Target object chassis control method and system, electronic device and medium

Abstract

The application relates to the field of automatic driving test, in particular to a target object chassis control method and system, an electronic device and a medium. The control method is suitable for a virtual control input device that can be recognized by original driving software of a target object chassis, and is used as a unified control entrance between an upper test module and a chassis execution layer. The method comprises the following steps: receiving output data of the upper test control module as task input of the target object chassis; generating expected physical quantities according to the task input and real-time pose feedback information of the target object chassis; converting the expected physical quantities into virtual control inputs recognizable by the original driving software of the chassis based on a pre-established control quantity-vehicle physical quantity mapping relationship; and sending the virtual control inputs into the original driving software of the chassis so that the original driving software of the chassis drives the target object chassis to perform corresponding movements. The application can realize automatic closed-loop control of the target object chassis, dynamic game scenario reproduction, low platform migration cost and self-controllable technology implementation.

Description

Technical Field

[0001] This application relates to the field of autonomous driving testing, and more specifically, to a target chassis control method, system, electronic device, and medium. Background Technology

[0002] In simulation and real-vehicle closed-loop testing of autonomous vehicles, soft target vehicles, pedestrians, and two-wheeled vehicles are often used as dynamic obstacles or adversaries to reproduce typical scenarios such as rear-end collisions, cut-ins, crossings, emergency braking, and obstacle avoidance, thus forming a repeatable and quantifiable safety assessment process. As autonomous driving functions evolve to higher levels, testing requirements are gradually shifting from single-function verification to systematic verification of closed-loop interaction, adversarial strategies, and edge case coverage capabilities. Therefore, the target chassis is required not only to execute a predetermined trajectory but also to adjust its motion behavior in real time according to the state of the vehicle under test.

[0003] However, existing target chassis typically rely on manual handles or dedicated software interfaces for control, resulting in closed control entry points and difficulty in directly connecting to upper-level automatic control or game algorithms. Even if a certain degree of software control can be achieved, it often remains at the level of communication access, handle simulation, or single control links. There is a lack of a closed-loop virtual control method system that unifies task command input, pose feedback analysis, longitudinal and lateral collaborative control, control quantity-physical response mapping, and mode safety management without modifying the original chassis drive software and control protocol. This leads to difficulties in reproducing dynamic game scenarios, insufficient test consistency, and high platform migration costs.

[0004] In view of the above, this application is hereby submitted. Summary of the Invention

[0005] The purpose of this application is to provide a target chassis control method, system, electronic device and medium to solve the problems of existing technologies such as inability to achieve automatic and closed-loop control, difficulty in reproducing dynamic game scenarios, high platform migration costs and lack of independent controllability.

[0006] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application provides a target chassis control method applicable to virtual control input devices that can be recognized by the original drive software of the target chassis, wherein the virtual control input device serves as a unified control entry point between the upper-level test module and the chassis execution layer; the method includes: The system receives output data from the upper-level test control module as task input for the target chassis. The output data includes at least one of the following: reference trajectory, target speed, target position, or interaction strategy command. Based on the task input and the real-time pose feedback information of the target chassis, expected physical quantities are generated; the expected physical quantities include the expected longitudinal acceleration and the expected equivalent front wheel rotation angle. Based on the pre-established mapping relationship between control quantity and vehicle physical quantity, the desired physical quantity is converted into a virtual control input that can be recognized by the original chassis drive software; The virtual control input is sent to the original chassis drive software so that the original chassis drive software drives the target chassis to perform corresponding movements.

[0007] In some technical solutions, the receiving of output data from the upper-level test control module serves as the task input for the target chassis. The output data includes at least one of the following: reference trajectory, target speed, target position, or interaction strategy instructions. The system receives output data from the upper-level test control module, unpacks, extracts, and cleans the output data, and then uses it as the task input for the target chassis.

[0008] In some technical solutions, generating the desired physical quantity based on the task input and the real-time pose feedback information of the target chassis includes: Based on the real-time pose feedback information of the target chassis, data validity verification, pose data parsing, velocity conversion and coordinate conversion are performed to obtain the real-time pose information of the usable state. Based on the task input and the real-time pose information of the available state, the desired physical quantity is generated.

[0009] In some technical solutions, the mapping relationship between control quantities and vehicle physical quantities is constructed in the following way: Based on the chassis calibration test data of the target object, the mapping relationship between control quantity and vehicle physical quantity is determined. The mapping relationship between control quantity and vehicle physical quantity includes: the mapping relationship between longitudinal control quantity and longitudinal acceleration, and the mapping relationship between lateral control quantity and equivalent front wheel steering angle.

[0010] In some technical solutions, the step of converting the desired physical quantity into a virtual control input recognizable by the original chassis drive software based on a pre-established mapping relationship between control quantity and vehicle physical quantity includes: Based on the pre-established mapping relationship between control quantity and vehicle physical quantity, the desired physical quantity is converted into virtual control input data, which is divided into continuous control quantity and discrete function quantity according to data type. The continuous control quantity is normalized and limited; Press or release control is performed on the discrete functional quantity.

[0011] In some technical solutions, the control method further includes: determining the control mode of the target chassis according to the mode management and safety takeover mechanism, wherein the control mode includes automatic control mode, virtual manual mode or emergency braking mode; and when the control mode is automatic control mode, executing the steps of receiving the output data of the upper-level test control module and thereafter.

[0012] In some technical solutions, after the virtual control input is sent to the original chassis drive software, the following is also included: If the current frame state of the virtual control input is inconsistent with the previous frame state, return to execute the real-time pose feedback information based on the task input and the target chassis to correct the expected physical quantity.

