Control system and control method

Abstract

To improve vehicle's ability to follow a target route.SOLUTION: A control system comprises: an acquisition section 121 to acquire a distance deviation of a vehicle from a target route thereof, an azimuth angle deviation between the first azimuth angle of the target route and the second azimuth angle of the vehicle, the yaw rate of the vehicle, the vehicle speed, and the sideslip angle of the vehicle; a generation section 122 to generate prediction models for changes in the distance deviation, the azimuth angle deviation, the sideslip angle, and the second azimuth angle on the basis of the distance deviation, the azimuth angle deviation, the vehicle speed, the sideslip angle, the yaw rate, the first azimuth angle, and a transfer function representing the relation between the yaw rate and the sideslip angle; and a yaw rate determination section 123 to determine a target yaw rate which minimizes a value of an evaluation function including, as parameters, an estimated distance deviation, an estimated azimuth angle deviation, and the target yaw rate predicted from the prediction models.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a control system and a control method for controlling the behavior of a vehicle.

Background Art

[0002] A control system for controlling the behavior of a vehicle is known. Patent Document 1 discloses a technique for determining a steering angle that minimizes the value of an evaluation function including a lateral deviation, an azimuth angle deviation, a steering angle, and a change amount of the steering angle.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, when a vehicle turns, a side slip angle is generated between the traveling direction of the vehicle and the direction of the wheels, and the vehicle turns accordingly. Therefore, when the vehicle is traveling along a target path with a large curvature, it is necessary for the vehicle to generate a side slip angle such that the vehicle follows the target path. However, the side slip angle generated by the steering angle or yaw rate of the vehicle determined without considering the side slip angle may be different from the side slip angle for turning the vehicle along the target path. Therefore, with a steering angle or yaw rate that does not take into account the side slip angle, the vehicle turns so as to deviate from the target path, and the vehicle cannot follow the target path.

[0005]

Means for Solving the Problems

[0006] In a first aspect of the present invention, there is provided an acquisition unit that acquires a distance deviation between a path point of a target path of a vehicle and the vehicle, an azimuth angle deviation between a first azimuth angle of the path point and a second azimuth angle of the vehicle, a yaw rate of the vehicle, a vehicle speed of the vehicle, and a sideslip angle of the vehicle; a generation unit that generates a prediction model for predicting changes in each of the distance deviation, the azimuth angle deviation, the sideslip angle, and the second azimuth angle based on the distance deviation, the azimuth angle deviation, the vehicle speed, the sideslip angle, the yaw rate, and the first azimuth angle, and a transfer function representing the relationship between the yaw rate and the sideslip angle; and a yaw rate determination unit that determines a target yaw rate as a target yaw rate by minimizing a value of an evaluation function that includes an estimated distance deviation, an estimated azimuth angle deviation, and a target yaw rate predicted from the prediction model and into which the acquired distance deviation, azimuth angle deviation, and yaw rate are input, thereby providing a control system.

[0007] The generation unit may generate a continuous-time prediction model and generate a discrete-time prediction model for predicting changes in each of the distance deviation, the azimuth angle deviation, the sideslip angle, and the second azimuth angle one unit of time ahead by discretizing the generated continuous-time prediction model.

[0008] The transfer function may be a function corresponding to a canonical response model that represents the relationship between the yaw rate and the second azimuth angle and outputs a change amount of the second azimuth angle when the yaw rate is input.

[0009] The control system may further include a steering angle determination unit that determines a target steering angle of the vehicle when the yaw rate and the determined target yaw rate are input, and the yaw rate determination unit may notify the target yaw rate to the steering angle determination unit.

[0010] The control system may further include a steering control unit that operates a steering wheel of the vehicle to set the steering angle of the vehicle to the target steering angle, and the acquisition unit may acquire the distance deviation, the azimuth angle deviation, the vehicle speed, the sideslip angle, and the yaw rate after the steering control unit sets the steering angle to the target steering angle.

