The preset base torque A increases as the vehicle speed range increases. The matching method of the base torque A is:

[0008] For vehicle speeds greater than or equal to 0 km / h and less than 60 km / h, set the base torque A=1.5+V*0.01;

[0009] For vehicle speeds greater than or equal to 60 km / h and less than 90 km / h, set the base torque A=2+V*0.006;

[0010] For vehicle speeds greater than or equal to 90 km / h, set the basic torque limit to A=2.5+V*0.003;

[0011] V is the real-time vehicle speed;

[0012] In step S2, an angle control request is sent to the EPS, and the driver's hand torque B transmitted by the EPS is obtained. The driver's hand torque is filtered using a Kalman filter and a 12-pole, non-order Butterworth filter with a cutoff frequency of 10 Hz. The torque limit C is adjusted in real time to be equal to the base torque A minus the driver's hand torque B.

[0013] In step S3, the curve compensation torque D is obtained according to the curve radius and added to the torque limit C. The curve radius identification method is:

[0014] The vehicle's rotation rate ω around the vertical axis is measured by the inertial measurement unit, and the vehicle's longitudinal velocity v1 is obtained through the wheel speed meter or GPS speed information. The radius R1 = v1 / ω is calculated by combining the data;

[0015] Use an edge detection algorithm or a lane detection algorithm to identify the road boundary or centerline, fit the detected pixel points into a smooth curve, calculate the curvature κ of each point on the smooth curve using the curve fitting equation, and calculate the fitting radius R2 = 1 / |κ|;

[0016] Calculate the curve radius: R = √(R1*R2);

[0017] In step S4, the vehicle's lane change requirement is identified based on the vehicle's turn signal status or the driver's lane change confirmation information, and a lane change compensation torque F is provided during the vehicle's lane change process and added to the torque limit C. A lane change requirement is determined when any of the following scenarios is identified: the vehicle's centerline is offset from the lane centerline by more than 15% of the lane width and continues to increase within a preset time range; the vehicle's heading angle is greater than 5° and persists for a period exceeding a preset time range; the vehicle's lateral acceleration is greater than or equal to 0.3 m / s² and less than or equal to 0.6 m / s²; or the left or right turn signal is on.

[0018] In step S5, the comprehensive torque limit G is calculated and output to the EPS for execution. The calculation formula of the comprehensive torque limit G is: comprehensive torque limit G = torque limit C + curve compensation torque D + lane change compensation torque F; the EPS uses the comprehensive torque limit G as the torque upper limit to drive the steering motor to execute the requested angle.

[0019] Preferably, in step S1, the basic torque A is set to 2.0 N*m when the vehicle speed is greater than or equal to 0 km / h and less than 60 km / h, the basic torque A is set to 2.5 N*m when the vehicle speed is greater than or equal to 60 km / h and less than 90 km / h, and the basic torque limit A is set to 3.0 N*m when the vehicle speed is greater than or equal to 90 km / h.

[0020] Preferably, in step S3, when the curve radius is less than or equal to 100m, the preset compensation torque D is 1.5N*m; when the curve radius is greater than 100m and less than or equal to 500m, the preset compensation torque D is 1.0N*m; when the curve radius is greater than 500m and less than or equal to 1500m, the preset compensation torque D is 0.8N*m.

[0021] Preferably, in step S4, when it is identified that the vehicle is in the process of changing lanes through the vehicle's turn signal status or the driver's lane change confirmation information, the lane change compensation torque F is a fixed value of 1 N*m and is added to the torque limit.

[0022] According to a second aspect of the present invention, a human-machine co-driving control system based on steering wheel angle control is provided, which is used to execute the above-mentioned human-machine co-driving control method based on steering wheel angle control, comprising:

[0023] ADAS control module, capable of sending angle control requests to EPS;

[0024] A basic torque acquisition module is used to match the corresponding basic torque A according to the vehicle speed;

[0025] The torque reduction module is used to obtain the driver's hand torque B transmitted by the EPS and obtain the torque limit C based on the basic torque A and the driver's hand torque B;

[0026] A curve compensation module is used to obtain a curve compensation torque D according to a curve radius;

[0027] A lane change compensation module is used to identify the vehicle's lane change requirements and provide a lane change compensation torque F during the vehicle's lane change process and add it to the torque limit;

[0028] The torque limit output module calculates and outputs the comprehensive torque limit G. The calculation formula of the comprehensive torque limit G is: comprehensive torque limit G = torque limit C + cornering compensation torque D + lane change compensation torque F;

[0029] EPS can perform angle control based on the comprehensive torque limit G.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. The present invention considers the driver's hand torque information during the angle control process, thereby carrying out dynamic confrontation weakening in real time, being able to respond to the driver's intervention in real time, and solving the problem of the traditional angle control steering wheel stiffness.

