Collision control method, device, recording medium and electronic device using man-machine collaborative operation

Abstract

The present invention belongs to the technical field of automatic driving, and particularly relates to a method, device, recording medium and electronic device for collision control by man-machine collaborative driving. The collision control method by man-machine collaborative driving includes the steps of: establishing a man-machine path tracking control game model corresponding to man-machine interaction behavior based on a driver's deterministic steering torque and a driver's random steering torque (S101); solving the man-machine path tracking control game model to obtain man-machine torque collision information (S102); and determining a shared control strategy based on the man-machine torque collision information, thereby controlling the vehicle based on the shared control strategy (S103). The collision control method by man-machine collaborative driving provided in the present invention can improve the accuracy of vehicle control by describing the mapping relationship between the difference in man-machine decision-making and the man-machine steering torque interaction.

Description

[Technical field]

[0001] The present invention claims priority to a Chinese patent application filed on April 14, 2022, bearing application number 202210414179.X and entitled "Method, device, recording medium and electronic device for collision control through man-machine collaborative operation," the entire contents of which are incorporated by reference into this application.

[0002] The present invention relates to the technical field of automatic driving, and in particular to a collision control method through man-machine cooperative operation, a collision control device through man-machine cooperative operation, a recording medium, and an electronic device. [Background technology]

[0003] Both the autonomous driving system and the driver are agents and make judgments and decisions based on their own understanding of the scene. Therefore, in addition to the man-machine steering conflict caused by the difference in the man-machine preview actions in the control layer of the collaborative driving system, another major cause of man-machine conflict is the difference in the man-machine decision-making layer, that is, the difference in the target trajectory planned by the driver and the autonomous driving system, which further causes steering torque conflict.

[0004] However, in modeling the man-machine interaction mechanism, it becomes difficult to directly measure the driver's decision-making goal, and especially in the process of modeling man-machine interaction for vehicle limit driving situations (e.g. man-machine collaborative emergency avoidance), it becomes difficult to directly describe the man-machine interaction behavior with a linear dynamic model.

[0005] Many nonlinear methods, such as nonlinear prediction method, local linearization method, piecewise affine method, etc., are all applied to deal with the problem of model mismatch under the vehicle's limit driving conditions, but the nonlinear prediction method often has poor real-time performance of the algorithm due to its high computational complexity. Although the local linearization or piecewise affine method can ensure the real-time performance of the algorithm, these methods inevitably cause the control strategy to alternate within different linearization intervals, which causes the man-machine interaction result to have a non-smooth phenomenon, and even the sliding mode phenomenon of alternating near the linear section point appears.

[0006] In addition, the information disclosed in the above background art is used only to enhance understanding of the background of the present invention, and may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] According to one aspect of an embodiment of the present invention, a collision control method for man-machine collaborative driving is provided, the method including: establishing a man-machine path tracking control game model corresponding to a man-machine interaction behavior based on a driver's deterministic steering torque and a driver's random steering torque; solving the man-machine path tracking control game model to obtain man-machine torque collision information; and determining a shared control strategy based on the man-machine torque collision information, thereby controlling a vehicle based on the shared control strategy.

[0008] According to a second aspect of the embodiment of the present invention, there is provided a collision control device for man-machine collaborative operation, the device including: a modeling module for establishing a man-machine path tracking control game model corresponding to a man-machine interaction behavior based on a driver's deterministic steering torque and a driver's random steering torque; a solution module for solving the man-machine path tracking control game model to obtain man-machine torque collision information; and an operation module for determining a shared control strategy based on the man-machine torque collision information, and thereby performing vehicle control based on the shared control strategy.

[0009] According to a third aspect of an embodiment of the present invention, there is provided a computer-readable recording medium having a computer program stored thereon, which, when executed by a processor, realizes the collision control method through man-machine collaborative operation in the above embodiment.

[0010] According to a fourth aspect of an embodiment of the present invention, there is provided an electronic device, the electronic device including one or more processors and a memory device for storing one or more programs, the one or more programs being executed by the one or more processors to cause the one or more processors to realize the collision control method through man-machine collaborative operation in the above embodiment.

[0011] It should be noted that the above general description and the following detailed description are merely exemplary and explanatory and are not intended to limit the present invention. [Brief description of the drawings]

[0012] The drawings herein are incorporated in the specification and constitute a part of this specification, illustrate embodiments suitable for the present invention, and are intended to explain the principles of the present invention together with the specification. Note that the drawings in the following description are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings from these drawings without giving creative labor. [Figure 1]FIG. 2 is a schematic diagram showing a flow of a collision control method by man-machine collaborative operation in an exemplary embodiment of the present invention. [Diagram 2] FIG. 2 is a schematic diagram illustrating the principle of steering interaction of the man-machine collaborative driving system in an exemplary embodiment of the present invention; [Diagram 3] FIG. 2 is a schematic diagram illustrating the principle of a non-cooperative game of a man-machine cooperative operation system in an exemplary embodiment of the present invention. [Figure 4] FIG. 2 is a schematic diagram illustrating the principle of the closed-loop dynamic game of the man-machine collaborative driving system in an exemplary embodiment of the present invention. [Diagram 5] FIG. 2 is a schematic diagram illustrating the principle of the open-loop dynamic game of the man-machine collaborative driving system in an exemplary embodiment of the present invention; [Figure 6] FIG. 2 is a schematic diagram illustrating the flow of a method for constructing a closed-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. [Figure 7] 1A and 1B are schematic diagrams illustrating the principle of a multi-point preview mode in an exemplary embodiment of the present invention; [Figure 8] FIG. 2 is a schematic diagram showing a flow of an open-loop man-machine path tracking control game model construction method in an exemplary embodiment of the present invention; [Figure 9] FIG. 2 is a schematic diagram illustrating a flow of a method for solving a closed-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. [Figure 10] FIG. 11 is a schematic diagram illustrating a flow of a method for solving another closed-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. [Figure 11] FIG. 11 is a schematic diagram showing a flow of a method for solving another open-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. [Figure 12] FIG. 11 is a schematic diagram showing a flow of a method for solving another open-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. [Figure 13]FIG. 2 is a schematic diagram showing a configuration of a collision control device based on man-machine cooperative operation in an exemplary embodiment of the present invention; [Figure 14] FIG. 1 is a schematic diagram showing a computer-readable recording medium according to an exemplary embodiment of the present invention. [Figure 15] FIG. 2 is a schematic diagram showing a structure of a computer system of an electronic device in an exemplary embodiment of the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, exemplary embodiments will be described in more detail with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in various forms and are not limited to the examples set forth herein. On the contrary, these embodiments are provided to fully complete the present invention and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0014] It should be noted that the described features, configurations, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to fully understand the embodiments of the present invention. However, it should be understood by those skilled in the art that the technical solutions of the present invention can be realized without one or more of the specific details, or other methods, components, devices, steps, etc. may be employed. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present invention.

[0015] The block diagrams shown in the drawings are merely functional entities which do not necessarily correspond to physically separate entities, i.e. these functional entities are implemented in software form or in one or more hardware modules or integrated circuits or in different network and / or processor and / or microcontroller devices.