[0011] The acquisition unit acquires the yaw moment of inertia of the vehicle, the weight of the vehicle, a first distance from the center of gravity of the vehicle to the axis of the front wheels of the vehicle, a second distance from the center of gravity point of the vehicle to the axis of the rear wheels of the vehicle, the vehicle length of the vehicle, the rear wheel cornering stiffness, and the longitudinal vehicle speed in the traveling direction of the vehicle as the vehicle speed, and the transfer function may be represented using the yaw moment of inertia, a first product of the weight, the longitudinal vehicle speed, and the first distance, a ratio of the longitudinal vehicle speed to a product of the rear wheel cornering stiffness, the second distance, and the vehicle length, a second product of the weight, the longitudinal vehicle speed, and the first distance, and a third product of the rear wheel cornering stiffness and the vehicle length.

[0012] In a second aspect of the present invention, a step of acquiring a distance deviation between a path point of a target path of a vehicle and the vehicle, an azimuth deviation between a first azimuth angle of the path point and a second azimuth angle of the vehicle, a yaw rate of the vehicle, the vehicle speed of the vehicle, and a sideslip angle of the vehicle, which are executed by a processor mounted on the vehicle; a step of generating a prediction model for predicting changes in each of the distance deviation, the azimuth deviation, the sideslip angle, and the second azimuth angle based on the distance deviation, the azimuth deviation, the vehicle speed, the sideslip angle, the yaw rate, the first azimuth angle, and a transfer function that represents the relationship between the yaw rate and the sideslip angle and outputs the sideslip angle when the yaw rate is input; and a step of determining a target yaw rate as a target yaw rate that minimizes a value of an evaluation function in which an estimated distance deviation, an estimated azimuth deviation, and a target yaw rate predicted from the prediction model are included as parameters and the acquired distance deviation, azimuth deviation, and yaw rate are input. A control method is provided.

Advantages of the Invention

[0013] According to the present invention, there is an effect that the followability of the vehicle to the target path can be improved.

Brief Description of the Drawings

[0014]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

[0015] [Configuration of Control System S] The configuration of the control system S will be described with reference to FIGS. 1 and 2. FIG. 1 is a diagram for explaining the movement of the vehicle A. FIG. 2 is a diagram for explaining the configuration of the control system S. The control system S is a system for causing the vehicle A to travel along the target path B by controlling the steering angle of the vehicle A. The control system S includes a vehicle control device 1 and is mounted on the vehicle A. The target path B is a predetermined path and includes path points indicating a plurality of traveling positions that the vehicle A aims at, and the directions that the vehicle A aims at at each path point.

[0016] In FIG. 1, an absolute coordinate system is used. The absolute coordinate system of the present embodiment uses, for example, the longitude direction as the X-axis and the latitude direction as the Y-axis, but is not limited thereto. Hereinafter, the speed component in the vehicle width direction of the vehicle speed V of the vehicle A is the lateral speed Vy. The speed component in the traveling direction orthogonal to the vehicle width direction of the vehicle speed V is the longitudinal speed Vx.

[0017] The distance deviation z is the distance between the center of gravity point C indicating the position of the vehicle A and the path point D of the target path B of the vehicle A. The azimuth angle deviation θ is the difference between the first azimuth angle ψ indicating the direction of the path point D of the target path B and the second azimuth angle φ indicating the direction of the vehicle A. The first azimuth angle ψ is the direction that the vehicle A aims at. The first azimuth angle ψ is, for example, the direction of the tangent line of the path point D.

[0018] The vehicle control device 1 is, for example, an ECU (Electronic Control Unit). The vehicle control device 1 includes a storage unit 11 and a control unit 12. The storage unit 11 is a storage medium including a ROM (Read Only Memory), a RAM (Random Access Memory), a hard disk, and the like. The storage unit 11 stores a program executed by the control unit 12.

[0019] The control unit 12 is a computing resource including a processor such as a CPU (Central Processing Unit). By executing the program stored in the storage unit 11, the control unit 12 realizes functions as an acquisition unit 121, a generation unit 122, a yaw rate determination unit 123, a steering angle determination unit 124, and a steering control unit 125.

