Parameter adjustment method and device for lateral control of autonomous vehicle

Abstract

The application relates to a parameter adjustment method and device for lateral control of an automatic driving vehicle, and belongs to the technical field of vehicle lateral control. The method comprises the following steps: acquiring vehicle body running information of the vehicle, so that equivalent input instructions and feedback variables for lateral control of the vehicle can be determined according to the vehicle body running information; then low-frequency response ratios and high-frequency response ratios can be obtained according to the equivalent input instructions and the feedback variables; then low-frequency compensation gains and high-frequency compensation gains corresponding to the low-frequency response ratios and the high-frequency response ratios can be obtained respectively; the low-frequency compensation gains and the high-frequency compensation gains of the vehicle can be determined simultaneously, and the working conditions and batches of the vehicle do not need to be considered; further, compensation gains can be determined through the low-frequency compensation gains and the high-frequency compensation gains, so that the corresponding compensation gains of the vehicle can be determined according to the specific conditions of the vehicle, and the stability of the lateral control of the vehicle can be adjusted through the compensation gains.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle lateral control, in particular to a parameter adjustment method and device for automatic driving vehicle lateral control. BACKGROUND

[0002] When the automatic / unmanned system drives the commercial vehicle, the front-end module identifies the relative error relationship between the vehicle and the road and sends it to the control module. The control module calculates the steering wheel angle instruction based on the vehicle dynamics model to control the lateral movement of the commercial vehicle. However, the differences between commercial vehicles result in that the same set of control parameters cannot be adapted to all vehicles of the same model. In addition, due to different working conditions (load, tire pressure, tire wear, steering clearance, etc.) and service life, the state of the same vehicle is different, and the originally adaptable control parameters may cause unstable lateral control. Therefore, the parameter of the lateral movement of the commercial vehicle needs to be controlled according to the state of the vehicle.

[0003] In the prior art, compared with passenger cars, commercial vehicles have large load changes, poor precision of vehicle chassis execution components, and poor consistency of vehicle states, which leads to high requirements for the robustness and adaptability of the control algorithm of the automatic driving vehicle control of the commercial vehicle. In particular, for vehicle lateral control, due to the low execution precision and difference of the steering system EHPS, the large difference of the steering clearance of different vehicles, the large change of the load of the vehicle, and the large change of the tire pressure, the same set of control algorithm is difficult to adapt to vehicles in different working conditions and vehicles in different batches.

[0004] Therefore, it is urgent to provide an online adaptive parameter adjustment method and device for vehicle lateral control to solve the technical problem that the same set of control algorithm cannot be used to adapt the lateral movement parameters of vehicles in different working conditions and vehicles in different batches due to the poor consistency of the state of the commercial vehicle. SUMMARY

[0005] Therefore, it is necessary to provide a parameter adjustment method and device for automatic driving vehicle lateral control to solve the technical problem that the same set of control algorithm cannot be used to adapt the lateral movement parameters of vehicles in different working conditions and vehicles in different batches due to the poor consistency of the state of the commercial vehicle.

[0006] To solve the above problems, the present application provides a parameter adjustment method for automatic driving vehicle lateral control, comprising:

[0007] obtaining vehicle body running information of the vehicle, and determining an equivalent input instruction and a feedback variable for lateral control of the vehicle according to the vehicle body running information;

[0008] obtaining a low-frequency response ratio and a high-frequency response ratio according to the equivalent input instruction and the feedback variable;

[0009] obtaining a low-frequency compensation gain and a high-frequency compensation gain according to the low-frequency response ratio and the high-frequency response ratio respectively;

[0010] determining a compensation gain according to the low-frequency compensation gain and the high-frequency compensation gain, and adjusting a parameter of lateral control according to the compensation gain.

[0011] In a possible implementation manner, the vehicle body running information comprises yaw rate information and chassis steering wheel angle, and the determining of the equivalent input instruction and the feedback variable for the lateral control of the vehicle according to the vehicle body running information comprises:

[0012] obtaining the equivalent input instruction for the lateral control of the vehicle according to the yaw rate information;

[0013] determining the chassis steering wheel angle as the feedback variable, and filtering the chassis steering wheel angle to obtain the equivalent output of the feedback variable.

[0014] In a possible implementation manner, the vehicle body running information further comprises vehicle wheelbase, vehicle speed, understeering slope and lateral acceleration, and the obtaining of the equivalent input instruction for the lateral control of the vehicle according to the yaw rate information comprises:

[0015] calculating the yaw rate information, the vehicle wheelbase and the vehicle speed to obtain a front wheel steering angle;

[0016] calculating the understeering slope and the lateral acceleration to obtain an understeering compensation angle;

[0017] calculating the front wheel steering angle and the understeering compensation angle to obtain an expected steering wheel angle;

[0018] filtering the expected steering wheel angle to obtain the equivalent input instruction.