[0016] The flowcharts shown in the drawings are merely illustrative and do not necessarily include all contents and operations / steps, nor do they necessarily have to be performed in the order described. For example, some operations / steps may be separated, while some operations / steps may be merged or partially merged, so that the order of actual execution may be changed according to actual circumstances.

[0017] In a man-machine dual agent system, the driver and the autonomous driving system can simultaneously operate actuators and change the vehicle state to achieve their respective goals. However, such input redundancy inevitably causes man-machine conflict interactions, which have serious impacts on the vehicle's safety, comfort, dynamics, fuel economy, etc.

[0018] Game theory is an effective means of describing and understanding both interaction conflicts in multi-agent systems, and provides effective theoretical methods for quantitative modeling of man-machine interactions, resolving man-machine conflicts, and estimating the driver's true intentions.

[0019] Regarding the problem of man-machine collaborative driving trajectory tracking control, both the automatic driving system and the driver are agents and make judgments and decisions based on their own understanding of the scene. Therefore, in addition to the man-machine steering collision caused by the difference in the man-machine preview behavior in the control layer of the collaborative driving system, another main cause of man-machine collision is the difference in the man-machine decision-making layer, that is, the difference in the target trajectory planned by the driver and the automatic driving system, which further causes steering torque collision.

[0020] On the other hand, in the modeling of man-machine interaction mechanism, especially in the modeling process of man-machine interaction for vehicle limit driving conditions (such as man-machine collaborative emergency avoidance), it is difficult to directly describe man-machine interaction behavior with a linear dynamic model. Many nonlinear methods, such as nonlinear prediction method, local linearization method, and piecewise affine method, are all applied to deal with the problem of model mismatch under vehicle limit driving conditions, and nonlinear prediction method often has poor real-time performance of algorithm due to its high computational complexity. Although local linearization or piecewise affine method can ensure the real-time performance of algorithm, these methods inevitably cause the control strategy to alternate within different linearization intervals, which causes non-smooth phenomenon in man-machine interaction result, and even the sliding mode phenomenon of alternating near linear section points appears. On the other hand, for multi-agent dynamic systems, the theory of dynamic non-cooperative games can also be adopted, but the current research on game theory in cooperative driving systems is mainly limited to the design of shared control strategies, and there is still no complete theoretical description of the mapping relationship between the differences in man-machine decision-making and collision control.

[0021] To solve this complicated problem, the present invention studies the man-machine interaction mechanism of collision control from the difference in decision-making. In the dynamic steering system with man-machine interaction, two kinds of disturbances simultaneously exist, namely, deterministic steering resistance torque and uncertain steering torque of the driver. Therefore, the present invention proposes a new random game theoretical framework, takes into account deterministic and random steering torque, and fully describes the mapping relationship by Nash equilibrium and Stackelberg equilibrium in different information modes, thereby designing a theoretical bridge connecting the difference in man-machine decision-making and collision control, overcoming the confusion problem of man-machine decision-making existing in the cooperative driving system, and further providing a theoretical basis for the design of a shared control strategy.

[0022] The implementation details of the technical solutions of the embodiments of the present invention are described in detail below.

[0023] 1 is a schematic diagram showing a flow of a method for collision control by man-machine cooperative operation in an exemplary embodiment of the present invention. As shown in FIG. 1, the method for collision control by man-machine cooperative operation includes steps S101 to S103.

[0024] In step S101, a man-machine path tracking control game model corresponding to man-machine interaction behavior is established according to the driver's deterministic steering torque and the driver's random steering torque.

[0025] In step S102, the man-machine path tracing control game model is solved to obtain man-machine torque collision information.

[0026] In step S103, a shared control strategy is determined based on the man-machine torque collision information, and then vehicle control is performed based on the shared control strategy.

[0027] In the technical solutions provided in some embodiments of the present invention, the present invention establishes a man-machine path tracking control game model corresponding to the man-machine interaction behavior based on the driver's deterministic steering torque and the driver's random steering torque, and obtains man-machine torque collision information for vehicle control by solving the man-machine path tracking control game model. The driver's uncertain behavior can be incorporated into the man-machine path tracking control, which can better meet the needs of the actual scene and make the control effect more accurate, while the man-machine torque collision information obtained by solving the game model can accurately describe the man-machine interaction behavior of collision control from the decision-making difference in the man-machine collaborative driving model, which can overcome the man-machine decision-making confusion problem existing in the collaborative driving system, and further provide a theoretical basis for the design of a shared control strategy to further optimize the vehicle control result.

[0028] Hereinafter, each step of the method for collision control through man-machine collaboration in this exemplary embodiment will be described in more detail with reference to the drawings and examples.

[0029] In step S101, a man-machine path tracking control game model corresponding to man-machine interaction behavior is established according to the driver's deterministic steering torque and the driver's random steering torque.

[0030] In one embodiment of the present invention, firstly, a man-machine path-tracking control game model is established to solve man-machine interaction behavior, and the man-machine path-tracking control game model can use the theoretical framework of non-cooperative games.

[0031] FIG. 2 is a schematic diagram showing the principle of steering interaction of a man-machine collaborative driving system in an exemplary embodiment of the present invention. As shown in FIG. 2, both the driver and the automatic driving system (hereinafter simply referred to as the driving system) generate corresponding steering operation actions based on their own target trajectories, and at the same time, both can sense the decision-making of both through the steering system and the motion state of the entire vehicle. Therefore, for the driver, in order to achieve his own decision-making goal, his steering operation action also includes the reaction to the steering action of the driving system, and therefore, when designing the controller of the driving system, the driver's steering control input should also be fully considered. Therefore, in the modeling of man-machine steering collision in the man-machine collaborative driving system, the interaction of man-machine steering actions must be taken into account, and especially under the condition that the man-machine decision-making goals are different, the driver's steering action is not only based on his own decision-making goal, but also actively compensates for the steering action of the automatic driving system, which is very different from pure manual driving.

[0032] In the collaborative driving process, the steering actions of both the driver and the automatic driving system aim to minimize the tracking error of each trajectory, and each steering action is generated based on the state feedback of the lane system and the steering action of the other party. Therefore, it is inevitable that the target trajectories of each decision-making layer of the man-machine will differ. Under such conditions, the man-machine interaction process can be described using the theoretical framework of a non-cooperative game.

[0033] 3 is a schematic diagram showing the principle of the non-cooperative game of the man-machine cooperative driving system in an exemplary embodiment of the present invention. As shown in FIG. 3, the driver and the driving system are regarded as game participants, and both of them aim to maximize their profits by integrating the state information of the game process and the actions of the other party to generate their own actions.

[0034] When studying the problem of man-machine collaborative driving using game theory, the trajectory tracking behavior of the driver and the automatic driving system is described using an optimal control strategy based on a cost function, and the sum of the cost functions of both is a non-zero value. Moreover, the optimal trajectory tracking control is usually described by a predictive horizon and a control time domain, so the problem of trajectory tracking by man-machine collaborative driving can be abstracted as a non-zero-sum multi-stage dynamic game problem. For non-zero-sum multi-stage dynamic games, the game problems can be divided into two types according to the information mode of the game: closed-loop memoryless dynamic game problems and open-loop dynamic game problems.