[0013] Secondly, this application provides a target chassis control system, including a virtual control input device that can be recognized by the original drive software of the target chassis. The virtual control input device serves as a unified control entry point between the upper-level test module and the chassis execution layer. The virtual control input device includes: The signal access module is used to receive the output data of the upper-level test control module as the task input of the target chassis. The output data includes at least one of the reference trajectory, target speed, target position or interaction strategy command. The expected physical quantity generation module is used to generate expected physical quantities based on the task input and the real-time pose feedback information of the target chassis; the expected physical quantities include the expected longitudinal acceleration and the expected equivalent front wheel rotation angle. The virtual control input generation module is used to convert the desired physical quantity into a virtual control input that can be recognized by the original chassis drive software based on a pre-established mapping relationship between control quantity and vehicle physical quantity. The input module is used to send the virtual control input to the original chassis drive software, and drive the target chassis to perform corresponding movements without modifying the original chassis drive software and control protocol.

[0014] Thirdly, this application provides an electronic device, comprising: At least one processor, and a memory communicatively connected to at least one of the processors; The memory stores instructions that can be executed by at least one of the processors, which are executed by at least one of the processors to enable at least one of the processors to perform the method described above.

[0015] Fourthly, this application provides a computer-readable storage medium storing computer instructions for causing a computer to perform the above-described method.

[0016] Compared with the prior art, the beneficial effects of this application are as follows: The target chassis control method provided in this application is applicable to virtual control input devices that can be recognized by the original driver software of the target chassis. The virtual control input device serves as a unified control entry point between the upper-level test module and the chassis execution layer. Without modifying the original driver software and control protocol of the target chassis, the virtual control input device reduces the access and modification costs of different test target platforms and provides a compatibility basis for the unified implementation of the method system.

[0017] This application constructs an integrated closed-loop virtual control method consisting of "task input - state feedback - control generation - mapping transformation - virtual execution - mode safety management", enabling the target chassis to automatically perform trajectory tracking and dynamic interactive test tasks. Its innovation lies in the fact that each link works collaboratively under a unified control cycle, a unified state benchmark, and a unified physical semantics to form a system solution for autonomous driving test scenarios.

[0018] This application establishes a correspondence between the controller output and the chassis physical response, and incorporates longitudinal and lateral collaborative control, virtual execution, and safe takeover into the same methodological framework. While ensuring the compatibility of the original system, it improves the repeatability of the testing process, the accuracy of trajectory execution, and the cross-platform reusability, making it suitable for adversarial, game-theoretic, and regression verification scenarios in autonomous driving testing. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the target chassis control method provided in this application.

[0021] Figure 2 This is the mapping curve between longitudinal control quantity and longitudinal acceleration in Embodiment 1 of this application.

[0022] Figure 3 This is the mapping curve between the lateral control quantity and the equivalent front wheel steering angle in Embodiment 1 of this application.

[0023] Figure 4 This is a schematic diagram of the longitudinal displacement comparison in Embodiment 2 of this application.

[0024] Figure 5 This is a schematic diagram of the longitudinal velocity comparison in Embodiment 2 of this application.

[0025] Figure 6This is a schematic diagram of the comparison of lateral displacement in Embodiment 2 of this application.

[0026] Figure 7 This is a schematic diagram of the heading angle curve in Embodiment 2 of this application.

[0027] Figure 8 This is a schematic diagram of the structure of the virtual control input device provided in this application.

[0028] Figure 9 This is a schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0029] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0030] Example 1 Figure 1 This is a flowchart of a target chassis control method provided in this embodiment. The method can be executed by the target chassis control system. The device can be composed of software and / or hardware and is generally integrated into an electronic device, such as a computer. For ease of understanding, each step in the control method of this embodiment is executed by an electronic computer.

[0031] like Figure 1 As shown, this embodiment provides a target chassis control method, applicable to virtual control input devices that can be recognized by the original drive software of the target chassis. The virtual control input device serves as a unified control entry point between the upper-level test module and the chassis execution layer. The method includes the following steps: S110. Receive the output data from the upper-level test control module as the task input for the target chassis. The output data includes at least one of the following: reference trajectory, target speed, target position, or interaction strategy command.

[0032] The upper-level test control module refers to the module that outputs the reference trajectory of the target chassis according to the actual test requirements.

[0033] The reference trajectory is the target trajectory that enables the chassis of the target object to move.

[0034] The target speed is the planned driving speed that the chassis of the target object will reach.

[0035] The target location is the planned location where the chassis of the target object will reach.

[0036] Interactive strategy commands refer to action commands that the upper layer actively outputs based on the dynamics of the vehicle under test, using the reference trajectory module that has interactive behavior.

[0037] Optionally, the receiving of output data from the upper-level test control module serves as the task input for the target chassis. The output data includes at least one of the following: reference trajectory, target speed, target position, or interaction strategy instructions. The system receives output data from the upper-level test control module, unpacks, extracts, and cleans the output data, and then uses it as the task input for the target chassis.

[0038] Specifically, the upper-layer test control module encapsulates the output data into data packets of a predefined format; the virtual control input device unpacks the data packets, extracts fields, and cleans the data to ensure stable transmission of control input within the control cycle. This step transforms the upper-layer task semantics into a transmittable, verifiable, and schedulable control data format, enabling task input to stably enter the closed-loop control link and maintain consistent interface specifications with subsequent mapping transformations and virtual execution processes.

[0039]

[0040]

[0041] Where S represents the mapped data string, f represents a floating-point number, d represents an integer number, u1~u3 represent the action input mapped to the joystick, b1~b14 represent the action input mapped to the button, and y[k] represents the S data string after ASCII encoding at step k.

[0042] The number of fields, encoding method, length, and transmission medium of the data message can be configured according to the access requirements of the original chassis driving software, so that the method system of this application can be reused in different target platforms and different chassis software environments, without relying on a single communication implementation method.

[0043] Virtual control input devices preferably perform channel number verification, numerical range verification, and duplicate frame filtering; subsequent control mapping and output updates are only triggered when there is a difference between the current frame and the previous frame, so as to reduce the impact of redundant transmission on the system's real-time performance.