[0019] In a possible implementation manner, the obtaining of the low-frequency response ratio and the high-frequency response ratio according to the equivalent input instruction and the feedback variable comprises:

[0020] discretizing the equivalent input instruction and the feedback variable in a frequency domain respectively to obtain an input instruction frequency spectrum and a feedback variable frequency spectrum;

[0021] dividing the input instruction frequency spectrum and the feedback variable frequency spectrum to obtain the low-frequency response ratio and the high-frequency response ratio.

[0022] In a possible implementation, the low-frequency compensation gain is obtained according to the low-frequency response ratio, including:

[0023] The low-frequency compensation gain table and the index table are set, different steering wheel angles correspond to different compensation gains in the low-frequency compensation gain table;

[0024] The low-frequency compensation gain table is updated according to the low-frequency response ratio and the index table, and a new low-frequency compensation gain table is obtained;

[0025] The index table is looked up according to the steering wheel control instruction of the vehicle, and an instruction index is obtained;

[0026] The new low-frequency compensation gain table is looked up according to the instruction index, and a low-frequency compensation gain is obtained.

[0027] In a possible implementation, the low-frequency compensation gain table is updated according to the low-frequency response ratio and the index table, and a new low-frequency compensation gain table is obtained, including:

[0028] The low-frequency compensation value is determined according to the low-frequency response ratio and a preset low-frequency range response expectation value;

[0029] The index table is looked up according to the equivalent input of the low-frequency response ratio, and a corresponding low-frequency index is determined;

[0030] The low-frequency compensation gain table is updated according to the low-frequency index and the low-frequency compensation value, and a new low-frequency compensation gain table is obtained.

[0031] In a possible implementation, the low-frequency compensation value is determined according to the low-frequency response ratio and a preset low-frequency range response expectation value, including:

[0032] When the low-frequency response ratio is less than a first preset low-frequency range response expectation value, the first preset low-frequency range response expectation value and the low-frequency response ratio are calculated to obtain a low-frequency compensation value;

[0033] When the low-frequency response ratio is greater than a second preset low-frequency range response expectation value, the second preset low-frequency range response expectation value and the low-frequency response ratio are calculated to obtain a low-frequency compensation value; the first preset low-frequency range response expectation value is less than the second preset low-frequency range response expectation value.

[0034] In a possible implementation, the high-frequency compensation gain is obtained according to the high-frequency response ratio, including:

[0035] When the high-frequency response ratio is greater than a preset high-frequency range response expectation value, the high-frequency range response expectation value and the high-frequency response ratio are calculated to obtain a first high-frequency compensation value;

[0036] According to the high frequency response ratio, a preset high frequency compensation gain table is looked up to determine a second high frequency compensation value;

[0037] The minimum value of the first high frequency compensation value and the second high frequency compensation value is determined as a high frequency compensation gain.

[0038] In a possible implementation, the determining of the compensation gain according to the low frequency compensation gain and the high frequency compensation gain comprises:

[0039] The minimum value of the low frequency compensation gain and the high frequency compensation gain is determined as the compensation gain.

[0040] In another aspect, the application further provides a parameter adjustment device for lateral control of an autonomous vehicle, comprising:

[0041] An information acquisition module is configured to acquire vehicle body running information of the vehicle, and determine an equivalent input instruction and a feedback variable for lateral control of the vehicle according to the vehicle body running information;

[0042] A response ratio determination module is configured to obtain a low frequency response ratio and a high frequency response ratio according to the equivalent input instruction and the feedback variable;

[0043] A gain calculation module is configured to obtain a corresponding low frequency compensation gain and a high frequency compensation gain according to the low frequency response ratio and the high frequency response ratio, respectively;

[0044] A parameter adjustment module is configured to determine a compensation gain according to the low frequency compensation gain and the high frequency compensation gain, and adjust parameters for lateral control according to the compensation gain.