[0032] 2. The present invention can achieve scene-adaptive compensation through the torque compensation steps in special scenarios. Relying on the compensation mechanism for curve radius and lane change status, it ensures control stability in complex scenarios, realizes human-machine collaborative optimization, and balances system control requirements and driver operating experience by outputting comprehensive torque limits, thereby improving the availability of intelligent driving functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0034] Figure 1 Schematic diagram of the process described in Example 1;

[0035] Figure 2 Schematic diagram of the structure of the system described in Example 2. DETAILED DESCRIPTION

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0037] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without making any creative efforts shall fall within the scope of protection of the present application.

[0038] It should be noted that similar reference numerals and letters denote similar items in the following figures. Therefore, once an item is defined in one figure, it does not require further definition or explanation in subsequent figures. Furthermore, all directional designations (such as up, down, left, right, front, back, bottom, etc.) in this application are intended only to explain the relative positional relationships and movement of components in a specific posture (as shown in the figures). If the specific posture changes, the directional designations will also change accordingly.

[0039] Example 1

[0040] This embodiment provides a human-machine co-driving control method based on steering wheel angle control. To address the shortcomings of human-machine co-driving with lateral control function angle control, such as a strong sense of confrontation, a hard steering wheel, and easy exit of the lateral control function after driver intervention, the control strategy is optimized to achieve a human-machine co-driving friendly system, and the lateral control function is not easily exited after the driver intervenes and takes over control.

[0041] The method provided in this embodiment involves interaction signals between an ADAS (Advanced Driver Assistance System) control module and an EPS (Electronic Power Steering System), an angle request signal, a driver's hand torque, and an execution angle torque limit. The angle request signal indicates the need to control the steering wheel to turn left or right; the driver's hand torque represents the torque generated by the driver's hand holding the steering wheel; and the execution angle torque limit is the maximum torque limit that can be used during the EPS execution angle process.

[0042] like Figure 1 As shown, it includes the following steps:

[0043] In step S1, a base torque A is matched in real time based on vehicle speed. This embodiment acquires vehicle speed information in real time, identifies the speed range it is in, and then matches the base torque A to the speed range. Each speed range is preset with a corresponding base torque A, and base torque A increases as the speed range increases. Specifically, base torque A is set to 2.0 Nm for speeds greater than or equal to 0 km / h and less than 60 km / h; 2.5 Nm for speeds greater than or equal to 60 km / h and less than 90 km / h; and a base torque limit A of 3.0 Nm is set for speeds greater than or equal to 90 km / h.

[0044] In other optional embodiments, the method for determining the basic torque A may also be: after obtaining vehicle speed information in real time and identifying the vehicle speed range in which the vehicle speed is located, the basic torque A corresponding to the vehicle speed range is matched according to the vehicle speed range and the real-time vehicle speed. The matching method is:

[0045] For vehicle speeds greater than or equal to 0 km / h and less than 60 km / h, set the base torque A=1.5+V*0.01;

[0046] For vehicle speeds greater than or equal to 60 km / h and less than 90 km / h, set the base torque A=2+V*0.006;

[0047] For vehicle speeds greater than or equal to 90 km / h, set the basic torque limit to A=2.5+V*0.003;

[0048] The above V is the real-time vehicle speed.

[0049] In step S2, an angle control request is issued to the EPS. The system then obtains and applies torque reduction based on the driver's hand torque B, resulting in a torque limit C. Specifically, the EPS receives the driver's hand torque B and adjusts the torque limit C in real time to equal the base torque A minus the driver's hand torque B. This reduces the torque used by the EPS during angle control and also reduces the perceived resistance felt by the driver. While base torque A remains constant, as driver hand torque B increases, the system's output torque limit C decreases. This creates a trade-off effect, significantly reducing the perceived resistance felt by the driver and the machine. Furthermore, base torque A acts as an upper limit, ensuring the system maintains basic control capabilities.

[0050] Furthermore, when obtaining the driver's hand torque B transmitted by the EPS, since the driver's hand force obtained by the EPS from the sensor is often subject to noise interference, such as road bumps, in order to more robustly calculate the human-machine co-driving torque, step S2 of this embodiment also performs Kalman filtering on the driver's hand torque, performing 12-pole non-order Butterworth filtering with a cutoff frequency of 10 Hz.

[0051] In step S3, the curve compensation torque D is obtained based on the curve radius and added to the torque limit. This step can solve the problem of the torque limit C being too small when the driver holds the steering wheel, which may not meet the cornering performance requirements. Specifically, this embodiment presets corresponding compensation torques D for different curve radius ranges. In a preferred embodiment, when the curve radius is less than or equal to 100m, the preset compensation torque D is 1.5N*m; when the curve radius is greater than 100m and less than or equal to 500m, the preset compensation torque D is 1.0N*m; when the curve radius is greater than 500m and less than or equal to 1500m, the preset compensation torque D is 0.8N*m.