[0044] S120. Based on the task input and the real-time pose feedback information of the target chassis, generate the desired physical quantity; the desired physical quantity includes the desired longitudinal acceleration and the desired equivalent front wheel rotation angle.

[0045] The real-time pose feedback information of the target chassis is the real-time pose information of the target chassis, which can be output by the pose measurement system through the network.

[0046] The desired longitudinal acceleration is the acceleration along the longitudinal axis that the target object is expected to achieve.

[0047] The expected equivalent front wheel steering angle refers to the angle between the longitudinal axis of the front wheel projection on the ground and the longitudinal axis of the vehicle body.

[0048] Optionally, generating the desired physical quantity based on the task input and the real-time pose feedback information of the target chassis includes: Based on the real-time pose feedback information of the target chassis, data validity verification, pose data parsing, velocity conversion and coordinate conversion are performed to obtain the real-time pose information of the usable state. Based on the task input and the real-time pose information of the available state, the desired physical quantity is generated.

[0049] Optionally, the virtual control input device performs integrity and validity checks on each frame of data, and maintains continuous output using the valid value of the previous frame when the check fails. Based on this, pose data analysis is performed to obtain raw state variables such as acceleration, angular velocity, attitude angle, ground speed, and latitude and longitude, providing feedback input for subsequent closed-loop control. The purpose of this step is to convert the raw state variables sensed at the lower level into a unified state expression that can directly participate in control calculations, enabling longitudinal control, lateral control, mode judgment, and safety takeover to share the same state reference. Part of the pose conversion principle is shown below: Acceleration:

[0050] Angular velocity:

[0051] Heading angle:

[0052] Pitch angle:

[0053] Roll angle:

[0054] Northbound speed:

[0055] in, Raw data representing acceleration. Raw data representing angular velocity. The raw data representing the heading angle. The raw data representing the pitch angle. The raw data representing the roll angle. The raw data represents the northward velocity, and e represents the first eccentricity of the WGS84 ellipsoid model.

[0056] Regarding coordinate conversion: the latitude, longitude, and altitude at the moment of the first valid frame or the reset signal trigger are used as the reference origin. , , And lock the initial heading angle (That is, the initial heading angle latched at the moment of the first valid frame or reset signal trigger). The latitude and longitude are represented using the WGS84 (World Geodetic System 1984, a geocentric coordinate system) ellipsoidal model. With height The conversion to Earth-Centered, Earth-Fixed coordinates (ECEF) is calculated as follows:

[0057]

[0058]

[0059]

[0060] in, λ represents the latitude of the target chassis's current position; λ represents the longitude of the target chassis's current position; h represents the altitude of the target chassis's current position. λ0 represents the latitude of the reference origin latched at the moment of the first valid frame or reset signal trigger; h0 represents the altitude of the reference origin latched at the moment of the first valid frame or reset signal trigger; a represents the semi-major axis of the WGS84 ellipsoid model; e represents the first eccentricity of the WGS84 ellipsoid model. Represents latitude The radius of curvature of the ramusoidal circle at the point; X represents the X-axis coordinate component in the ECEF coordinate system after transformation; Y represents the Y-axis coordinate component in the ECEF coordinate system after transformation; Z represents the Z-axis coordinate component in the ECEF coordinate system after transformation. The semi-major axis is used. Taking the position at the initial run or reset moment as the reference origin, the difference vector is calculated and projected onto the local tangent plane ENU (local Cartesian coordinates coordinate system). Then, a two-dimensional rotation matrix is ​​constructed using the initial heading angle to obtain the relative position in the GST (Greenwich Sidereal Time) fixed coordinate system. This coordinate unification process ensures that the reference trajectory in the task input and the real-time feedback are on the same spatial reference, establishing a unified error calculation basis for subsequent longitudinal and lateral coordinated control.

[0061]

[0062] in, Represents the longitudinal position of the target chassis in the GST fixed coordinate system; R(ψ0) represents the lateral position of the target chassis in the GST fixed coordinate system; R(ψ0) represents the two-dimensional rotation matrix constructed from the initial heading angle ψ0. [E,N] represents the initial heading angle latched at the moment of the first valid frame or reset signal trigger; E represents the eastward displacement component of the target chassis relative to the reference origin in the ENU coordinate system; N represents the northward displacement component of the target chassis relative to the reference origin in the ENU coordinate system; This represents the local tangent plane position vector composed of the eastward displacement component and the northward displacement component; This represents the relative position vector in the GST fixed coordinate system obtained after rotation by the initial heading angle.

[0063] Regarding speed conversion, the following method can be used: transform the ground speed from NED coordinates (North-East-Down) to vehicle system coordinates. Let the NED velocity vector be... Vehicle system velocity vector Construct the direction cosine matrix according to the ZYX Euler angle order (based on the heading angle). Pitch angle Roll angle ):

[0064]

[0065]

[0066]

[0067]

[0068] in, Represents the velocity vector in the NED coordinate system; These represent the eastward and groundward velocity components of the target chassis in the NED coordinate system, respectively, both in m / s; The velocity vector represents the vehicle's system coordinates. Represents the current heading angle of the target chassis. Constructed rotation matrix around the Z-axis; This represents the rotation matrix about the Y-axis constructed from the pitch angle θ; Represents the roll angle Constructed rotation matrix around the X-axis; This represents the direction cosine matrix from the vehicle system coordinate system to the NED coordinate system. From this, the vehicle system's longitudinal, lateral, and vertical velocities are obtained, and together with vehicle speed and other states, serve as the state feedback inputs for subsequent longitudinal and lateral closed-loop controllers. By uniformly converting position, attitude, and velocity into controllable states, the coupling chaos caused by each control module processing raw measurement data separately is avoided, further demonstrating the unified design of the methodology at the state level.