[0035] Figure 4 is a schematic diagram showing the principle of the closed-loop dynamic game of the man-machine collaborative operation system in an exemplary embodiment of the present invention. As shown in Figure 4, in this information model, the participants' allowable strategy sets are mapped according to the initial state and the state of each stage, and "memoryless" means that the participants only know the initial and current states of the system when making decisions at each stage, and have no memory of the states of the remaining stages, so the actions of the participants at the i-th stage are JPEG2025512106000002.jpg514, JPEG2025512106000003.jpg514, i∈{0,1,…,n u}.

[0036] The closed-loop memoryless dynamic game corresponds to the open-loop dynamic game. Figure 5 is a schematic diagram showing the principle of the open-loop dynamic game of the man-machine collaborative operation system in an exemplary embodiment of the present invention. As shown in Figure 5, the entire process of the game has a total of n u The state vector of each stage system is x k Since the allowable strategy set of a participant at each stage is related only to the initial state, given the initial state x0, the strategy set is a constant function, so the behavior of the participant at the i-th stage is also a constant function. JPEG2025512106000004.jpg54, JPEG2025512106000005.jpg54, i∈{0,1,…, n u}.

[0037] Therefore, in step S101, the man-machine path tracking control game models in two different information modes, closed loop and open loop, can be established respectively.

[0038] (1) A closed-loop man-machine path-tracking control game model Figure 6 is a schematic diagram showing the flow of a method for constructing a closed-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. That is, the steering actions of the driver and the driving system are described by the Linear Quadratic Regulator (LQR) method of optimal multi-point preview. As shown in Figure 6, the method for constructing a man-machine path tracking control game model includes the following steps: In step S601, a first discrete state update equation of a vehicle dynamics system under man-machine collaborative driving in a closed-loop information mode is established according to the driver's deterministic steering torque and the driver's random steering torque. In step S602, the first discrete state update equation is extended according to the dynamic process of the man-machine preview to obtain a path tracking extended system including the man-machine preview state. In step S603, a driver trajectory cost function and a driving system trajectory cost function are constructed based on the path tracing extension system to obtain the man-machine path tracing control game model.

[0039] Specifically, since this section focuses on the modeling problem of man-machine interaction, the target trajectories of the man-machine can be assumed to have small tangential angles. Under the condition of small heading angles, the state vector in the model is: JPEG2025512106000006.jpg532, where: JPEG2025512106000007.jpg46 is the steering wheel rotation angle, JPEG2025512106000008.jpg56 is JPEG2025512106000009.jpg46, Y is the global ordinate of the center of gravity of the vehicle, JPEG2025512106000010.jpg43 is the vehicle heading angle, JPEG2025512106000011.jpg53 is This is the result of calculating the derivative of JPEG2025512106000012.jpg43.

[0040] In step S601, a first discrete state update equation of a vehicle dynamics system under man-machine collaborative driving in a closed-loop information mode is established according to the driver's deterministic steering torque and the driver's random steering torque.

[0041] Driver's deterministic steering torque JPEG2025512106000013.jpg54, and random steering torque JPEG2025512106000014.jpg57, and the steering torque of the driving system JPEG2025512106000015.jpg55. State vector Based on JPEG2025512106000016.jpg44, the driver's deterministic steering torque is expressed as shown in Equation (1). JPEG2025512106000017.jpg54 and driver random steering torque A continuous state space equation is established by JPEG2025512106000018.jpg57. JPEG2025512106000019.jpg1069(1) During the ceremony, JPEG2025512106000020.jpg47 is the steering torque related to distance, JPEG2025512106000021.jpg44, JPEG2025512106000022.jpg44, JPEG2025512106000023.jpg45, JPEG2025512106000024.jpg44 and JPEG2025512106000025.jpg44 are all parameter matrices in the model, as shown below. JPEG2025512106000026.jpg50170

[0042] To describe the man-machine cooperative operation problem as a multi-stage game, we consider the discrete time T s By discretizing the continuous system of the above equations by: JPEG2025512106000027.jpg1087(2) During the ceremony,

number

[0043] In step S602, the first discrete state update equation is extended according to the dynamic process of the man-machine preview to obtain a path tracking extended system including the man-machine preview state.

[0044] 7 is a schematic diagram illustrating the principle of the multi-point preview mode in an exemplary embodiment of the present invention. In order to model the path tracking control system by the LQR method and take into account the man-machine's predictive behavior on vehicle dynamics, the man-machine's preview behavior is first modeled as a multi-point preview mode as shown in FIG. 7. Referring to FIG. 7, at each time, the driver and the driving system preview a part of the target trajectory based on their own decision-making, and divide this area into n p The preview distance can be described as the number of preview points, and the preview distance is the driver's preview time t p is determined by t p =n p ×T s This dynamic process may be represented by a shift register as shown in equation (3). JPEG2025512106000033.jpg538(3) Where:

number

[0045] In the dynamic process of man-machine preview The dynamic system of the man-machine shared vehicle is extended by JPEG2025512106000035.jpg538, and the path tracking extended system including the man-machine preview state can be obtained, as shown in Equation (4). JPEG2025512106000036.jpg1079(4) Where:

number

[0046] In step S603, a driver trajectory cost function and a driving system trajectory cost function are constructed based on the path tracing extension system to obtain the man-machine path tracing control game model.

[0047] Specifically, in a path-tracking augmented system where man-machine decision-making conflicts, the prediction time domain and the control time domain are both n u By designing the steps, the driver trajectory cost function J1 and the driving system trajectory cost function J2, we obtain a man-machine path-following control game model that can be described as shown in Equation (6). JPEG2025512106000043.jpg1179 JPEG2025512106000044.jpg1166(6) Where:

number

[0048] Based on this, equation (6) can be calculated by the linear-quadratic method: u A multi-stage man-machine path-tracking control game model is constructed, and both cost functions include the steering control input of the other party to represent the man-machine interaction characteristics.

[0049] (2) Open-loop man-machine path-following control game model Figure 8 is a schematic diagram showing the flow of a method for constructing an open-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. That is, the mapping relationship between the difference in man-machine decision-making in open-loop information mode and steering torque collision is described by a distributed model predictive control (DMPC) strategy. As shown in Figure 8, the method for constructing a man-machine path tracking control game model includes the following steps: In step S801, a second discrete state update equation of a vehicle dynamics system under man-machine collaborative driving in an open-loop information mode is established according to the driver's deterministic steering torque and the driver's random steering torque. In step S802, a predicted output vector in a predicted time domain is determined according to the second discrete state update equation, and a driver-referred trajectory vector and a driving system-referred trajectory vector are determined. In step S803, the predicted output vector, the driver reference trajectory vector and the driving system reference trajectory vector are used to construct a driver trajectory cost function and a driving system trajectory cost function respectively, to obtain the man-machine path tracking control game model.