[0045] The application has the advantages that the vehicle body running information of the vehicle is acquired, so that the equivalent input instruction and the feedback variable for lateral control of the vehicle can be determined according to the vehicle body running information, then the low frequency response ratio and the high frequency response ratio can be obtained according to the equivalent input instruction and the feedback variable, and then the corresponding low frequency compensation gain and high frequency compensation gain can be obtained according to the low frequency response ratio and the high frequency response ratio, respectively; thus the low frequency compensation gain and the high frequency compensation gain of the vehicle can be determined simultaneously, and the working conditions and batches of the vehicle do not need to be considered; further, the compensation gain can be determined through the low frequency compensation gain and the high frequency compensation gain, so that the corresponding compensation gain of the vehicle can be determined according to the specific conditions of the vehicle, and then the parameters for lateral control of the vehicle can be adjusted through the compensation gain, thereby realizing the technical problem of self-adaptive adjustment of the lateral motion parameters of vehicles in different working conditions and vehicles in different batches. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1An embodiment flow chart of the parameter adjustment method for the lateral control of the autonomous vehicle provided by the present application is shown in the figure;

[0047] Figure 2 An embodiment flow chart of the equivalent input instruction determination provided by the present application is shown in the figure;

[0048] Figure 3 An embodiment flow chart of the step S103 in the present application Figure 1 is shown in the figure;

[0049] Figure 4 An embodiment flow chart of the step S302 in the present application Figure 3 is shown in the figure;

[0050] Figure 5 An embodiment flow chart of the high-frequency compensation gain calculation provided by the present application is shown in the figure;

[0051] Figure 6 An embodiment structure diagram of the parameter adjustment device for the lateral control of the autonomous vehicle provided by the present application is shown in the figure;

[0052] Figure 7 An embodiment structure diagram of the electronic device provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0053] The preferred embodiments of the present application will be specifically described below with reference to the accompanying drawings, which form a part of this application, and are used to explain the principles of the embodiments of the present application, and are not used to limit the scope of the present application.

[0054] As Figure 1 shown in the figure, one specific embodiment of the present application discloses a parameter adjustment method for the lateral control of an autonomous vehicle, which comprises:

[0055] S101, obtaining the vehicle body running information of the vehicle, and determining the equivalent input instruction and the feedback variable for the lateral control of the vehicle according to the vehicle body running information;

[0056] S102, obtaining the low-frequency response ratio and the high-frequency response ratio according to the equivalent input instruction and the feedback variable;

[0057] S103, obtaining the corresponding low-frequency compensation gain and high-frequency compensation gain according to the low-frequency response ratio and the high-frequency response ratio, respectively;

[0058] S104, determining the compensation gain according to the low-frequency compensation gain and the high-frequency compensation gain, and adjusting the parameters for the lateral control according to the compensation gain.

[0059] In specific embodiments of the present application, the commercial vehicle or other vehicle that can be applied to automatic driving or manual driving is not limited herein. The vehicle body driving information during automatic driving can also be obtained through the CAN bus. The vehicle body driving information can include yaw rate information, chassis steering wheel angle, vehicle speed, vehicle wheelbase, lateral acceleration, etc. The vehicle body driving information can also be obtained through other ways, and the specific obtaining method is not limited herein. Then, the equivalent input instruction and feedback variable for lateral control of the vehicle can be calculated according to the vehicle body driving information. Then, the low-frequency response ratio and the high-frequency response ratio can be calculated through the equivalent input instruction and feedback variable. Because the gain compensation methods of vehicles in different conditions are different, in order to enable vehicles in different conditions to be compensated through the embodiments of the present application, the low-frequency response ratio and the high-frequency response ratio of the vehicle can be calculated at the same time. Then, the corresponding low-frequency compensation gain can be determined through the low-frequency response ratio, and the corresponding high-frequency compensation gain can be determined through the high-frequency response ratio. Then, the compensation gain of the corresponding vehicle can be determined according to the low-frequency compensation gain and the high-frequency compensation gain. For example, when the low-frequency compensation gain of vehicle A is greater than the high-frequency compensation gain, the high-frequency compensation gain can be determined as the compensation gain of vehicle A. Thus, the parameters for lateral control of vehicle A can be adjusted according to the compensation gain, so as to achieve the purpose of identifying the current working condition of the vehicle during automatic driving of the vehicle and adjusting the control parameters online.

[0060] Compared with the prior art, the vehicle body driving information of the vehicle is obtained, so that the equivalent input instruction and feedback variable for lateral control of the vehicle can be determined according to the vehicle body driving information. Then, the low-frequency response ratio and the high-frequency response ratio can be obtained according to the equivalent input instruction and feedback variable. Then, the corresponding low-frequency compensation gain and high-frequency compensation gain can be obtained according to the low-frequency response ratio and the high-frequency response ratio, respectively. Thus, the low-frequency compensation gain and the high-frequency compensation gain of the vehicle can be determined at the same time, and the working condition and batch of the vehicle do not need to be considered. Further, the compensation gain can be determined through the low-frequency compensation gain and the high-frequency compensation gain, so that the corresponding compensation gain of the vehicle can be determined according to the specific situation of the vehicle. Then, the parameters for lateral control of the vehicle can be adjusted through the compensation gain.