[0069] S130. Based on the pre-established mapping relationship between control quantity and vehicle physical quantity, the desired physical quantity is converted into a virtual control input that can be recognized by the original chassis drive software.

[0070] Optionally, the mapping relationship between the control quantity and the vehicle physical quantity is constructed in the following manner: Based on the chassis calibration test data of the target object, the mapping relationship between control quantity and vehicle physical quantity is determined. The mapping relationship between control quantity and vehicle physical quantity includes: the mapping relationship between longitudinal control quantity and longitudinal acceleration, and the mapping relationship between lateral control quantity and equivalent front wheel steering angle.

[0071] Calibration tests were conducted on the chassis to obtain the correspondence between longitudinal control variables and longitudinal acceleration, and between lateral control variables and equivalent front wheel steering angles, respectively, and a discrete mapping table was generated. The relevant mapping curves are shown below. Figure 2 and Figure 3 As shown. During runtime, the expected physical quantities are converted into control quantities recognizable by the chassis through table lookup or interpolation, thereby giving the upper-level control commands executable physical meaning. This mapping step is not an isolated calibration step, but rather connects the "standardized physical target output by the controller" with the "control entry point of the original chassis drive software," enabling longitudinal and lateral control to access different chassis platforms through a unified physical semantics. This is a crucial fulcrum for the transferability and reusability of the method system in this application. Through this method, different test target chassis can be adapted, achieving low-cost and rapid system migration and adaptation.

[0072]

[0073] And apply saturation constraints to the output. .

[0074] in, This represents the desired longitudinal control value obtained by interpolating the desired longitudinal acceleration. Represents the expected longitudinal acceleration; This represents the i-th longitudinal acceleration calibration value in the calibration mapping table; This represents the (i+1)th longitudinal acceleration calibration value in the calibration mapping table; Representative and The corresponding longitudinal control calibration value; Representative and The corresponding longitudinal control calibration value; i represents the data sequence number in the calibration mapping table.

[0075] The mapping relationship between lateral control variables and equivalent front wheel steering angles is obtained as follows: the chassis steering channel is calibrated, the wheel steering angle response under different lateral control variables is measured, the equivalent front wheel steering angle is calculated based on the chassis steering geometry, and a mapping relationship between the lateral physical response and the chassis control variables is established. During runtime, the conversion can also be completed using table lookup, interpolation, and amplitude limiting methods. By uniformly expressing the lateral control output at the equivalent front wheel steering angle level, this application decouples lateral control generation from the chassis execution layer, enabling the path tracking algorithm to adapt to different target chassis while maintaining consistent control objectives.

[0076]

[0077] And apply saturation constraints to the output. .

[0078] in, This represents the desired lateral control amount obtained by interpolating the expected equivalent front wheel steering angle. This represents the expected equivalent front wheel steering angle; This represents the j-th equivalent front wheel steering angle calibration value in the calibration mapping table; This represents the (j+1)th equivalent front wheel steering angle calibration value in the calibration mapping table; Representative and The corresponding lateral control calibration value; Representative and The corresponding lateral control calibration value; j represents the data sequence number in the lateral calibration mapping table.

[0079] Longitudinal control generation: Based on the reference longitudinal position, target velocity, and real-time longitudinal state of the target chassis, a longitudinal error is constructed and the desired longitudinal acceleration is output. Longitudinal control can be implemented using a combination of position feedforward and velocity feedback to balance trajectory tracking accuracy, response speed, and control stability. The focus of this step is not on the single control law itself, but on unifying the reference task, real-time state, and executable physical quantities of the chassis into the same longitudinal control link, so that the longitudinal control results can directly enter the mapping transformation and virtual execution stages.

[0080]

[0081] Calculate speed error:

[0082] Discrete integral of velocity error:

[0083] The desired longitudinal acceleration is obtained by superimposing the feedforward and PI:

[0084] Capacity limiting of acceleration:

[0085] in, This represents the longitudinal position error; Represents the reference vertical position; This represents the actual longitudinal position of the target chassis in a fixed coordinate system. Represents speed error; Represents reference speed or target speed; This represents the actual longitudinal velocity of the target object's chassis; This represents the integral value of the speed error in the kth control cycle. This represents the integral value of the speed error in the (k-1)th control cycle; This represents the speed error in the kth control cycle; This represents the time interval between two adjacent control cycles; This represents the desired longitudinal acceleration obtained from the longitudinal position error, velocity error, and the integral of the velocity error. Represents the longitudinal position error feedback coefficient; Represents the proportional feedback coefficient of speed error; Represents the integral feedback coefficient of speed error; This represents the output longitudinal acceleration after capacity limiting; Represents the saturation limiting function; This represents the minimum longitudinal acceleration that the target chassis is allowed to output. This represents the maximum longitudinal acceleration that the target chassis is allowed to output.

[0086] The desired longitudinal acceleration is mapped to a longitudinal control quantity via lookup table or interpolation and then output to the drive / braking channel of the virtual control input to achieve closed-loop tracking of the target velocity and target displacement. Therefore, longitudinal control generation does not end independently, but rather, together with mapping transformation, virtual execution, and state feedback, forms a longitudinal closed-loop sub-link, serving the overall trajectory tracking task.

[0087] Lateral control generation: Based on the reference trajectory and the target's current position and heading angle from the real-time pose feedback information of the target chassis, the target to be aimed at and the lateral error are determined, and the desired equivalent front wheel steering angle is output. Lateral control can be achieved by combining aiming curvature with error compensation to improve path tracking accuracy and suppress lateral jitter. This step unifies the path geometry, vehicle attitude feedback, and chassis execution requirements at the desired steering angle level, enabling the lateral control results to be subject to unified constraints, mapping, and execution within the same methodology as the longitudinal control results.