[0050] Specifically, under the framework of model predictive control, both the driver and the driving system predict the time domain n p The vehicle trajectory is estimated within the control time domain n uCompared with the linear quadratic regulator method, the model predictive control more intuitively reflects the target trajectory planned by the driver and the decision-making layer of the autonomous driving system in the final interaction model. At the same time, as can be seen from the model predictive control algorithm, the state prediction vector in its cost function is both the current state of the system and the control time domain n u Since the control law is established based on the control input in the , the control law is also related only to the current initial state, which is exactly in line with the definition of the open-loop information mode.

[0051] In step S801, a second discrete state update equation of a vehicle dynamics system under man-machine collaborative driving in an open-loop information mode is established according to the driver's deterministic steering torque and the driver's random steering torque.

[0052] For the dynamic system of a man-machine collaborative driving vehicle, when the uncertain actions of the driver are incorporated into the disturbances of the system, the second discrete state update equation is obtained, as shown in equation (7). JPEG2025512106000062.jpg1083(7) Where:

number

[0053] Based on the second discrete state update equation above, the disturbance input in the predicted time domain If JPEG2025512106000069.jpg56 is assumed to remain constant, the next n p The model output of a step may be expressed as: JPEG2025512106000070.jpg76168

[0054] In step S802, a predicted output vector in a predicted time domain is determined according to the second discrete state update equation, and a driver-referred trajectory vector and a driving system-referred trajectory vector are determined.

[0055] The prediction time domain and control time domain of the model prediction algorithm for man-machine collaborative operation system are both n u At time point k, we assume that the model prediction output vector in the prediction time domain is JPEG2025512106000071.jpg55, and the man-machine control input vector is defined as shown in equations (9) and (10). JPEG2025512106000072.jpg46 and Define them as JPEG2025512106000073.jpg47 respectively. JPEG2025512106000074.jpg761(8) JPEG2025512106000075.jpg644(9) JPEG2025512106000076.jpg645(10)

[0056] Based on the second discrete state update equation (Eq. 7), the next n p The model output of a step, i.e., the predicted output vector, may be expressed as shown in equation (11). JPEG2025512106000077.jpg556(11) Where: JPEG2025512106000078.jpg649, JPEG2025512106000079.jpg676, JPEG2025512106000080.jpg2279, The file is JPEG2025512106000081.jpg2279.

[0057] At each time step k, the reference trajectory vectors of the driver and the automated driving system may be expressed as shown in equation (12). JPEG2025512106000082.jpg654 JPEG2025512106000083.jpg657(12)

[0058] In step S803, the predicted output vector, the driver reference trajectory vector and the driving system reference trajectory vector are used to construct a driver trajectory cost function and a driving system trajectory cost function respectively, to obtain the man-machine path tracking control game model.

[0059] The parameters in the man-machine path-following control game model are the predicted output vector JPEG2025512106000084.jpg55 and reference trajectory vector JPEG2025512106000085.jpg46, JPEG2025512106000086.jpg47, and obtain the driver trajectory cost function and the driving system trajectory cost function as shown in equation (13). JPEG2025512106000087.jpg652 JPEG2025512106000088.jpg554(13) During the ceremony, JPEG2025512106000089.jpg55, JPEG2025512106000090.jpg45 is a weight matrix for path tracking control, where x∈{1, 2}, JPEG2025512106000091.jpg670, JPEG2025512106000092.jpg658.

[0060] In step S102, the man-machine path tracing control game model is solved to obtain man-machine torque collision information.

[0061] In step S101, man-machine path tracking control game models are constructed in two different information modes, closed loop and open loop, respectively, and the solution methods for the two game models are also different.

[0062] In addition, for the problem of non-cooperative games, in man-machine cooperative driving systems, the controller of the automatic driving system is usually designed by a mirror symmetric anthropomorphic strategy to improve the consistency between man and machine, so that the driver and the automatic driving system have an equal relationship in the game process, and when the game participants have a symmetric or equal relationship, Nash equilibrium provides a reasonable theoretical solution to non-cooperative games, and in this equilibrium state, neither party occupies a leading position in the decision-making process, and neither party can unilaterally adjust its own decision-making to reduce the value of its own trajectory tracking cost function.

[0063] There is also another non-cooperative game problem, the Master-Slave game problem in a dual agent system, in which the leader makes a decision first based on the follower's reaction to his decision, but the follower makes a corresponding decision after observing the leader's decision. The result of such a hierarchical game is called the Stackelberg Equilibrium.

[0064] Nash equilibrium and Stackelberg equilibrium are theoretical models of the decision-making and control mechanism of the man-machine cooperative driving system, and for each game model, two solutions of Nash equilibrium and Stackelberg equilibrium corresponding to this model can be obtained. Therefore, we next use a quantitative model based on the theory of four non-cooperative games to deeply analyze the mapping relationship between the difference in man-machine decision-making and steering torque conflict in Nash equilibrium and Stackelberg equilibrium based on two information modes of open loop and closed loop, and explore the optimal modeling scheme and modeling method of the man-machine interaction mechanism.

[0065] (1) Nash equilibrium solutions for man-machine decision-making and control in the closed-loop information mode In one embodiment of the present invention, the problem of solving a Nash equilibrium in the closed-loop information mode can be written as a Hamiltonian constrained optimization problem as shown in equation (14). JPEG2025512106000093.jpg43134 During the ceremony, JPEG2025512106000094.jpg54 is a covariant vector.

[0066] This is a closed-form solution to the constraint optimization problem in the above equation. JPEG2025512106000095.jpg552 constitutes a closed-loop Nash equilibrium solution.

[0067] The Nash equilibrium solution in the open-loop mode is an open-loop Nash equilibrium solution because it is related only to the initial state and not to the current state of each stage. Although JPEG2025512106000096.jpg543 also satisfies the closed-loop Nash equilibrium condition (14), it becomes clear that the solution to the closed-loop Nash equilibrium problem is not limited to the open-loop Nash equilibrium solution, and this non-uniqueness of information causes the problem that there are multiple Nash equilibrium solutions in the closed-loop information structure. In this specification, when modeling the system, the parameter of the driver random steering torque, Considering JPEG2025512106000097.jpg44, the non-uniqueness of information in the game process is exactly eliminated, so that the problem of multiple solutions can be avoided by feedback Nash equilibrium, and the optimal solutions at each stage of feedback Nash equilibrium respectively satisfy the following conditions: JPEG2025512106000098.jpg71167

[0068] The feedback Nash equilibrium condition under closed-loop conditions conforms to the Bellman principle of optimality, and the random Stochastic Dynamic Programming (SDP) algorithm can be used to obtain the closed-loop Nash equilibrium solution (also called the feedback Nash equilibrium solution) of the path tracking control system under the condition of conflicting man-machine decision-making.

