A human-machine co-driving steering control method for an intelligent driving system

Abstract

The present invention discloses a human-machine co-driving steering control method for an intelligent driving system, comprising: when the vehicle intelligent driving system controls the steering, identifying the torque τ0 exerted by the driver on the steering wheel; calculating the average value of the steering wheel torque within a certain time T0 #imgabs0# and calculating the intelligent driving system steering wheel steering control weight coefficient α according to #imgabs1#; performing slope restriction and smooth output on α to obtain the slope-restricted control weight coefficient α', so that it changes continuously; when the driver has a strong intention to intervene, adjusting the driving state of the vehicle; outputting the slope-restricted control weight coefficient α' to EPS along with the steering wheel angle control command of the intelligent driving system. The present invention can enable the vehicle to achieve smooth transition and seamless switching in the three driving states of the intelligent driving system control state, the human-machine co-driving state, and the driver control state, greatly improving the driving experience and the utilization rate of the intelligent driving function.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent driving vehicles, and in particular relates to a human-machine co-driving steering control method of an intelligent driving system. Background Art

[0002] In the L2 and L3 intelligent driving functions, lateral control mainly includes lane keeping assist, lane centering assist, intelligent navigation assist and other functions, which are mainly short-term lateral intervention and long-term lateral control. However, L2 and L3 intelligent driving require drivers not to drive hands-free for a long time to ensure that the driver is responsible for the safety of the vehicle. But taking lane centering control as an example, if the driver needs to fine-tune the driving position of the vehicle within the lane line, the traditional steering control function is an "either-or" mode, either the intelligent driving is in full control, and when the driver's torque is large, it is recognized as manual intervention, and the intelligent driving function releases the steering wheel control to downgrade to only longitudinal control mode or exit mode. The driving experience is poor, and the use rate of intelligent driving is not high, which is easy to cause user complaints. It may even be difficult for the driver to take over in an emergency due to the large intervention torque of the intelligent driving function, resulting in dangerous situations. Summary of the invention

[0003] The purpose of the present invention is to provide a human-machine co-driving steering control method for an intelligent driving system, which can enable the vehicle to achieve smooth transition and seamless switching among the three driving states of intelligent driving system control state, human-machine co-driving state, and driver idling state, thereby greatly improving the driving experience and greatly improving the utilization rate of the intelligent driving function and user satisfaction.

[0004] In order to solve the above technical problems, the technical solution of the present invention is: a human-machine co-driving steering control method of an intelligent driving system, comprising the following steps:

[0005] When the vehicle intelligent driving system controls the steering, the steering wheel torque sensor identifies the rotational torque τ0 applied by the driver on the steering wheel;

[0006] Calculate the average steering wheel torque within a certain period of time T0

[0007] according to Calculate the steering wheel steering control weight coefficient α of the intelligent driving system;

[0008] Slope limiting and smoothing the output of α is used to obtain the control weight coefficient α' after slope limiting, so that it can change continuously;

[0009] When the driver has a strong intention to intervene, that is, the rotation torque recognized by the steering wheel torque sensor exceeds the maximum intervention torque and the maintenance time reaches the time threshold ΔT, the driving state of the vehicle is adjusted;

[0010] The control weight coefficient α' after slope limitation is output to the EPS electronic steering power system along with the steering wheel angle control command of the intelligent driving system.

[0011] The average square of the steering wheel torque The calculation method is:

[0012]

[0013] Where N is the number of sampling cycles within T0.

[0014] The calculation method of the control weight coefficient α is:

[0015]

[0016] Among them, τ min is the minimum intervention torque, τ min ∈[0,1]N m , when the steering wheel torque sensor recognizes that the driver's torque on the steering wheel is less than or equal to τ min When τ max is the maximum intervention torque, τ max ∈[1,2]Nm, when the steering wheel torque sensor recognizes that the driver's torque on the steering wheel is greater than or equal to τ max When α min To control the minimum value of the weight coefficient, α min ∈[0,0.2]; α max To control the minimum value of the weight coefficient, α max ∈[0.4,1].