[0088] Transform the path points to local vehicle coordinates:

[0089] in, This represents the longitudinal relative position of the reference trajectory point in the local coordinate system of the target vehicle's chassis; This represents the lateral relative position of the reference trajectory point in the local coordinate system of the target object's chassis; The current heading angle of the target chassis; This represents the vertical position of the k-th trajectory point in the reference trajectory in a fixed coordinate system; This represents the horizontal position of the k-th trajectory point in the reference trajectory in a fixed coordinate system; This represents the actual longitudinal position of the target chassis in a fixed coordinate system. This represents the current lateral position of the target chassis in a fixed coordinate system. The relative position vector of the reference trajectory point with respect to the current position of the target chassis; by The constructed two-dimensional rotation matrix represents the coordinate transformation matrix that converts the relative position vector in the fixed coordinate system to the local coordinate system of the target chassis body.

[0090] by Determining the projection point index by changing from negative to positive And search forward to satisfy Pre-aiming line segment .

[0091] Linear interpolation for aiming error:

[0092] The curvature is obtained from the pure pre-aiming curvature law:

[0093] And obtain the pre-aiming angle:

[0094] To suppress jitter, a lateral PI is added, and the integral is updated:

[0095] Corresponding compensation:

[0096] Final expected equivalent front wheel steering angle:

[0097] in, This represents the lateral error of the aiming point in the local coordinate system of the target's chassis; This represents the lateral position of the starting point of the pre-aiming line segment in the local coordinate system of the target's chassis; This represents the longitudinal position of the starting point of the pre-aiming line segment in the local coordinate system of the target's chassis; This represents the lateral position of the endpoint of the pre-aimed line segment in the local coordinate system of the target's chassis; This represents the longitudinal position of the endpoint of the pre-aimed line segment in the local coordinate system of the target's chassis; This represents the index of the trajectory point used to determine the pre-aimed line segment; Represents the pre-aiming distance; This represents the pre-aiming curvature calculated based on the pre-aiming lateral error; This represents the aiming angle obtained based on the aiming curvature; The equivalent wheelbase of the target chassis; This represents the integral value of the lateral error in the k-th control cycle; This represents the integral value of the lateral error during the (k-1)th control cycle; This represents the lateral error in the k-th control cycle; This represents the time interval between two adjacent control cycles; This represents the lateral PI compensation angle used to suppress lateral jitter; Represents the horizontal error proportional feedback coefficient; Represents the integral feedback coefficient of the lateral error; Represents the integral term of the lateral error; This represents the expected equivalent front wheel angle of the final output.

[0098] The final expected equivalent front wheel steering angle is mapped to a lateral control variable through table lookup or interpolation, and then output to the steering channel of the virtual control input to achieve lateral closed-loop control. Thus, the lateral control generation also forms a closed-loop sub-link of "task input—error calculation—physical quantity output—mapping conversion—chassis execution—state feedback," which, together with the longitudinal sub-link, constitutes the overall coordinated control structure.

[0099] Optionally, the step of converting the desired physical quantity into a virtual control input recognizable by the original chassis drive software based on a pre-established mapping relationship between control quantity and vehicle physical quantity includes: Based on the pre-established mapping relationship between control quantity and vehicle physical quantity, the desired physical quantity is converted into virtual control input data, which is divided into continuous control quantity and discrete function quantity according to data type. The continuous control quantity is normalized and limited; Press or release control is performed on the discrete functional quantity.

[0100] As mentioned earlier, virtual control input data consists of longitudinal control quantities and lateral control quantities. Based on data type, it can also be divided into two categories: continuous control quantities and discrete functional quantities. Continuous control quantities refer to control quantities that can change continuously within a certain numerical range, such as speed and steering angle. Discrete functional quantities refer to control quantities associated with vehicle function buttons, such as start, emergency stop, and mode switching.

[0101] The unpacked continuous control quantities and discrete function quantities are mapped to the corresponding channels of the virtual control input device. The continuous control quantities are normalized and limited, while the discrete function quantities are controlled by pressing / releasing. A complete virtual control state is submitted in each control cycle. This step interfaces the control generation results with the existing input logic of the original chassis drive software, allowing the upper-level algorithm output to be executed by the original system without modifying the chassis software. This is the key execution step for the non-intrusive implementation of the entire methodology.

[0102]

[0103] in, This represents the normalized virtual control input. This represents the original control quantity obtained from the mapping, including longitudinal control quantity or lateral control quantity; This means converting the original control quantity into a normalized value that can be recognized by the virtual control input device by converting it into a percentage range. This represents the saturation limiting function.

[0104] Lateral control quantities, drive / brake control quantities, and function buttons are mapped to channels according to the existing control habits of the original chassis drive software to ensure system compatibility and reduce adaptation and modification costs.

[0105] S140. The virtual control input is sent to the original chassis drive software so that the original chassis drive software drives the target chassis to perform corresponding movements.

[0106] Optionally, the control method further includes: determining the control mode of the target chassis according to the mode management and safety takeover mechanism, wherein the control mode includes an automatic control mode, a virtual manual mode, or an emergency braking mode; and, when the control mode is an automatic control mode, performing the steps of receiving the output data of the upper-level test control module and thereafter.

[0107] Pattern management is not an independent additional function, but rather a constraint and takeover layer in the methodology system. It provides unified governance for the task execution chain, ensuring that the system can switch controllably between automatic execution, manual takeover, and abnormal security handling.