[0020] The acquisition unit 121 acquires a plurality of pieces of information regarding the vehicle A. For example, the acquisition unit 121 uses the coordinates indicating the position of the vehicle A specified by a positioning system that measures the position using a signal output from a satellite and the coordinates indicating the position of the path point D of the target path to acquire a distance deviation z. The acquisition unit 121 acquires a first azimuth angle ψ and a second azimuth angle φ, and acquires the difference between the first azimuth angle ψ and the second azimuth angle φ as an azimuth angle deviation θ.

[0021] The acquisition unit 121 acquires a sideslip angle β of the vehicle A. For example, the acquisition unit 121 calculates the sideslip angle β using the acceleration in the traveling direction of the vehicle A and the acceleration in the vehicle width direction detected by an acceleration sensor mounted on the vehicle A. Note that the acquisition unit 121 may acquire the sideslip angle β using other methods.

[0022] The acquisition unit 121 acquires the yaw rate, vehicle speed V, and acceleration of the vehicle A. The acquisition unit 121 acquires the yaw rate of the vehicle A from, for example, a yaw rate sensor that detects the yaw rate of the vehicle A. The acquisition unit 121 acquires the acceleration from an acceleration sensor and acquires the vehicle speed V based on the acquired acceleration. The acquisition unit 121 may acquire the vehicle speed V based on a pulse signal proportional to the rotational speed of the wheels of the vehicle A. The acquisition unit 121 acquires the longitudinal vehicle speed Vx based on the acquired vehicle speed V.

[0023] The acquisition unit 121 is the yaw moment of inertia l of the vehicle A z , weight m, vehicle length l, and rear wheel cornering stiffness K r to acquire. Further, the acquisition unit 121 is the first distance l from the center of gravity of the vehicle A to the axis of the front wheels of the vehicle A f and the second distance l from the center of gravity point of the vehicle A to the axis of the rear wheels of the vehicle A r to acquire. For example, the acquisition unit 121 acquires the weight m, the first distance l f , the second distance l r and the vehicle length l stored in the storage unit 11. The acquisition unit 121, based on the yaw rate and acceleration, can acquire the yaw moment of inertia l z , the rear wheel cornering stiffness K r and the longitudinal vehicle speed. Note that the method by which the acquisition unit 121 acquires information regarding the vehicle A is not limited to this.

[0024] When traveling on a target path B along a road with a radius of curvature R, the desired rate of change of the azimuth angle of the vehicle A is expressed by the following formula (1) using the first azimuth angle ψ. Also, the desired acceleration in the vehicle width direction of the vehicle A is expressed by the following formula (2) using the distance deviation z.

Equation

[0025] The acquisition unit 121 acquires a relational expression representing the change amount of the distance deviation z (the first-order differential of the distance deviation z) from Equation (2). Specifically, the acquisition unit 121 acquires a relational expression representing the change amount of the distance deviation z shown in Equation (5) from Equation (3) representing the azimuth angle deviation θ and Equation (2). The azimuth angle deviation θ represented by the following Equation (3) is the difference between the second azimuth angle φ of the vehicle A and the first azimuth angle ψ of the path point D. Equation (4) is the equation obtained by differentiating both sides of Equation (3). Equation (5) is the equation obtained by substituting Equation (4) into Equation (2) and integrating both sides.

Number

[0026] In FIG. 1, when the sideslip angle β of the vehicle A is in a minute range (β << 1), the following Equation (6) holds.

Number

[0027] Here, a transfer function representing the relationship between the yaw rate and the sideslip angle will be described. The transfer function is a function that outputs the sideslip angle when the yaw rate is input. For example, the transfer function is the yaw inertia moment l z and the first product of the weight m, the longitudinal vehicle speed Vx, and the first distance l f and the ratio of the product of the rear wheel cornering stiffness K r , the second distance l r and the vehicle length l to the longitudinal vehicle speed Vx, and the second product of the weight m, the longitudinal vehicle speed Vx, and the first distance l f and the third product of the rear wheel cornering stiffness K r and the vehicle length l. Specifically, the transfer function is represented by the following Equation (7) using the change amounts of the sideslip angle β and the second azimuth angle φ (the first-order differential of the second azimuth angle φ represented by φ with a dot).