[0069] 9 is a schematic diagram showing a flow of a method for solving a closed-loop man-machine path tracking control game model in an exemplary embodiment of the present invention. As shown in FIG. 9, the method for solving a man-machine path tracking control game model includes the following steps: In step S901, the recursive relationship of the steering control value functions corresponding to the driver and the driving system respectively under the Nash equilibrium condition is determined by the random dynamic programming algorithm. In step S902, according to the first discrete state update equation and the recurrence relationship, closed-loop Nash equilibrium solutions corresponding to the driver and the driving system respectively are calculated as the man-machine torque collision information.

[0070] Specifically, at any time step k, the unmodeled disturbances of the man-machine collaborative operation system JPEG2025512106000099.jpg44 is u If it is assumed to remain constant in the dynamic game over the entire stage, the Gaussian random distribution JPEG2025512106000100.jpg419 is used to describe the parameters related to the driver random steering torque, where: JPEG2025512106000101.jpg42, JPEG2025512106000102.jpg43 represent the mean and standard deviation of the Gaussian distribution, respectively.

[0071] is the disturbance vector JPEG2025512106000103.jpg44, Due to the existence of JPEG2025512106000104.jpg44, the solution of the man-machine game problem based on the steering torque interaction becomes an affine quadratic type problem, so in the solution process based on dynamic programming, the steering control value function of the driver and the driving system has an affine quadratic type form, as shown in equation (15). JPEG2025512106000105.jpg1279 JPEG2025512106000106.jpg1169(15)

[0072] The steering control value function in the above equation (15) is the jth to nth stages of the cost functions of the driver and the driving system. u represents the value of the value function in the game process up to the stage, and the steering control value functions of the k+j-th step and the k+j+1-th step satisfy a recurrence relationship as shown in equation (16). JPEG2025512106000107.jpg871 JPEG2025512106000108.jpg771(16) In the equation, the superscript “N” represents the value function under the Nash equilibrium condition, and the one-step cost function g() of each stage may be expressed as shown in equation (17). JPEG2025512106000109.jpg1179 JPEG2025512106000110.jpg1178(17)

[0073] First discrete state update equation By substituting JPEG2025512106000111.jpg555 (Equation 4) into the steering control value function (Equation 15), the man-machine torque that satisfies the closed-loop Nash equilibrium relationship satisfies the relationship shown in Equation (18). JPEG2025512106000112.jpg1079 JPEG2025512106000113.jpg1071(18)

[0074] (2) Stackelberg equilibrium solution of man-machine decision-making and control in the closed-loop information mode 10 is a schematic diagram showing the flow of another closed-loop man-machine path tracking control game model solution method in an exemplary embodiment of the present invention. As shown in FIG. 10, the man-machine path tracking control game model solution method includes the following steps: In step S1001, a random dynamic programming algorithm is used to determine the recursive relationship of steering control value functions corresponding respectively to the driver and the driving system under the Stackelberg equilibrium condition. In step S1002, a driver response function is determined based on a recursive relationship of a steering control value function corresponding to the driving system. In step S1003, an open-loop Stackelberg equilibrium solution corresponding to the driving system is calculated based on the recurrence relationship between the first discrete state update equation, the driver response function, and the steering control value function corresponding to the driving system. In step S1004, an open-loop Stackelberg equilibrium solution corresponding to the driver is calculated based on the open-loop Stackelberg equilibrium solution corresponding to the driving system, and is used as the man-machine torque collision information.

[0075] Specifically, the Stackelberg equilibrium is different from the Nash equilibrium in that there is a master-slave relationship between the driver and the automated driving system. At each stage of the game, the driving system, which is the leader, takes the steering control input first, and the driver observes this action and makes a corresponding reaction.

[0076] Therefore, the closed-loop Stackelberg equilibrium solution can be found by backward induction. Based on the random dynamic programming method, the recursion relation of the driver steering control value function is JPEG2025512106000114.jpg57 is This is the same as JPEG2025512106000115.jpg57 (see Expression 16).

[0077] The recurrence relationship of the steering control value function of the driving system in the closed-loop Stackelberg equilibrium solution (also called the feedback Stackelberg equilibrium solution) in the closed-loop information mode satisfies the condition shown in equation (19). JPEG2025512106000116.jpg1379(19) where the superscript "S" represents the value function in the Stackelberg equilibrium condition, where The image is JPEG2025512106000117.jpg15166.

[0078] First discrete state update equation JPEG2025512106000118.jpg555(Equation 4) and the recurrence relationship of the driver steering control value function By substituting JPEG2025512106000119.jpg57 into the recurrence relationship (Equation 19) of the driving system steering control value function, a driver response function with respect to the driving system steering torque can be obtained as shown in Equation (20). JPEG2025512106000120.jpg1179(20)

[0079] By substituting the first discrete state update equation (Equation 4) and the driver response function (Equation 20) into the recurrence relationship (Equation 19) of the driving system steering control value function, an open-loop Stackelberg equilibrium solution of the driving system in the Stackelberg equilibrium strategy is obtained, as shown in Equation (21). JPEG2025512106000121.jpg1079JPEG2025512106000122.jpg577JPEG2025512106000123.jpg1079(21) During the ceremony, JPEG2025512106000124.jpg647, JPEG2025512106000125.jpg539, JPEG2025512106000126.jpg539, JPEG2025512106000127.jpg560.

[0080] Since the driving system is the leader and the driver is the follower, a closed-form solution to the constraint optimization problem of the Hamiltonian function corresponding to the driver can be obtained as the open-loop Stackelberg equilibrium solution of the driver from the open-loop Stackelberg equilibrium solution of the driving system.

[0081] (3) Nash equilibrium solutions for man-machine decision-making and control in the open-loop information mode 11 is a schematic diagram showing the flow of another open-loop man-machine path tracking control game model solving method in an exemplary embodiment of the present invention. As shown in FIG. 11, the man-machine path tracking control game model solving method includes the following steps: In step S1101, a closed-form solution of a model corresponding to the man-machine path tracing control game model is obtained, and then a relational equation between the man-machine steering control and the target trajectory is obtained based on the closed-form solution of the model. In step S1102, the relational equation is solved by a convex iterative algorithm to obtain open-loop Nash equilibrium solutions corresponding to the driver and the driving system, respectively, as the man-machine torque collision information.

[0082] Specifically, based on the definition of open-loop Nash equilibrium, we obtain the Nash equilibrium solution of the system in the open-loop information mode by a convex iterative algorithm.