[0108]

[0109] in, This represents the longitudinal control quantity that is ultimately output to the virtual control input device for drive or braking control. This represents the lateral control quantity that is ultimately output to the virtual control input device for steering control. and These represent the longitudinal and lateral control values ​​obtained manually in virtual manual mode, respectively. This represents the desired longitudinal control value obtained by interpolating the desired longitudinal acceleration. This represents the desired lateral control amount obtained by interpolating the expected equivalent front wheel steering angle. This represents the braking control quantity in emergency braking mode; the virtual manual mode is used for debugging and manual takeover, the automatic control mode is used to execute closed-loop trajectory tracking tasks, and the emergency braking mode is used to forcibly output safety control quantities when an emergency stop is triggered, communication is abnormal, or pose data is continuously invalid. To ensure smooth mode switching, it is preferable to limit and smooth the output when switching from manual to automatic; after the emergency state is lifted, the system exits emergency braking mode and returns to manual mode when the reset signal is valid. By embedding the mode switching logic into the closed-loop control link, this application further realizes the systematic linkage between control generation, execution path, and safety strategy.

[0110] Optionally, after sending the virtual control input to the original chassis drive software, the method further includes: If the current frame state of the virtual control input is inconsistent with the previous frame state, return to execute the real-time pose feedback information based on the task input and the target chassis to correct the desired physical quantity.

[0111] The virtual control system uses virtual control input devices, functionally equivalent to physical controllers, as signal inputs for the chassis drive software. During the control cycle, the system writes longitudinal and lateral control quantities into the drive / brake and steering channels respectively, and writes the button states related to the function modes into the corresponding button channels, driving the chassis to execute corresponding actions according to the original logic. This step ensures that the results of the aforementioned task input, state feedback, control generation, mapping conversion, and mode management ultimately converge at the same execution output, completing a closed-loop system from the task layer to the chassis execution layer.

[0112]

[0113] in, This represents the normalized virtual steering input. Represents the normalized virtual longitudinal input; This represents the desired lateral control amount obtained by mapping the expected equivalent front wheel steering angle. This represents the desired longitudinal control quantity obtained by mapping the desired longitudinal acceleration. This means that the desired lateral control quantity is converted into a normalized steering input that can be recognized by the virtual control input device by a percentage range; This means converting the desired longitudinal control quantity into a normalized longitudinal input that can be recognized by the virtual control input device, based on a percentage range. This represents the saturation limiting function.

[0114] To reduce redundant output and improve control stability, a consistency check is preferably performed on the virtual control input, updating the output only when the current frame state differs from the previous frame state. After completing the virtual control input, the complete virtual control state for the current cycle is submitted. Based on this, the chassis drive software drives the target chassis to perform corresponding steering and driving / braking actions, thereby achieving automatic control of the test target and dynamic confrontation, game interaction, and other testing functions without changing the original chassis software and protocols. Therefore, what this application innovates is not a single virtual control device, but a complete closed-loop virtual control method system built around this execution output.

[0115] This application achieves non-intrusive automatic control of the target chassis using a closed-loop architecture of "task input - status feedback - control generation - mapping transformation - virtual execution - mode safety management". The steps are not set in isolation, but rather revolve around the requirements of "accessible, executable, closed-loop and safe takeover" of the target chassis in autonomous driving testing. Under a unified control cycle, the dynamic behavior generation and control of the test target are realized, forming a systematic and innovative methodology.

[0116] Example 2 This embodiment takes the GST target chassis of an autonomous driving test site as the object. Without modifying its chassis drive software (such as Driveless Base Station, DBS) and existing control protocol, a closed-loop virtual control link of "task input - status feedback - control generation - mapping conversion - virtual execution - safety management" is constructed to realize the automatic execution of the target chassis on the reference trajectory and dynamic interactive tasks.

[0117] Step A: Deployment of virtual control input and signal access.

[0118] Deploy a Python control signal access program on the control computer (Windows), use vgamepad to create a virtual Xbox 360 controller device, and establish a UDP receive port 127.0.0.1:12345 on the local machine to receive control data packets from Matlab / Simulink. Upon receiving the data packets, execute the following commands sequentially: (1) Convert bytes to strings and remove illegal characters; (2) Parse the data into 17 channels (3 axes + 14 buttons) separated by commas. (3) Verify the number of channels and the range of values ​​(axis range ±100, key is 0 / 1). If the verification fails, discard the frame. (4) If all 17 channels are consistent with the previous frame state, it is determined to be a duplicate frame and filtered to reduce system overhead. (5) Normalize the axis values ​​to the range of [-1,1] of the virtual controller API and write them to the corresponding joystick / trigger channel. Write the 14 button states to the virtual buttons. ; (6) Call update() to submit the complete handle status for this cycle.

[0119] The appearance of "Xbox 360 peripherals" in Windows Device Manager and the ability to access the joystick calibration interface in DBS software (without the "Remote controls are not attached" error) confirm that the virtual controller has been successfully created and input has been connected.

[0120] Step B: Building a Simulink-based virtual control and data transmission model.

[0121] An integrated upper-level control and data transmission model for autonomous driving testing tasks was built on Matlab / Simulink, including modules for mode selection, manual takeover, automatic control, data encapsulation, and UDP transmission.

[0122] (1) In manual mode, three-axis control quantities are generated by slider / switch. and button positions And set the Index Vector to switch modes (e.g., 0: initial / zero output; 1: slider control; 2 / 3: single-axis / dual-axis debugging; 4: braking test).

[0123] (2) The data encapsulation module uses sprintf to generate a CSV string in the format of "3 floating-point numbers + 14 integers" and converts it into a fixed-length 90-byte uint8 data packet; (3) The UDP Send module sends data packets to 127.0.0.1:12345 to achieve local loopback communication with the Python access program.

[0124] By observing the changes in axle displacement and the effects of button triggering in the DBS, the correspondence between each virtual control input channel and the chassis software function can be determined, such as the steering channel, throttle / brake channel, and function buttons for clutch, reverse switching, etc.

[0125] Step C: RT pose output reception, parsing, and coordinate / velocity conversion.