[0017] According to the size of the control weight coefficient α, there are the following judgment rules:

[0018] (1) When the absolute value of the average steering wheel torque When it is less than or equal to the minimum intervention torque, the vehicle is in the control state of the intelligent driving system, and the control weight coefficient α is 1;

[0019] (2) When the absolute value of the average steering wheel torque When the vehicle is between the minimum intervention torque and the maximum intervention torque, it is in a human-machine co-driving state, and the control weight coefficient α decreases as the average steering wheel torque increases. min ,α max ] to adjust between;

[0020] (3) When the absolute value of the average steering wheel torque When the maximum intervention torque is exceeded, the vehicle is in driver control and the control weight coefficient α is kept at the minimum value αmin .

[0021] The calculation method of limiting the slope k in the slope limiting smoothing output is:

[0022]

[0023] Wherein, k1 is the first change rate of the control weight coefficient, k1∈[1,10], k2 is the second change rate of the control weight coefficient, k2∈[0.1,1], and the unit is 1 / s.

[0024] T0 is a calibratable value, T0∈[0.1s,1s].

[0025] The time threshold ΔT is 1s.

[0026] A computer device is also provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above methods when executing the computer program.

[0027] A computer-readable storage medium is also provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention uses a filtering algorithm module to identify the driver's steering wheel torque, judge the driver's intention to take over, and distribute the weights of intelligent driving and manual driving according to the driver's willingness to take over. This weight distribution coefficient controls the torque limit threshold when the EPS electronic steering power system executes the steering wheel angle control command, and can adjust the force acting on the steering column when the EPS electronic steering power system controls the steering wheel to respond to the angle control command, and then feedback to the driver's hand torque feeling. Through this intelligent driving system steering human-machine co-driving control method, the vehicle can achieve smooth transition and seamless switching in the three driving states of intelligent driving system control state, human-machine co-driving state, and driver control state, greatly improving the driving experience, and greatly improving the utilization rate and user satisfaction of intelligent driving functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Schematic diagram of the change of the control weight coefficient with the average value of the steering wheel torque in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0032] (1) When the vehicle is steering controlled by the intelligent driving system, the steering wheel torque sensor identifies the torque τ0 applied by the driver on the steering wheel.

[0033] (2) Calculate the square average of the steering wheel torque during time T0 (which can be calibrated, generally T0∈[0.1s,1s])

[0034]

[0035] Where N is the number of sampling cycles within T0, is the steering wheel torque value after filtering during T0. (3) According to Calculate the steering wheel steering control weight coefficient α of the intelligent driving system, such as Figure 1 shown.

[0036]

[0037] Among them, τ min is the minimum intervention torque, generally τ min ∈[0,1]Nm, below this torque, the driver is considered to have no intention to intervene; τ max is the maximum intervention torque, generally τ max ∈[1,2]Nm. When this torque is exceeded, it is considered that the driver has a greater willingness to intervene.

[0038] a) When the average steering wheel torque When the torque is less than the minimum intervention torque, the steering wheel is completely controlled by the intelligent driving system, and the control weight coefficient is 100%;

[0039] b) When the steering wheel torque average When the torque is between the minimum and maximum intervention torque, it is the human-machine co-driving state. The control weight coefficient decreases as the average steering wheel torque increases. min ,α max ] is adjusted between . Generally set to α min ∈[0,0.2],α max ∈[0.4,1].

[0040] c) When the steering wheel torque average When the maximum intervention torque is exceeded, it is the driver control state, and the control weight coefficient is kept at the minimum value α min If α is set min >0, the driver can still maintain a certain hand feeling when a large torque is involved, and feel the slight steering action of the intelligent driving system. min =0, when the driver intervenes with a large torque, the steering wheel is completely controlled by the driver, and the intelligent driving system does not apply torque response to the steering control command.

[0041] (4) The calculated weight coefficient α is output with slope limitation and smoothing to make it change continuously.

[0042] The limiting slope k is calculated as follows:

[0043]

[0044] Among them, generally k1∈[1,10], generally k2∈[0.1,1], the unit is 1 / s, which represents the rate of change of the control weight coefficient. max The above calculation method is to make the rise and fall faster in the high range, and the fall faster and rise slower in the low range. The control weight coefficient falls faster so that the intelligent driving system can release the steering faster when the driver intervenes, so that the driver can feel the takeover obstacle as little as possible. The rise is slower in the first range so that when the driver no longer intervenes in the steering, the intelligent driving system can slowly restore control of the driving right. The control weight coefficient after slope limitation is α'

[0045] (5) When the driver intervenes strongly, the strong intervention state is maintained for at least a period of time.