[0083] For an unconstrained problem such as equation (13), the man-machine path-following control law has the following closed-form solution, as shown in equation (22).

number

number

[0084] As can be seen from equation (23), there is an interaction between the two control laws, that is, each control action is not only related to the decision-making objective, system state, and disturbance, but also closely related to the other control strategy. Therefore, in order to eliminate the interaction from equation (23), it is solved by a convex iterative algorithm to obtain the update equation as shown in equation (24). JPEG2025512106000133.jpg553 JPEG2025512106000134.jpg456(24)

[0085] The solution process of the convex iterative algorithm can be summarized as follows. First, the initial value of the iteration JPEG2025512106000135.jpg59, JPEG2025512106000136.jpg510 is determined, and then substituted into the relational expression (Equation 23) to obtain the current optimal value. JPEG2025512106000137.jpg59, JPEG2025512106000138.jpg510 is calculated, and then substituted into the update formula (Formula 24). JPEG2025512106000139.jpg59, Update JPEG2025512106000140.jpg510 and repeat in this manner. As i approaches infinity, the update equation (Equation 24) becomes: JPEG2025512106000141.jpg554 JPEG2025512106000142.jpg457(25) Therefore, the relational expression (Equation 23) becomes as follows: JPEG2025512106000143.jpg20129Therefore, the expression of the Nash equilibrium solution of man-machine decision-making and control in the open-loop information mode is as shown in equation (27). JPEG2025512106000144.jpg2079(27)

[0086] In the actual modeling process, the value of the first stage of the game is taken as the man-machine interaction result of the open-loop Nash equilibrium at time point k, that is, the man-machine torque conflict information. JPEG2025512106000145.jpg546 JPEG2025512106000146.jpg547(28)

[0087] (4) Stackelberg equilibrium solutions for man-machine decision-making and control in the open-loop information mode 12 is a schematic diagram showing the flow of another open-loop man-machine path tracking control game model solving method in an exemplary embodiment of the present invention. As shown in FIG. 12, the man-machine path tracking control game model solving method includes the following steps: In step S1201, the driving system trajectory cost function is converted into a driving system trajectory optimization function that takes into account the driver's response function. In step S1202, the steering system trajectory optimization function is solved to obtain an open-loop Stackelberg equilibrium solution corresponding to the steering system. In step S1203, an open-loop Stackelberg equilibrium solution corresponding to the driver is calculated based on the open-loop Stackelberg equilibrium solution and the driver trajectory cost function, and is set as the man-machine torque collision information.

[0088] Specifically, the open-loop Stackelberg equilibrium solution is realized by a backward induction method similar to that used to solve the closed-loop Stackelberg equilibrium. The predicted output vector JPEG2025512106000147.jpg55 (Equation 11) is substituted into the game model (Equation 13) to obtain the following equation. JPEG2025512106000148.jpg656 JPEG2025512106000149.jpg560(29) During the ceremony, JPEG2025512106000150.jpg553, The image is JPEG2025512106000151.jpg554.

[0089] Unlike solving an open-loop Nash equilibrium, the master-slave game is different in that in each stage of the game process, the autonomous driving system acts first as the leader, and the driver observes the operation of the autonomous driving system and then makes a corresponding reaction.

[0090] Therefore, as shown in equation (30), JPEG2025512106000152.jpg43 is calculated to obtain the driver response function to the driving system. JPEG2025512106000153.jpg1379(30)

[0091] When a control strategy is adopted, the driving system takes into account the driver's response function to it in its cost function to obtain a new driving system trajectory cost function, as shown in equation (31). JPEG2025512106000154.jpg1179(31)

[0092] Therefore, finding a Stackelberg equilibrium solution for steering torque control of a driving system in the open-loop information mode amounts to solving an unconstrained optimization problem such as that shown in equation (32). JPEG2025512106000155.jpg10104(32)

[0093] By solving the above optimization problem, we can obtain the open-loop Stackelberg equilibrium solution corresponding to the operation system, as shown in equation (33). JPEG2025512106000156.jpg569(33) During the ceremony, JPEG2025512106000157.jpg528, JPEG2025512106000158.jpg526, JPEG2025512106000159.jpg517, JPEG2025512106000160.jpg531, The image is JPEG2025512106000161.jpg1034.

[0094] This is the Stackelberg equilibrium solution for steering control of the driving system. Based on JPEG2025512106000162.jpg57, the optimal driver response to the autonomous driving system steering control can be obtained by solving an optimization problem such as equation (34). JPEG2025512106000163.jpg1086(34)

[0095] From the above equations, the Stackelberg equilibrium solution of the driver steering control in the open-loop information mode can be obtained, as shown in equation (35). JPEG2025512106000164.jpg570(35) During the ceremony, JPEG2025512106000165.jpg527, JPEG2025512106000166.jpg518, JPEG2025512106000167.jpg531, JPEG2025512106000168.jpg529, JPEG2025512106000169.jpg930.

[0096] Similarly, we take the open-loop Stackelberg equilibrium solution of the first stage of the game to describe the interaction result of the man-machine steering torque at time point k, as shown in equation (36). JPEG2025512106000170.jpg545 JPEG2025512106000171.jpg547(36)

[0097] Unlike open-loop Nash equilibrium, the open-loop Stackelberg equilibrium is solved by backward induction. Therefore, when solving the autonomous driving system control law (Equation 34), it is possible to add constraints to make it a constraint optimization problem so that the controller satisfies the expected performance. Therefore, the significance of the open-loop Stackelberg equilibrium strategy proposed in this specification is not only that it proposes a theoretical model of man-machine steering torque interaction, but also that this algorithm makes it possible to flexibly design an interaction-type steering assist controller that satisfies kinematic and dynamic safety constraints.

[0098] In step S103, a shared control strategy is determined based on the man-machine torque collision information, and then vehicle control is performed based on the shared control strategy.

[0099] Specifically, the man-machine torque collision information obtained in step S102 establishes a theoretical basis between the difference in man-machine decision-making and collision control, and based on this theoretical basis, a shared control strategy under emergency lane change situations can be better designed, thereby guiding vehicle control.

[0100] In order to establish the theoretical relationship between the difference in man-machine decision-making and collision control, the present invention respectively models the mapping relationship between the difference in man-machine decision-making and the interaction of man-machine steering torque within the theoretical framework of four types of dynamic non-cooperative games.

[0101] On the one hand, the dynamic model of the collaborative driving system is extended by the man-machine target trajectory, and then the linear-quadratic regulator method is used to model the man-machine interaction behavior in the feedback information mode.

[0102] Since the model establishes a mapping relationship between the difference in man-machine decision-making and the interaction of steering torque, the solution to the problem of discrepancies in man-machine decision-making due to the existence of steering resistance torque and driver uncertainty torque becomes an affine quadratic game problem, so this specification proposes an algorithm for an affine quadratic game based on random dynamic programming to find feedback-Nash equilibrium solutions and feedback-Stackelberg equilibrium solutions that describe the interaction relationship between man-machine decision-making and steering torque.

[0103] On the other hand, the problem of multi-target path tracking control of humans and vehicles in an open loop is described using a distributed model predictive control method, and in order to solve the man-machine decision-making and control model in the open-loop information mode, the open-loop Nash equilibrium solution and the open-loop Stackelberg equilibrium solution that describe the mapping relationship between man-machine decision-making and control are obtained using the model predictive control method.

[0104] 13 is a schematic diagram showing the configuration of a collision control device operated by a man-machine in collaboration with one another in an exemplary embodiment of the present invention. As shown in FIG. 13, the collision control device operated by a man-machine in collaboration with one another 1300 can include a modeling module 1301, a solution module 1302, and an operation module 1303. Here, The modeling module 1301 is configured to establish a man-machine path tracking control game model corresponding to the man-machine interaction behavior based on the driver's deterministic steering torque and the driver's random steering torque. The solution module 1302 is configured to solve the man-machine path tracking control game model to obtain man-machine torque conflict information. The operation module 1303 is configured to determine a shared control strategy according to the man-machine torque collision information, and then perform vehicle control according to the shared control strategy.