Number

Equation

[0028] The generation unit 122 generates a prediction model for predicting the state of the vehicle A. Specifically, the generation unit 122 generates a continuous-time prediction model for predicting the changes in the distance deviation z, the azimuth angle deviation θ, the vehicle speed V, the sideslip angle β, the target yaw rate r, and the first azimuth angle ψ, and the transfer function, for predicting the changes in each of the distance deviation z, the azimuth angle deviation θ, the sideslip angle β, and the second azimuth angle φ. More specifically, the generation unit 122 generates a continuous-time state equation represented by the following Equation (9) as the prediction model.

Equation

[0029] Note that the coefficient matrices A C , B cu and B cv vary according to the target path and the target vehicle speed. Therefore, the generation unit 122 discretizes the prediction model to generate a prediction model for predicting the change one unit time ahead (one step ahead). For example, the generation unit 122 generates a discrete-time prediction model by discretizing the continuous-time prediction model. Specifically, the generation unit 122 generates a discrete-time state equation for predicting the change of each of the distance deviation z, the azimuth angle deviation, the sideslip angle, and the second azimuth angle one unit time ahead by discretizing the continuous-time state equation represented by Equation (9) online. Hereinafter, a method for deriving the discrete-time state equation will be described.

[0030] The state equation after discretization is represented by the following Equations (10) to (13). T is the sampling period.

Equation

[0031] Since the solution of the continuous-time state equation is given by the following equation (14), substituting equation (14) into equation (10) allows us to derive the following equations (15) and (16).

Number

[0032] When representing zero-order hold as in the following equation (17) and substituting equation (17) into equation (16), the state variables for each sampling period can be expressed as in the following equation (18).

Number

[0033] Furthermore, from equation (18), the following equation (19) can be derived.

Number

[0034] Subsequently, by defining the following equations (20) and (21), the discrete-time state equation can be expressed as in the following equation (22).

Number

[0035] By comparing the coefficients of equations (10) and (22), the coefficient matrices of the state equation can be expressed as in the following equations (23) and (24).

Number

[0036] In this way, the discrete-time state equation was derived from the continuous-time state equation, which is a prediction model of continuous time. However, since Equation (24) is an equation including integration, it includes the movement of Vehicle A in the past cycle. As a result, a prediction model with high accuracy in the current cycle cannot be generated. In contrast, the generation unit 122 derives the following Equations (26) and (27) by using the following Equation (25) that holds in the matrix exponential function of A and B.

Number

[0037] The generation unit 122 generates a discrete-time prediction model by using Equations (25) to (27). In this way, by operating the generation unit 122, the generation unit 122 can generate a discrete-time prediction model with high accuracy. Furthermore, since the generation unit 122 can omit calculating the movement of Vehicle A in the past cycle, the calculation time can be shortened. As a result, the generation unit 122 can generate a prediction model with high accuracy at a certain cycle.

[0038] The yaw rate determination unit 123 determines the target yaw rate r of Vehicle A. The yaw rate determination unit 123 determines the target yaw rate r that minimizes the evaluation function based on the discrete-time prediction model. Specifically, the yaw rate determination unit 123 determines the target yaw rate r that minimizes the evaluation function including the estimated distance deviation z, the estimated azimuth angle deviation, and the target yaw rate predicted from the prediction model as parameters, and to which the acquired distance deviation z, azimuth angle deviation, and yaw rate are input. More specifically, the yaw rate determination unit 123 determines the target yaw rate r by using the weight Q z of the lateral deviation, the weight Q θ of the azimuth angle deviation, the weight R r of the target yaw rate r, the terminal weight Q zfinal of the lateral deviation, the terminal weight Q θfinal of the azimuth angle deviation, and the following Equation (28). Note that p is the length of the prediction horizon from the current time to a time a predetermined time ahead.