[0126] The pose measurement system (RT) is configured to output NCOM data packets via UDP. The Simulink end uses UDP Receive to receive 72-byte uint8 data packets from the RT (remote address 195.0.0.14:3000) on the designated network port 195.0.0.204:3000. Integrity checks are performed on each data frame: the packet length is 72 bytes and the header identifier is 231. Checksum1 and Checksum2 are verified, and the navigation status bit is 4 (high-precision solution is valid). If the verification fails, the frame is discarded, and the valid value of the previous frame is used to maintain output continuity. 24-bit signed integers are parse_s24 to perform sign extension to restore them to 32-bit integers, and physical quantities such as acceleration, angular velocity, latitude and longitude, NED velocity, and attitude angles are restored according to the protocol scaling factor.

[0127] In the position conversion, the initial latitude and longitude and the initial heading angle are latched as the reference origin. The WGS84→ECEF→ENU transformation is used, and the position in the fixed coordinate system is obtained by rotating the initial heading angle. With heading angle In the speed conversion, the ZYX direction cosine matrix is ​​used to convert the NED speed into the vehicle system speed. It serves as the feedback input for closed-loop control.

[0128] Step D: Control quantity-vehicle physical quantity mapping calibration and table lookup establishment.

[0129] To achieve the conversion from the "desired physical quantity output by the controller" to the "control quantity recognizable by the chassis," calibration mappings are established for both longitudinal and lateral directions, enabling the upper-level control results to be executed by the chassis without modifying the original chassis software. (1) Longitudinal calibration: Send fixed longitudinal control quantities at 5% intervals, record steady-state longitudinal acceleration, and form a mapping table of "longitudinal acceleration-longitudinal control quantity"; (2) Lateral calibration: Under the condition of chassis suspension, send fixed lateral control quantity (also known as steering control quantity) at 10% intervals, measure the inner and outer wheel rotation angles and calculate the equivalent front wheel rotation angle to form a mapping table of "equivalent front wheel rotation angle - lateral control quantity"; (3) Piecewise linear interpolation is used during operation to determine the desired longitudinal acceleration. Mapped to The expected equivalent front wheel steering angle Mapped to And perform necessary amplitude limiting.

[0130] Step E: Closed-loop control and trajectory tracking are implemented.

[0131] The target generation module outputs a reference trajectory and target speed based on the test conditions, and the trajectory tracking controller jointly generates longitudinal and lateral control commands within a unified control cycle.

[0132] (1) The longitudinal control adopts position feedforward + velocity PI feedback, and outputs the desired longitudinal acceleration:

[0133] (2) Lateral control uses preview error and curvature law: Calculate preview error y_error to obtain:

[0134]

[0135] And PI compensation is added:

[0136]

[0137] (3) The axis quantity and key quantity, which are mapped to virtual control inputs by table lookup / interpolation respectively, are encapsulated into UDP data packets and sent to the Python access program. The data is written to the virtual input device and updated() is used to submit, thus forming a closed-loop link of "task input - feedback - control - mapping - virtual execution - chassis response".

[0138] (4) The mode management adopts Index Vector: 0 is virtual manual mode, 1 is automatic control mode, and 2 is emergency braking mode; in emergency braking mode, the full braking control quantity is output and the steering is set to zero.

[0139] Step F: Verification and Evaluation.

[0140] Tracking tests were conducted under typical operating conditions such as straight lines, acceleration / deceleration, and single lane change. Position, speed, heading angle, and control variable curves were recorded to verify the stability and repeatability of the closed-loop control. In emergency braking mode, it was verified that the system could output full braking force at any time and bring the target object to a stop. The control accuracy and stability were evaluated using indicators such as lateral error, longitudinal velocity error, and control variable saturation ratio. The control parameters were then tuned based on the experimental results. Some experimental test results are shown below. Figures 4-7As shown.

[0141] Example 3 like Figure 8 As shown, this embodiment provides a target chassis control system, including a virtual control input device 2 that can be recognized by the original drive software of the target chassis. The virtual control input device serves as a unified control entry point between the upper-level test module and the chassis execution layer. The virtual control input device includes: The signal access module 201 is used to receive the output data of the upper test control module as the task input of the target chassis. The output data includes at least one of the reference trajectory, target speed, target position or interaction strategy command. The expected physical quantity generation module 202 is used to generate expected physical quantities based on the task input and the real-time pose feedback information of the target chassis; the expected physical quantities include the expected longitudinal acceleration and the expected equivalent front wheel rotation angle. The virtual control input generation module 203 is used to convert the desired physical quantity into a virtual control input that can be recognized by the original chassis drive software based on a pre-established mapping relationship between control quantity and vehicle physical quantity. The input module 204 is used to send the virtual control input to the original chassis drive software, and drive the target chassis to perform corresponding movements without modifying the original chassis drive software and control protocol.

[0142] The device is used to perform the above method, and therefore has at least the functional modules and beneficial effects corresponding to the above method.

[0143] Example 4 like Figure 9 As shown, this embodiment provides an electronic device, including: At least one processor; and A memory communicatively connected to at least one of the processors; wherein, The memory stores instructions executable by at least one of the processors to enable the processor to perform the described method. Since at least one processor in the electronic device is capable of performing the described method, it thus possesses at least the same advantages as the described method.

[0144] Optionally, the electronic device also includes interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The components are interconnected using different buses and can be mounted on a common motherboard or otherwise installed as needed. The processor can process instructions executed within the electronic device, including instructions stored in or on memory to display graphical information of a GUI (Graphical User Interface) on an external input / output device (such as a display device coupled to the interface). In other embodiments, multiple processors can be used with multiple memories, and / or multiple buses can be used with multiple memories, if desired. Similarly, multiple electronic devices (e.g., as a server array, a group of blade servers, or a multiprocessor system) can be connected, each providing some of the necessary operations. Figure 9 Take processor 301 as an example.

[0145] The memory 302, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the target chassis control method in the embodiments of this application (e.g., the signal access module, desired physical quantity generation module, virtual control input generation module, and input module in the target chassis control device). The processor 301 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 302, thereby realizing the aforementioned target chassis control method.