[0105] According to an exemplary embodiment of the present invention, the modeling module 1301 includes a first modeling unit, which is configured to establish a first discrete state update equation of a vehicle dynamic system under man-machine collaborative driving in a closed-loop information mode based on the driver's deterministic steering torque and the driver's random steering torque, extend the first discrete state update equation according to a dynamic process of a man-machine preview, obtain a path tracking extension system including a man-machine preview state, and construct a driver trajectory cost function and a driving system trajectory cost function based on the path tracking extension system, thereby obtaining a man-machine path tracking control game model.

[0106] According to an exemplary embodiment of the present invention, the modeling module 1301 includes a second modeling unit, which is configured to establish a second discrete state update equation of a vehicle dynamics system under man-machine collaborative driving in an open-loop information mode based on the driver's deterministic steering torque and the driver's random steering torque, determine a predicted output vector in a predicted time domain based on the second discrete state update equation, and determine a driver reference trajectory vector and a driving system reference trajectory vector, and use the predicted output vector, the driver reference trajectory vector and the driving system reference trajectory vector to respectively construct a driver trajectory cost function and a driving system trajectory cost function to obtain a path tracking control game model of the man-machine.

[0107] According to an exemplary embodiment of the present invention, the solution module 1302 includes a first solution unit, which is configured to determine a recurrence relationship of steering control value functions respectively corresponding to the driver and the driving system under a Nash equilibrium condition through a random dynamic programming algorithm, and calculate a closed-loop Nash equilibrium solution respectively corresponding to the driver and the driving system as the torque collision information of the man-machine based on the first discrete state update equation and the recurrence relationship.

[0108] According to an exemplary embodiment of the present invention, the solution module 1302 includes a second solution unit, which is configured to use a random dynamic programming algorithm to determine a recurrence relationship of steering control value functions respectively corresponding to a driver and a driving system under a Stackelberg equilibrium condition, determine a driver response function according to the recurrence relationship of the steering control value function corresponding to the driving system, calculate an open-loop Stackelberg equilibrium solution corresponding to the driving system according to the first discrete state update equation, the driver response function, and the recurrence relationship of the steering control value function corresponding to the driving system, and calculate an open-loop Stackelberg equilibrium solution corresponding to the driver according to the open-loop Stackelberg equilibrium solution corresponding to the driving system, as the torque collision information of the man-machine.

[0109] According to an exemplary embodiment of the present invention, the solution module 1302 includes a third solution unit, which is configured to obtain a closed-form solution of a model corresponding to the man-machine path tracking control game model, obtain a relationship equation between the man-machine steering control and a target trajectory based on the closed-form solution of the model, and obtain an open-loop Nash equilibrium solution corresponding to the driver and the driving system as the torque collision information of the man-machine by solving the relationship equation through a convex iteration algorithm.

[0110] According to an exemplary embodiment of the present invention, the solution module 1302 includes a fourth solution unit, which is configured to convert the driving system trajectory cost function into a driving system trajectory optimization function taking into account a driver's reaction function, solve the driving system trajectory optimization function to obtain an open-loop Stackelberg equilibrium solution corresponding to the driving system, and calculate an open-loop Stackelberg equilibrium solution corresponding to the driver based on the open-loop Stackelberg equilibrium solution and the driver trajectory cost function, as the torque collision information of the man-machine.

[0111] The specific details of each module in the man-machine collaborative collision control device 1300 are described in detail in the corresponding man-machine collaborative collision control method, so that the description will be omitted here.

[0112] It should be noted that, although the above detailed description describes several modules and units of the device for performing operations, such division is not mandatory. In fact, according to an embodiment of the present invention, features and functions of two or more of the modules and units described above may be embodied in one module and unit. Conversely, features and functions of one of the modules and units described above may be further embodied by multiple modules and units.

[0113] In an exemplary embodiment of the present invention, a recording medium capable of implementing the above method is further provided. FIG. 14 is a schematic diagram showing a computer-readable recording medium in an exemplary embodiment of the present invention. As shown in FIG. 14, a program product 1400 for implementing the above method according to an embodiment of the present invention is shown, which can use a portable compact disc read-only memory (CD-ROM), includes a program code, and can be executed on a terminal device such as a mobile phone. However, the program product of the present invention is not limited thereto, and in this specification, a readable recording medium can be any tangible medium that contains or stores a program that can be used by or with an instruction execution system, apparatus, or device.

[0114] In an exemplary embodiment of the present invention, there is further provided an electronic device capable of implementing the above method. Figure 15 is a schematic diagram showing the structure of a computer system of the electronic device in the exemplary embodiment of the present invention.

[0115] It should be noted that the computer system 1500 of the electronic device shown in FIG. 15 is merely an example and does not impose any limitations on the functions and scope of use of the embodiments of the present invention.

[0116] As shown in Fig. 15, a computer system 1500 includes a central processing unit (CPU) 1501, and can execute various appropriate operations and processes based on a program stored in a read-only memory (ROM) 1502 or a program loaded from a storage unit 1508 to a random access memory (RAM) 1503. The RAM 1503 further stores various programs and data necessary for the operation of the system. The CPU 1501, the ROM 1502, and the RAM 1503 are connected to each other via a bus 1504. An input / output (I / O) interface 1505 is also connected to the bus 1504.

[0117] To the I / O interface 1505, an input unit 1506 including a keyboard, a mouse, etc., an output unit 1507 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, a storage unit 1508 including a hard disk, etc., and a communication unit 1509 including, for example, a network interface card such as a LAN (Local Area Network) card and a modem, are connected. The communication unit 1509 executes communication processing via a network such as the Internet. A driver 1510 is also connected to the I / O interface 1505 as necessary. A removable medium 1511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is installed in the driver 1510 as necessary, and a computer program read from the medium is installed in the storage unit 1508 as necessary.

[0118] In particular, according to an embodiment of the present invention, the processes described below with reference to the flowcharts may be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product including a computer program carried on a computer-readable medium, the computer program including program code for performing the methods illustrated in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication unit 1509 and / or installed from a removable medium 1511. When the computer program is executed by the central processing unit (CPU) 1501, it performs various functions specific to the system of the present invention.

[0119] It should be noted that the computer-readable medium according to the embodiment of the present invention may be a computer-readable signal medium or a computer-readable recording medium or any combination thereof. The computer-readable recording medium may be, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable recording medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer magnetic disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable recording medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, in which computer-readable program code is carried. Such a propagated data signal may take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable recording medium that may transmit, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained in the computer-readable medium may be transmitted by any suitable medium, including, but not limited to, wireless, wire, or the like, or any suitable combination thereof.