[0061] In some embodiments of the present application, the vehicle body driving information includes yaw rate information and chassis steering wheel angle, and step S101 includes:

[0062] The equivalent input instruction for lateral control of the vehicle is obtained according to the yaw rate information.

[0063] The chassis steering wheel angle is determined as the feedback variable, and the chassis steering wheel angle is filtered to obtain the equivalent output of the feedback variable.

[0064] In the specific embodiments of the present application, the vehicle body running information can include yaw rate information and chassis steering wheel angle, which can be obtained through the CAN bus, so that the yaw rate information can be calculated to obtain the equivalent input instruction for controlling the vehicle in the lateral direction, and the chassis steering wheel angle can be determined as the feedback variable, and then the chassis steering wheel angle can be filtered to obtain the equivalent output of the filtered feedback variable , and the specific filtering mode is not limited in the embodiments of the present application.

[0065] In some embodiments of the present application, as shown in Figure 2 , the vehicle body running information further includes vehicle wheelbase, vehicle speed, understeering slope and lateral acceleration, and the equivalent input instruction for controlling the vehicle in the lateral direction is obtained according to the yaw rate information, including:

[0066] S201, calculating the yaw rate information, vehicle wheelbase and vehicle speed to obtain the front wheel angle;

[0067] S202, calculating the understeering slope and lateral acceleration to obtain the understeering compensation angle;

[0068] S203, calculating the front wheel angle and the understeering compensation angle to obtain the expected steering wheel angle;

[0069] S204, filtering the expected steering wheel angle to obtain the equivalent input instruction.

[0070] In the specific embodiments of the present application, the vehicle body running information can further include vehicle wheelbase, vehicle speed, understeering slope and lateral acceleration, and the front wheel angle can be calculated according to the vehicle body angular velocity information with the rear axle of the vehicle as the center, and the calculation is as shown in formula (1):

[0071] (1)

[0072] In the formula, represents the front wheel angle; represents the yaw rate information; is the vehicle wheelbase; V is the vehicle speed.

[0073] Then the understeering slope and the lateral acceleration can be calculated to obtain the understeering compensation angle, and the calculation is as shown in formula (2):

[0074] (2)

[0075] wherein, represents a deficient compensation angle of turning; represents a deficient turning slope, represents a lateral acceleration.

[0076] Then the front wheel turning angle and the deficient compensation angle can be calculated to obtain the expected steering wheel turning angle, and the calculation is shown in formula (3):

[0077] (3)

[0078] The expected steering wheel turning angle is further subjected to a sliding window filtering process to obtain a filtered equivalent input instruction .

[0079] In some embodiments of the present application, the step S102 comprises:

[0080] The equivalent input instruction and the feedback variable are respectively subjected to frequency domain discretization to obtain an input instruction spectrum and a feedback variable spectrum;

[0081] The input instruction spectrum and the feedback variable spectrum are subjected to division processing to obtain a low frequency response ratio and a high frequency response ratio.

[0082] In specific embodiments of the present application, the FFT (Fast Fourier Transform) can be used to calculate the spectrum of the input instruction and the feedback variable, i.e. the input instruction spectrum and the feedback variable spectrum. Specifically, the frequency domain discretization of the input instruction can be performed, as shown in formula (4):

[0083] (4)

[0084] wherein, represents the input instruction spectrum; represents the equivalent input instruction; represents the Euler formula; N= 256, k [1, 256 / 2+1], f = k / N .

[0085] The frequency domain discretization of the feedback variable is shown in formula (5):

[0086] (5)

[0087] wherein, represents the feedback variable spectrum; represents the equivalent output of the feedback variable.

[0088] Then the input instruction spectrum and the feedback variable spectrum can be divided to obtain a low-frequency response ratio and a high-frequency response ratio. Specifically, response data of automatic driving of the vehicle can be counted, a low-frequency band interval is set as in combination with a modal frequency of the vehicle, a high-frequency band interval is set as . Then the low-frequency response ratio and the high-frequency response ratio can be calculated. The low-frequency response ratio is calculated as shown in formula (6):

[0089] (6)

[0090] In the formula, denotes the low-frequency response ratio.

[0091] The high-frequency response ratio is calculated as shown in formula (7):

[0092] (7)

[0093] In the formula, denotes the high-frequency response ratio.