[0052] Furthermore, in step S3 of this embodiment, the curve radius is also identified by:

[0053] Directly measure the vehicle's rotation rate ω around the vertical axis through on-board sensors (such as using an inertial measurement unit, IMU), and obtain the vehicle's longitudinal velocity v1 through a wheel speed meter or GPS speed information. Combine this data to inversely calculate the radius R1 = v1 / ω;

[0054] Use edge detection or lane detection algorithms to identify road boundaries or centerlines, and fit the detected pixels into a smooth curve (e.g., a polynomial curve, a B-spline curve, or an explicit arc). Use the curve fitting equation to calculate the curvature κ of each point on the curve, and calculate the identification curve fitting radius R2 = 1 / |κ|.

[0055] The calculated curve radius is: R = √(R1*R2). In step S4, the vehicle's lane change demand is identified, and a lane change compensation torque F is provided during the vehicle's lane change process and superimposed on the torque limit. When the vehicle is in the process of changing lanes, including whether the driver turns on the light to change lanes or the driver confirms the lane change, there is no additional torque compensation when the vehicle is not in a curve, so there will be insufficient torque during the lane change process. This step takes into account and can effectively solve the torque compensation demand in this scenario, judges the lane change process and provides lane change torque compensation. Specifically, the lane change compensation torque F of this embodiment defaults to 0N*m. When the vehicle is in the process of changing lanes through the vehicle's turn signal status or the driver's lane change confirmation information, the lane change compensation torque F is a fixed value of 1N*m, which is superimposed on the torque limit.

[0056] Furthermore, this embodiment determines that there is a need for the vehicle to change lanes when any of the following scenarios is identified:

[0057] Monitoring lateral displacement: Identifying when the vehicle centerline is offset from the lane centerline by more than 15% of the lane width and continues to increase within a preset timeframe;

[0058] Monitor yaw angle changes: The angle between the vehicle's heading angle and the lane direction is greater than 5° and lasts for more than a preset time range;

[0059] Lateral acceleration monitoring: vehicle lateral acceleration is greater than or equal to 0.3m / s² and less than or equal to 0.6m / s²;

[0060] Turn signal monitoring: The left turn signal or the right turn signal is on.

[0061] In step S5, the integrated torque limit G is calculated and output to the EPS for execution. In this embodiment, the formula for calculating the integrated torque limit G is: Integrated torque limit G = Torque limit C + Curve compensation torque D + Lane change compensation torque F. The EPS uses the calculated integrated torque limit G as the torque upper limit and drives the steering motor to achieve the angle requested by the ADAS control module, ultimately achieving an excellent driver-machine co-driving experience.

[0062] This solution optimizes the human-machine co-driving experience. Based on the current vehicle's intelligent driving controller, this system allows for software algorithm updates without increasing hardware costs, enhancing the user experience of intelligent driving assistance features. Specifically, this embodiment can achieve the following beneficial effects: First, this method dynamically counteracts weakening and responds to driver intervention in real time, resolving the stiffness of traditional angle-controlled steering wheels. Second, this method enables scenario-adaptive compensation, relying on compensation mechanisms for curve radius and lane change status to ensure control stability in complex scenarios. This enables human-machine collaborative optimization, balancing system control requirements with the driver's operational experience by outputting comprehensive torque limits, and improving the usability of intelligent driving features.

[0063] Example 2

[0064] This embodiment provides a human-machine co-driving control system based on steering wheel angle control. Through the cooperation of various modules in the system, the human-machine co-driving control method based on steering wheel angle control described in Example 1 can be implemented.

[0065] like Figure 2 As shown, the system provided by this embodiment includes: an ADAS control module, which can send an angle control request to the EPS; a basic torque acquisition module, which is used to match the corresponding basic torque A according to the vehicle speed; a torque reduction module, which is used to obtain the driver's hand torque B transmitted by the EPS, and obtain the torque limit C according to the basic torque A and the driver's hand torque B; a curve compensation module, which is used to obtain the curve compensation torque D according to the curve radius; a lane change compensation module, which is used to identify the vehicle judgment needs and provide the lane change compensation torque F during the vehicle lane change process and add it to the torque limit; a torque limit output module, which calculates and outputs the comprehensive torque limit G, and the calculation formula of the comprehensive torque limit G is: comprehensive torque limit G=torque limit C+curve compensation torque D+lane change compensation torque F; EPS, which can perform angle control according to the comprehensive torque limit G.

[0066] It should be noted that the explanation of various implementation methods and beneficial effects of the method in the above embodiment 1 is also applicable to this embodiment. To avoid redundancy, it will not be expanded here in detail.

[0067] The above describes the specific embodiments of the present invention. Based on the above description, relevant personnel can make various changes and modifications without departing from the scope of the technical concept of this invention.