[0120] The flowcharts and block diagrams in the drawings illustrate possible architectures, functions, and operations of systems, methods, and computer program products in various embodiments of the present invention. In this regard, each block in the flowcharts or block diagrams may represent a module, program segment, or part of code, which includes executable instructions for implementing one or more predetermined logical functions. It should also be noted that in some alternative embodiments, the functions described in the blocks may be executed in a different order than the order described in the drawings. For example, two blocks shown in succession may actually be executed substantially in parallel, or may be executed in the reverse order depending on the related functions. It should also be noted that each block in the block diagrams or flowcharts, and combinations of blocks in the block diagrams or flowcharts, may be implemented in a dedicated hardware-based system for executing a predetermined function or operation, or in a combination of dedicated hardware and computer instructions.

[0121] The units according to the embodiments of the present invention may be implemented in software or hardware, and the described units may be provided in a processor, where the names of the units do not limit the units themselves, if any.

[0122] According to another aspect, the present invention further provides a computer-readable medium. The computer-readable medium may be included in the electronic device according to the above embodiment, or may exist independently but not integrated in the electronic device. The computer-readable medium has one or more programs disposed thereon, and when the one or more programs are executed by the electronic device, the electronic device realizes the method according to the above embodiment.

[0123] It should be noted that, although the above detailed description describes several modules and units of the device for performing operations, such division is not mandatory. In fact, according to an embodiment of the present invention, features and functions of two or more of the modules and units described above may be embodied in one module and unit. Conversely, features and functions of one of the modules and units described above may be further embodied by multiple modules and units.

[0124] From the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein may be realized by hardware or by combining software with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention may be expressed in the form of a software product, which can be stored in a non-volatile storage medium (which may be a CD-ROM, a USB flash memory, a mobile hard disk, etc.) or a network, and includes a number of commands for causing a computer device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0125] Other embodiments of the present invention will be readily apparent to those skilled in the art upon consideration of this specification and by practicing the teachings disclosed herein. The present invention includes any modification, use, or adaptation to the present invention, which modification, use, or adaptation follows the general principles of the present invention and includes known or ordinary techniques in the art that are not disclosed herein.

[0126] The present invention is not limited to the specific constructions described above and illustrated in the drawings, and various modifications and variations may be made without departing from the scope of the present invention, which is limited only by the appended claims.

Claims

1. Establishing a man-machine path tracking control game model corresponding to a man-machine interaction behavior according to a driver's deterministic steering torque and a driver's random steering torque; solving the man-machine path tracking control game model to obtain man-machine torque collision information; determining a shared control strategy based on the man-machine torque collision information, and controlling the vehicle based on the shared control strategy. A collision control method using man-machine collaborative operation.

2. When the man-machine path tracking control game model is a closed-loop game model, the step of establishing a man-machine path tracking control game model corresponding to a man-machine interaction behavior according to the driver's deterministic steering torque and the driver's random steering torque includes: Establishing a first discrete state update equation of a vehicle dynamics system under man-machine collaborative driving in a closed-loop information mode according to the driver's deterministic steering torque and the driver's random steering torque; augmenting the first discrete state update equation with a dynamic process of the man-machine preview to obtain a path tracking augmented system including the man-machine preview state; and constructing a driver trajectory cost function and a driving system trajectory cost function based on the path tracking extension system to obtain the man-machine path tracking control game model.

2. A method for collision control through man-machine cooperative operation according to claim 1.

3. When the man-machine path tracking control game model is an open-loop game model, the step of establishing a man-machine path tracking control game model corresponding to a man-machine interaction behavior according to the driver's deterministic steering torque and the driver's random steering torque includes: Establishing a second discrete state update equation of a vehicle dynamics system under man-machine collaborative driving in an open-loop information mode according to the driver's deterministic steering torque and the driver's random steering torque; determining a predicted output vector in a predicted time domain according to the second discrete state update equation, and determining a driver-referred trajectory vector and a driving system-referred trajectory vector; and obtaining a man-machine path-following control game model by constructing a driver trajectory cost function and a driving system trajectory cost function using the predicted output vector, the driver reference trajectory vector, and the driving system reference trajectory vector, respectively.

2. A method for collision control through man-machine cooperative operation according to claim 1.

4. The step of solving the man-machine path tracing control game model to obtain man-machine torque collision information includes: determining a recurrence relationship of steering control value functions corresponding to the driver and the driving system respectively under a Nash equilibrium condition by a random dynamic programming algorithm; calculating closed-loop Nash equilibrium solutions corresponding to the driver and the driving system, respectively, as the man-machine torque collision information based on the first discrete state update equation and the recurrence relationship.

3. A method for collision control through man-machine cooperative operation according to claim 2.

5. The step of solving the man-machine path tracing control game model to obtain man-machine torque collision information includes: determining a recurrence relationship of steering control value functions corresponding to the driver and the driving system respectively under a Stackelberg equilibrium condition using a random dynamic programming algorithm; determining a driver response function based on a recursive relationship of a steering control value function corresponding to the driving system; calculating an open-loop Stackelberg equilibrium solution corresponding to a driving system based on a recurrence relationship between the first discrete state update equation, the driver response function, and a steering control value function corresponding to the driving system; and calculating an open-loop Stackelberg equilibrium solution corresponding to a driver based on the open-loop Stackelberg equilibrium solution corresponding to the driving system, and setting the calculated solution as torque collision information of the man-machine.

3. A method for collision control through man-machine cooperative operation according to claim 2.

6. The step of solving the man-machine path tracing control game model to obtain man-machine torque collision information includes: obtaining a closed-form solution of a model corresponding to the man-machine path tracking control game model, and obtaining a relationship between the man-machine steering control and a target trajectory based on the closed-form solution of the model; and solving the relational equations by a convex iterative algorithm to obtain open-loop Nash equilibrium solutions corresponding to the driver and the driving system, respectively, as the man-machine torque collision information.

4. A method for collision control through man-machine cooperative operation according to claim 3.

7. The step of solving the man-machine path tracing control game model to obtain man-machine torque collision information includes: converting the driving system trajectory cost function into a driving system trajectory optimization function that takes into account a driver response function; solving the steering system trajectory optimization function to obtain an open-loop Stackelberg equilibrium solution corresponding to the steering system; and calculating an open-loop Stackelberg equilibrium solution corresponding to the driver based on the open-loop Stackelberg equilibrium solution and a driver trajectory cost function, and setting the calculated solution as torque collision information of the man-machine.

4. A method for collision control through man-machine cooperative operation according to claim 3.

8. A modeling module for establishing a man-machine path tracking control game model corresponding to a man-machine interaction behavior according to a driver's deterministic steering torque and a driver's random steering torque; a solving module for solving the man-machine path tracking control game model to obtain man-machine torque collision information; and an operation module for determining a shared control strategy based on the man-machine torque collision information, and performing vehicle control based on the shared control strategy. Collision control system operated by man-machine collaboration.

9. A computer-readable recording medium having a computer program stored therein, the computer program being capable of implementing the method for collision control through man-machine cooperative operation according to any one of claims 1 to 7 when the program is executed by a processor. A computer-readable recording medium.

10. one or more processors; a storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors are caused to realize the collision control method by man-machine cooperative operation according to any one of claims 1 to 7. electronic equipment.

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