[0094] In some embodiments of the present application, as shown in Figure 3 , in step S103, a low-frequency compensation gain is obtained according to the low-frequency response ratio, including:

[0095] S301, a low-frequency compensation gain table and an index table are set; different steering wheel angles correspond to different compensation gains in the low-frequency compensation gain table;

[0096] S302, the low-frequency compensation gain table is updated according to the low-frequency response ratio and the index table to obtain a new low-frequency compensation gain table;

[0097] S303, the index table is looked up according to the steering wheel control instruction of the vehicle to obtain an instruction index;

[0098] S304, the new low-frequency compensation gain table is looked up according to the instruction index to obtain the low-frequency compensation gain.

[0099] In specific embodiments of the present application, the low-frequency compensation gain table and the index table can be set according to actual conditions, wherein different steering wheel angles correspond to different compensation gains in the low-frequency compensation gain table, and the index table can be key =[-20, -10, -7.5, -5, -2.5, -1, 0, 1, 2.5, 5, 7.5, 10, 20], the compensation gain in the low-frequency compensation gain table can be determined according to the index in the index table. Before the low-frequency compensation gain is determined, the low-frequency compensation gain table needs to be updated, and the specific updating process is as follows. In some embodiments of the present application, as shown in Figure 4 , step S302 includes:

[0100] S401, determining a low-frequency compensation value according to the low-frequency response ratio and a preset low-frequency range response expectation value;

[0101] S402, determining a corresponding low-frequency index according to the equivalent input of the low-frequency response ratio and a lookup index table;

[0102] S403, updating the low-frequency compensation gain table according to the low-frequency index and the low-frequency compensation value to obtain a new low-frequency compensation gain table.

[0103] In specific embodiments of the application, the low-frequency compensation value can be calculated according to the difference between the low-frequency response ratio and the preset low-frequency range response expectation value. Specifically, in some embodiments of the application, step S401 includes:

[0104] When the low-frequency response ratio is less than the first preset low-frequency range response expectation value, the first preset low-frequency range response expectation value and the low-frequency response ratio are calculated to obtain the low-frequency compensation value.

[0105] When the low-frequency response ratio is greater than the second preset low-frequency range response expectation value, the second preset low-frequency range response expectation value and the low-frequency response ratio are calculated to obtain the low-frequency compensation value. The first preset low-frequency range response expectation value is less than the second preset low-frequency range response expectation value.

[0106] In specific embodiments of the application, the first preset low-frequency range response expectation value and the second preset low-frequency range response expectation value can be set according to the first preset low-frequency range response expectation value and the second preset low-frequency range response expectation value to set the compensation to three segments, with ranges of respectively. When the low-frequency response ratio is less than the first preset low-frequency range response expectation value, the first preset low-frequency range response expectation value and the low-frequency response ratio are calculated to obtain the low-frequency compensation value. When the low-frequency response ratio is greater than the second preset low-frequency range response expectation value, the second preset low-frequency range response expectation value and the low-frequency response ratio are calculated to obtain the low-frequency compensation value. The first preset low-frequency range response expectation value is less than the second preset low-frequency range response expectation value. The specific calculation process is shown in formula (8):

[0107] (8)

[0108] Thus, according to the size of the low-frequency response ratio, the corresponding calculation formula can be selected to calculate the low-frequency compensation value.

[0109] Further, the low-frequency compensation gain table is related to the steering wheel angle. Different compensation gains corresponding to different steering wheel angles can be found according to the equivalent input of the low-frequency response ratio to find the corresponding low-frequency index indexThen, the corresponding low-frequency compensation gain table can be updated according to the relationship between the index table and the low-frequency compensation gain table table [index] = Thus, the updated new low-frequency compensation gain table can be obtained.

[0110] Further, the lateral control algorithm can be used to calculate the data of the vehicle to obtain the lateral control amount of the vehicle, i.e., the steering wheel control instruction. The specific lateral control algorithm and calculation process can be set according to actual conditions, and the embodiments of the present application are not limited thereto. Then, the index table can be looked up according to the steering wheel control instruction to obtain the current corresponding instruction index. Then, the new low-frequency compensation gain table is looked up according to the instruction index, and thus the low-frequency compensation gain expected in the current working condition can be obtained K1 .

[0111] In some embodiments of the present application, as shown in step S103, Figure 5 the high-frequency compensation gain is obtained according to the high-frequency response ratio, including:

[0112] S501, when the high-frequency response ratio is greater than the preset high-frequency band response expectation value, the high-frequency band response expectation value and the high-frequency response ratio are calculated to obtain a first high-frequency compensation value;

[0113] S502, the preset high-frequency compensation gain table is looked up according to the equivalent input of the high-frequency response ratio to determine a second high-frequency compensation value;

[0114] S503, the minimum value of the first high-frequency compensation value and the second high-frequency compensation value is determined as the high-frequency compensation gain.