[0046] When the control weight coefficient passes the slope limit, if α'=α min , it is considered that the current driver has a strong intention to intervene and is in a state of full driver control. Trigger α'=α min When α'=α, keep at least ΔT (usually about 1s) to make α'=α min , so that when the driver takes over the steering control during this period, the intelligent driving system will not immediately resume the control transition of the steering (if α is set min >0, only a slight control weight coefficient of the intelligent driving system on the steering is retained to provide the driver with a slight hand torque feedback). (6) The control weight coefficient processed as above is output to the EPS electronic steering assist system along with the steering wheel angle control command of the intelligent driving system.

[0047] When the EPS system responds to the steering wheel angle control command, the control weight coefficient is used to adjust the rotation torque limit acting on the steering motor and the steering column to achieve smooth processing of the driver's hand torque feeling. The above control method can achieve a smooth transition between the three modes of intelligent driving system control, human-machine co-driving control, and driver control, bringing a comfortable, safe, and convenient experience to the driver when using the intelligent driving system.

[0048] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A human-machine co-driving steering control method for an intelligent driving system, characterized in that: The following steps are involved: When the vehicle intelligent driving system controls the steering, the steering wheel torque sensor identifies the rotational torque τ0 applied by the driver on the steering wheel; Calculate the average steering wheel torque within a certain period of time T0 according to Calculate the steering wheel steering control weight coefficient α of the intelligent driving system; Slope limiting and smoothing the output of α is used to obtain the control weight coefficient α' after slope limiting, so that it can change continuously; When the driver has a strong intention to intervene, that is, the rotation torque recognized by the steering wheel torque sensor exceeds the maximum intervention torque and the maintenance time reaches the time threshold ΔT, the driving state of the vehicle is adjusted; The control weight coefficient α' after slope limitation is output to the EPS electronic steering power system along with the steering wheel angle control command of the intelligent driving system.

2. The method for controlling human-machine co-driving steering in an intelligent driving system according to claim 1, characterized in that: The square average of the steering wheel torque The calculation method is: Where N is the number of sampling cycles within T0.

3. The method for controlling human-machine co-driving steering in an intelligent driving system according to claim 1, characterized in that: The calculation method of the control weight coefficient α is: Among them, τ min is the minimum intervention torque, τ min ∈[0,1]Nm, when the steering wheel torque sensor recognizes that the driver's torque on the steering wheel is less than or equal to τ min When τ max is the maximum intervention torque, τ max ∈[1,2]Nm, when the steering wheel torque sensor recognizes that the driver's torque on the steering wheel is greater than or equal to τ max When α min To control the minimum value of the weight coefficient, α min ∈[0,0.2]; α max To control the minimum value of the weight coefficient, α max ∈[0.4,1].

4. The method for controlling human-machine co-driving steering in an intelligent driving system according to claim 3, characterized in that: According to the size of the control weight coefficient α, there are the following judgment rules: (1) When the absolute value of the average steering wheel torque When it is less than or equal to the minimum intervention torque, the vehicle is in the control state of the intelligent driving system, and the control weight coefficient α is 1; (2) When the absolute value of the average steering wheel torque When the vehicle is between the minimum intervention torque and the maximum intervention torque, it is in a human-machine co-driving state, and the control weight coefficient α decreases as the average steering wheel torque increases. min ,α max ] to adjust between; (3) When the absolute value of the average steering wheel torque When the maximum intervention torque is exceeded, the vehicle is in driver control and the control weight coefficient α is kept at the minimum value α min .

5. The method for controlling human-machine co-driving steering in an intelligent driving system according to claim 3, characterized in that: The calculation method of limiting the slope k in the slope limiting smoothing output is: Wherein, k1 is the first change rate of the control weight coefficient, k1∈[1,10], k2 is the second change rate of the control weight coefficient, k2∈[0.1,1], and the unit is 1 / s.

6. The method for controlling human-machine co-driving steering in an intelligent driving system according to claim 1, characterized in that: T0 is a calibratable value, T0∈[0.1s,1s].

7. The method for controlling human-machine co-driving steering in an intelligent driving system according to claim 1, characterized in that: The time threshold ΔT is 1s.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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