[0146] The memory 302 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on terminal usage. Furthermore, the memory 302 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 302 may further include memory remotely located relative to the processor 301, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0147] The electronic device may further include an input device 303 and an output device 304. The processor 301, memory 302, input device 303, and output device 304 can be connected via a bus or other means. Figure 9 Taking the example of a connection between China and Israel via a bus.

[0148] Input device 303 can receive input digital or character information, and output device 304 may include a display device, an auxiliary lighting device (e.g., an LED), and a haptic feedback device (e.g., a vibration motor). The display device may include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touchscreen.

[0149] Example 5 This embodiment provides a computer-readable storage medium storing computer instructions for causing a computer to perform the methods described above. The computer instructions on this computer-readable storage medium, used to cause a computer to perform the methods described above, thus have at least the same advantages as the methods described above.

[0150] The medium in this application may be any combination of one or more computer-readable media. The medium may be a computer-readable signal medium or a computer-readable storage medium. The medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the medium (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, the medium may be any tangible medium containing or storing a program that may be used by or in connection with an instruction execution system, apparatus, or device.

[0151] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0152] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF (Radio Frequency), or any suitable combination thereof.

[0153] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0154] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.

[0155] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for controlling the chassis of a target object, characterized in that, A virtual control input device applicable to objects whose original chassis drive software can be recognized, wherein the virtual control input device serves as a unified control entry point between the upper-level test module and the chassis execution layer; the method includes: The system receives output data from the upper-level test control module as task input for the target chassis. The output data includes at least one of the following: reference trajectory, target speed, target position, or interaction strategy command. Based on the task input and the real-time pose feedback information of the target chassis, expected physical quantities are generated; the expected physical quantities include the expected longitudinal acceleration and the expected equivalent front wheel rotation angle. Based on the pre-established control quantity-vehicle physical quantity mapping relationship, the desired physical quantity is converted into a virtual control input that can be recognized by the original chassis drive software; the control quantity-vehicle physical quantity mapping relationship is constructed in the following way: the control quantity-vehicle physical quantity mapping relationship is determined according to the chassis calibration test data of the target object, and the control quantity-vehicle physical quantity mapping relationship includes: the mapping relationship between longitudinal control quantity and longitudinal acceleration, and the mapping relationship between lateral control quantity and equivalent front wheel steering angle; The virtual control input is sent to the original chassis drive software so that the original chassis drive software drives the target chassis to perform corresponding movements.

2. The target chassis control method according to claim 1, characterized in that, The received upper-level test control module outputs data as the task input for the target chassis. The output data includes at least one of the following: reference trajectory, target speed, target position, or interaction strategy command. The system receives output data from the upper-level test control module, unpacks, extracts, and cleans the output data, and then uses it as the task input for the target chassis.

3. The target chassis control method according to claim 1, characterized in that, The step of generating the desired physical quantity based on the task input and the real-time pose feedback information of the target chassis includes: Based on the real-time pose feedback information of the target chassis, data validity verification, pose data parsing, velocity conversion and coordinate conversion are performed to obtain the real-time pose information of the usable state. Based on the task input and the real-time pose information of the available state, the desired physical quantity is generated.

4. The target chassis control method according to claim 1, characterized in that, The process of converting the desired physical quantity into a virtual control input recognizable by the original chassis drive software, based on a pre-established mapping relationship between control quantity and vehicle physical quantity, includes: Based on the pre-established mapping relationship between control quantity and vehicle physical quantity, the desired physical quantity is converted into virtual control input data, which is divided into continuous control quantity and discrete function quantity according to data type. The continuous control quantity is normalized and limited; Press or release control is performed on the discrete functional quantity.

5. The target chassis control method according to claim 1, characterized in that, The control method further includes: determining the control mode of the target chassis according to the mode management and safety takeover mechanism, wherein the control mode includes automatic control mode, virtual manual mode or emergency braking mode; and, when the control mode is automatic control mode, executing the steps of receiving the output data of the upper-level test control module and thereafter.

6. The target chassis control method according to claim 1, characterized in that, After sending the virtual control input to the original chassis drive software, the following is also included: If the current frame state of the virtual control input is inconsistent with the previous frame state, return to execute the real-time pose feedback information based on the task input and the target chassis to correct the desired physical quantity.

7. A target chassis control system, characterized in that, This includes a virtual control input device that can be recognized by the original drive software of the target chassis. The virtual control input device serves as a unified control entry point between the upper-level test module and the chassis execution layer. The virtual control input device includes: The signal access module is used to receive the output data of the upper-level test control module as the task input of the target chassis. The output data includes at least one of the reference trajectory, target speed, target position or interaction strategy command. The expected physical quantity generation module is used to generate expected physical quantities based on the task input and the real-time pose feedback information of the target chassis; the expected physical quantities include the expected longitudinal acceleration and the expected equivalent front wheel rotation angle. The virtual control input generation module is used to convert the desired physical quantity into a virtual control input that can be recognized by the original chassis drive software based on a pre-established control quantity-vehicle physical quantity mapping relationship. The control quantity-vehicle physical quantity mapping relationship is constructed in the following way: the control quantity-vehicle physical quantity mapping relationship is determined according to the chassis calibration test data of the target object. The control quantity-vehicle physical quantity mapping relationship includes: the mapping relationship between longitudinal control quantity and longitudinal acceleration, and the mapping relationship between lateral control quantity and equivalent front wheel steering angle. The input module is used to send the virtual control input to the original chassis drive software, and drive the target chassis to perform corresponding movements without modifying the original chassis drive software and control protocol.

8. An electronic device, characterized in that, include: At least one processor, and a memory communicatively connected to at least one of the processors; The memory stores instructions executable by at least one of the processors, which are executed to enable the at least one of the processors to perform the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The medium stores computer instructions for causing the computer to perform the method of any one of claims 1-6.

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