[0115] In specific embodiments of the present application, the preset high-frequency compensation gain table and the preset high-frequency band response expectation value can be set. The preset high-frequency compensation gain table and the preset high-frequency band response expectation value can be set according to actual conditions, so that the corresponding calculation formula can be selected according to the size of the high-frequency response ratio. The specific formula is shown in formula (9):

[0116] (9)

[0117] Thus, the first high-frequency compensation value can be calculated according to formula (9) . Then, the preset high-frequency compensation gain table is looked up according to the equivalent input of the high-frequency response ratio to determine the second high-frequency compensation value K2 = min .

[0118] ​In some embodiments of the present application, step S104 comprises:

[0119] The minimum value of the low-frequency compensation gain and the high-frequency compensation gain is determined as the compensation gain.

[0120] In specific embodiments of the present application, after obtaining the low-frequency compensation gain and the high-frequency compensation gain, the minimum value of the low-frequency compensation gain and the high-frequency compensation gain can be determined as the compensation gain K = min ( K1, K2 ).

[0121] Further, the lateral control amount of the vehicle can be adjusted online by the obtained compensation gain to ensure the stability of the lateral control of the vehicle under different working conditions.

[0122] In embodiments of the present application, for different vehicles of the same vehicle type, the differences of the commercial vehicle chassis execution components are large, and the load differences caused by different load capacities are large; at the same time, the wear and tear of the execution components and the changes of the clearances caused by the increase of the use time of the same vehicle will all cause the changes of the lateral control performance of the vehicle. Therefore, for the vehicle lateral control algorithm, in addition to meeting the stability and precision problems of different vehicles, it also needs to adapt to the differences caused by the changes of the working conditions of the vehicle. The online adaptive parameter adjustment method for lateral control proposed in embodiments of the present application solves the problem of the stability of the vehicle lateral control, which is crucial in the engineering of vehicle control. The technology of embodiments of the present application mainly reflects in two aspects:

[0123] First, the FFT method is used to identify the changes of the vehicle state online from the perspective of the frequency domain: the current working condition of the vehicle is identified online by real-time extraction of the vehicle body information; when the vehicle state changes, it can be quickly identified and the parameters are adjusted adaptively to make countermeasures to ensure the stability of the lateral control, and the adaptability of the lateral control algorithm is wider;

[0124] Second, online parameter adaptive adjustment: the performance of the vehicle under the standard working condition is extracted as the expected value, and when the vehicle state changes, i.e. the vehicle state deviates from the expected value, the gain required by the vehicle to reach the target state is calculated online to compensate for the current vehicle state; the purpose of achieving the stability of the lateral control when the vehicle state changes is achieved.

[0125] In order to better implement the parameter adjustment method of the automatic driving vehicle lateral control in embodiments of the present application, on the basis of the parameter adjustment method of the automatic driving vehicle lateral control, correspondingly, embodiments of the present application also provide a parameter adjustment device for automatic driving vehicle lateral control, as shown in Figure 6 Fig. 6, the parameter adjustment device for automatic driving vehicle lateral control 600 comprises:

[0126] The information acquisition module 601 is configured to acquire vehicle body running information of the vehicle, and determine an equivalent input instruction and a feedback variable for lateral control of the vehicle according to the vehicle body running information.

[0127] The response ratio determination module 602 is configured to obtain a low-frequency response ratio and a high-frequency response ratio according to the equivalent input instruction and the feedback variable.

[0128] The gain calculation module 603 is configured to obtain a low-frequency compensation gain and a high-frequency compensation gain corresponding to the low-frequency response ratio and the high-frequency response ratio, respectively.

[0129] The parameter adjustment module 604 is configured to determine a compensation gain according to the low-frequency compensation gain and the high-frequency compensation gain, and adjust parameters of the lateral control according to the compensation gain.

[0130] The parameter adjustment device 600 for lateral control of the autonomous vehicle provided in the above embodiment can implement the technical solutions described in the parameter adjustment method for lateral control of the autonomous vehicle, and the principles of the implementation of the above modules or units can be referred to the corresponding content in the parameter adjustment method for lateral control of the autonomous vehicle, which will not be described here.

[0131] As shown in FIG. 7, the present application also provides an electronic device 700. Figure 7 The electronic device 700 includes a processor 701, a memory 702, and a display 703. Figure 7 Only some components of the electronic device 700 are shown, but it should be understood that all the shown components are not required, and more or less components can be alternatively implemented.