Claims

1. A human-machine co-driving control method based on steering wheel angle control, characterized in that: The steps include: In step S1, the vehicle speed information is acquired in real time, and the vehicle speed range is identified. The base torque A is matched according to the vehicle speed range and the real-time vehicle speed. The preset base torque A increases as the vehicle speed range increases. The matching method of the base torque A is: For vehicle speeds greater than or equal to 0 km / h and less than 60 km / h, set the base torque A=1.5+V*0.01; For vehicle speeds greater than or equal to 60 km / h and less than 90 km / h, set the base torque A=2+V*0.006; For vehicle speeds greater than or equal to 90 km / h, the basic torque limit is set to A=2.5+V*0.003; V is the real-time vehicle speed; In step S2, an angle control request is sent to the EPS, and the driver's hand torque B transmitted by the EPS is obtained. The driver's hand torque is filtered using a Kalman filter and a 12-pole, non-order Butterworth filter with a cutoff frequency of 10 Hz. The torque limit C is adjusted in real time to be equal to the base torque A minus the driver's hand torque B. In step S3, the curve compensation torque D is obtained according to the curve radius and added to the torque limit C. The curve radius is identified as follows: The vehicle's rotation rate ω around the vertical axis is measured by the inertial measurement unit, and the vehicle's longitudinal velocity v1 is obtained through the wheel speed meter or GPS speed information. The radius R1 = v1 / ω is calculated by combining the data; Use an edge detection algorithm or a lane detection algorithm to identify the road boundary or centerline, fit the detected pixel points into a smooth curve, calculate the curvature κ of each point on the smooth curve using the curve fitting equation, and calculate the fitting radius R2 = 1 / |κ|; Calculate the curve radius: R = √(R1*R2); In step S4, the vehicle's lane change requirement is identified based on the vehicle's turn signal status or the driver's lane change confirmation information. During the lane change process, a lane change compensation torque F is provided and added to the torque limit C. A lane change requirement is determined when any of the following scenarios is identified: the vehicle's centerline is offset from the lane centerline by more than 15% of the lane width and continues to increase within a preset time range; The angle between the vehicle's heading and the lane direction is greater than 5° and lasts longer than the preset time range; the vehicle's lateral acceleration is greater than or equal to 0.3m / s² and less than or equal to 0.6m / s²; the left turn signal or the right turn signal is on; In step S5, the comprehensive torque limit G is calculated and output to the EPS for execution. The calculation formula of the comprehensive torque limit G is: comprehensive torque limit G = torque limit C + cornering compensation torque D + lane change compensation torque F; The EPS uses the integrated torque limit G as the upper torque limit and drives the steering motor to execute the requested angle.

2. The human-machine co-driving control method based on steering wheel angle control according to claim 1, characterized in that: In step S1 , the basic torque A is set to 2.0 N*m when the vehicle speed is greater than or equal to 0 km / h and less than 60 km / h, the basic torque A is set to 2.5 N*m when the vehicle speed is greater than or equal to 60 km / h and less than 90 km / h, and the basic torque limit A is set to 3.0 N*m when the vehicle speed is greater than or equal to 90 km / h.

3. The human-machine co-driving control method based on steering wheel angle control according to claim 1, characterized in that: In step S3, when the curve radius is less than or equal to 100m, the preset compensation torque D is 1.5N*m; when the curve radius is greater than 100m and less than or equal to 500m, the preset compensation torque D is 1.0N*m; when the curve radius is greater than 500m and less than or equal to 1500m, the preset compensation torque D is 0.8N*m.

4. The human-machine co-driving control method based on steering wheel angle control according to claim 1, characterized in that: In step S4 , when the vehicle is in the process of changing lanes as determined by the vehicle's turn signal status or the driver's lane change confirmation information, the lane change compensation torque F is fixed at 1 N*m and added to the torque limit.

5. A human-machine co-driving control system based on steering wheel angle control, characterized in that: The method for executing the human-machine co-driving control method based on steering wheel angle control according to any one of claims 1 to 4 comprises: ADAS control module, capable of sending angle control requests to EPS; A basic torque acquisition module is used to match the corresponding basic torque A according to the vehicle speed; The torque reduction module is used to obtain the driver's hand torque B transmitted by the EPS and obtain the torque limit C based on the basic torque A and the driver's hand torque B; A curve compensation module is used to obtain a curve compensation torque D according to a curve radius; A lane change compensation module is used to identify the vehicle's lane change requirements and provide a lane change compensation torque F during the vehicle's lane change process and add it to the torque limit; The torque limit output module calculates and outputs the comprehensive torque limit G. The calculation formula of the comprehensive torque limit G is: comprehensive torque limit G = torque limit C + cornering compensation torque D + lane change compensation torque F; EPS can perform angle control based on the comprehensive torque limit G.

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