[0132] The memory 702 can be an internal storage unit of the electronic device 700 in some embodiments, such as a hard disk or a memory of the electronic device 700.

[0133] Further, the memory 702 is an internal storage unit of the electronic device 700. The memory 702 is used to store application software and various data installed in the electronic device 700.

[0134] The processor 701 can be a central processing unit (CPU), a microprocessor, or other data processing chip in some embodiments, and is used to run program codes or process data stored in the memory 702, such as the parameter adjustment method for lateral control of the autonomous vehicle in the present application.

[0135] The display 703 can be, in some embodiments, an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) toucher, and the like. The display 703 is used to display information of the electronic device 700 and to display a visualized user interface. The components 701-703 of the electronic device 700 communicate with each other through a system bus.

[0136] In some embodiments of the present application, when the processor 701 executes the parameter adjustment program of the lateral control of the autonomous vehicle in the memory 702, the following steps can be implemented:

[0137] Obtaining the body running information of the vehicle, and determining the equivalent input instruction and feedback variable for the lateral control of the vehicle according to the body running information;

[0138] Obtaining the low-frequency response ratio and the high-frequency response ratio according to the equivalent input instruction and the feedback variable;

[0139] Obtaining the corresponding low-frequency compensation gain and high-frequency compensation gain according to the low-frequency response ratio and the high-frequency response ratio, respectively;

[0140] Determining the compensation gain according to the low-frequency compensation gain and the high-frequency compensation gain, and adjusting the parameters of the lateral control according to the compensation gain.

[0141] It should be understood that, in addition to the above functions, the processor 701 can also implement other functions when executing the parameter adjustment program of the lateral control of the autonomous vehicle in the memory 702. For details, please refer to the description of the corresponding method embodiments.

[0142] Further, the type of the electronic device 700 referred to in the embodiments of the present application is not specifically limited, and the electronic device 700 can be a portable electronic device such as a mobile phone, a tablet computer, a laptop, and the like. Exemplary embodiments of the portable electronic device include, but are not limited to, a portable electronic device running an IOS, a Linux, a Microsoft operating system. It should also be understood that, in some other embodiments of the present application, the electronic device 700 can also be a desktop computer having a touch-sensitive surface (such as a touch panel).

[0143] Correspondingly, the embodiments of the present application also provide a computer-readable storage medium for storing computer-readable programs or instructions, which, when executed by a processor, can implement the parameter adjustment method steps or functions of the lateral control of the autonomous vehicle provided by the above method embodiments.

[0144] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiment methods can be instructed by a computer program to relevant hardware (such as a processor, a controller, etc.) to complete, and the computer program can be stored in a computer readable storage medium.

[0145] The parameter adjustment method and device for lateral control of an autonomous vehicle provided by the present application are described in detail above, and the principles and implementation manners of the present application are described by applying specific examples. The above description of the embodiments is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manners and application ranges will be changed, and the above description of the present application should not be understood as a limitation.

Claims

1. A parameter adjustment method for lateral control of an autonomous driving vehicle, characterized in that: include: Acquiring vehicle body driving information, and determining equivalent input instructions and feedback variables for lateral control of the vehicle based on the vehicle body driving information; Obtaining a low-frequency response ratio and a high-frequency response ratio according to the equivalent input instruction and the feedback variable; Obtaining a corresponding low-frequency compensation gain and a corresponding high-frequency compensation gain according to the low-frequency response ratio and the high-frequency response ratio respectively; determining a compensation gain according to the low-frequency compensation gain and the high-frequency compensation gain, and adjusting a parameter of lateral control according to the compensation gain; Obtaining a low-frequency response ratio and a high-frequency response ratio according to the equivalent input instruction and the feedback variable includes: Discretizing the equivalent input command and the feedback variable in the frequency domain respectively to obtain an input command spectrum and a feedback variable spectrum; The input instruction spectrum and the feedback variable spectrum are divided and processed to obtain a low-frequency response ratio and a high-frequency response ratio.

2. The parameter adjustment method for lateral control of an autonomous driving vehicle according to claim 1, characterized in that: The vehicle body driving information includes yaw angular velocity information and chassis steering wheel angle, and determining the equivalent input command and feedback variable for lateral control of the vehicle based on the vehicle body driving information includes: obtaining an equivalent input instruction for lateral control of the vehicle according to the yaw angular velocity information; The chassis steering wheel angle is determined as a feedback variable, and the chassis steering wheel angle is filtered to obtain an equivalent output of the feedback variable.

3. The parameter adjustment method for lateral control of an autonomous driving vehicle according to claim 2, characterized in that: The vehicle driving information further includes vehicle wheelbase, vehicle speed, understeer slope, and lateral acceleration. Obtaining an equivalent input instruction for lateral control of the vehicle based on the yaw rate information includes: Calculating the yaw rate information, the vehicle wheelbase, and the vehicle speed to obtain a front wheel steering angle; Calculating the understeering slope and the lateral acceleration to obtain an understeering compensation angle; Calculating the front wheel steering angle and the undercompensation angle to obtain a desired steering wheel steering angle; The desired steering wheel angle is filtered to obtain an equivalent input instruction.

4. The parameter adjustment method for lateral control of an autonomous driving vehicle according to claim 1, characterized in that: According to the low-frequency response ratio, a low-frequency compensation gain is obtained, including: Setting a low-frequency compensation gain table and an index table; different steering wheel angles in the low-frequency compensation gain table correspond to different compensation gains; updating the low-frequency compensation gain table according to the low-frequency response ratio and the index table to obtain a new low-frequency compensation gain table; Look up the index table according to the steering wheel control command of the vehicle to obtain a command index; The new low-frequency compensation gain table is looked up according to the instruction index to obtain the low-frequency compensation gain.

5. The parameter adjustment method for lateral control of an autonomous driving vehicle according to claim 4, characterized in that: The updating of the low-frequency compensation gain table according to the low-frequency response ratio and the index table to obtain a new low-frequency compensation gain table includes: determining a low-frequency compensation value according to the low-frequency response ratio and a preset low-frequency band response expected value; Searching the index table according to the equivalent input of the low frequency response ratio to determine the corresponding low frequency index; The low-frequency compensation gain table is updated according to the low-frequency index and the low-frequency compensation value to obtain a new low-frequency compensation gain table.

6. The parameter adjustment method for lateral control of an autonomous driving vehicle according to claim 5, characterized in that: The determining of the low-frequency compensation value according to the low-frequency response ratio and a preset low-frequency band response expected value includes: When the low-frequency response ratio is less than a first preset low-frequency band response expected value, calculating the first preset low-frequency band response expected value and the low-frequency response ratio to obtain a low-frequency compensation value; When the low-frequency response ratio is greater than a second preset low-frequency band response expected value, the second preset low-frequency band response expected value and the low-frequency response ratio are calculated to obtain a low-frequency compensation value; and the first preset low-frequency band response expected value is less than the second preset low-frequency band response expected value.

7. The parameter adjustment method for lateral control of an autonomous driving vehicle according to claim 1, characterized in that: According to the high frequency response ratio, a high frequency compensation gain is obtained, including: When the high frequency response ratio is greater than a preset high frequency band response expected value, calculating the high frequency band response expected value and the high frequency response ratio to obtain a first high frequency compensation value; searching a preset high-frequency compensation gain table according to an equivalent input of the high-frequency response ratio to determine a second high-frequency compensation value; A minimum value between the first high frequency compensation value and the second high frequency compensation value is determined as a high frequency compensation gain.

8. The parameter adjustment method for lateral control of an autonomous driving vehicle according to claim 1, characterized in that: The determining of the compensation gain according to the low-frequency compensation gain and the high-frequency compensation gain includes: A minimum value of the low-frequency compensation gain and the high-frequency compensation gain is determined as the compensation gain.

9. A parameter adjustment device for lateral control of an autonomous driving vehicle, characterized in that: include: an information acquisition module, configured to acquire vehicle body driving information and determine equivalent input instructions and feedback variables for lateral control of the vehicle based on the vehicle body driving information; a response ratio determination module, configured to obtain a low-frequency response ratio and a high-frequency response ratio according to the equivalent input instruction and the feedback variable; a gain calculation module, configured to obtain a corresponding low-frequency compensation gain and a corresponding high-frequency compensation gain according to the low-frequency response ratio and the high-frequency response ratio respectively; a parameter adjustment module, configured to determine a compensation gain according to the low-frequency compensation gain and the high-frequency compensation gain, and adjust a parameter of lateral control according to the compensation gain; Obtaining a low-frequency response ratio and a high-frequency response ratio according to the equivalent input instruction and the feedback variable includes: Discretizing the equivalent input command and the feedback variable in the frequency domain respectively to obtain an input command spectrum and a feedback variable spectrum; The input instruction spectrum and the feedback variable spectrum are divided and processed to obtain a low-frequency response ratio and a high-frequency response ratio.

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