Number

[0039] The yaw rate determination unit 123 determines the target yaw rate r at each step from k = 0 to P - 1 that minimizes the evaluation function J. When the target yaw rate r at each step is determined, the sideslip angle corresponding to the target yaw rate r is estimated. In other words, when the estimated yaw rate at each step is determined, the influence of the sideslip angle corresponding to the target yaw rate r one step before is considered. Thereby, the yaw rate determination unit 123 can determine the target yaw rate r that can generate a sideslip angle capable of traveling along the target path B. Then, the yaw rate determination unit 123 notifies the steering angle determination unit 124 of the target yaw rate r at the next step (k = 1) among the plurality of target yaw rates r determined by minimizing the evaluation function J.

[0040] The steering angle determination unit 124 determines the target steering angle δ of the vehicle A based on the target yaw rate r determined by the yaw rate determination unit 123. For example, when the yaw rate of the vehicle A represented by φ with a dot acquired by the acquisition unit 121 and the target yaw rate r determined by the yaw rate determination unit 123 are input, the steering angle determination unit 124 determines the target steering angle δ of the vehicle A. FIG. 3 is a block diagram showing an example of the process of determining the target steering angle δ. The block diagram is designed so that the difference between the yaw rate of the vehicle A and the reference response becomes small.

[0041] The reference response model T in FIG. 3 d is the reference response model T corresponding to the transfer function represented by Equation (8) d is. C in FIG. 3 ff is a feedforward controller. C fb is a feedback controller. The range G surrounded by the broken line is a reference governor. The reference governor shapes the target value signal by numerical optimization so as to satisfy the constraint conditions regarding the input and output and realize a good transient response. The constraint conditions may be appropriately determined by experiments or the like.

[0042] Incidentally, the feedforward controller C ff, the feedback controller C fb , and the plant P are represented by the following equations. K, K P and K I are constants.

Equation

[0043] The steering angle determination unit 124 determines the target steering angle using equations (29), (30), and (31). Then, the steering angle determination unit 124 notifies the determined target steering angle to the steering control unit 125.

[0044] The steering control unit 125 operates the steering wheel 2 of the vehicle A to set the steering angle of the vehicle A to the target steering angle determined by the steering angle determination unit 124. For example, the steering control unit 125 rotates the steering wheel 2 so that the steering angle becomes the target steering angle by controlling an actuator that rotates the steering wheel 2. The acquisition unit 121 acquires the distance deviation z, the azimuth angle deviation θ, the vehicle speed V, the sideslip angle β, and the yaw rate again after the steering control unit 125 sets the steering angle to the target steering angle.

[0045] In this way, the vehicle control device 1 mounted on the vehicle A determines the target yaw rate r and the target steering angle δ based on the acquired information about the vehicle A, and rotates the steering wheel 2 of the vehicle A so that the determined target steering angle δ is achieved. The vehicle control device 1 can cause the vehicle A to travel along the target path B by repeatedly executing the process of acquiring information about the vehicle A and the process of rotating the steering wheel 2 while the vehicle A is traveling.

[0046] The effects of the control system S according to the present embodiment will be described with reference to FIGS. 4, 5, and 6. FIG. 4 is a schematic diagram of the target path B. As shown in FIG. 4, the target path B is a path with a large curvature in which straight lines and curves are mixed.

[0047] FIG. 5 is a schematic diagram of the traveling locus E1 of the vehicle according to the comparative example. The vehicle according to the comparative example traveled under the control of a control system different from the control system S according to the present embodiment (hereinafter referred to as "comparative example system"). The comparative example system controlled the vehicle to travel along the target path B. The portion filled with dark gray in the traveling locus E1 is a portion where the magnitude of the distance deviation z between the vehicle and the target path B is equal to or less than a predetermined value. Further, the portion filled with light gray in the traveling locus E1 is a portion where the magnitude of the distance deviation z is greater than the predetermined value. The predetermined value is, for example, 10 centimeters. As shown in FIG. 5, the traveling locus E1 has a portion filled with light gray (the portion surrounded by the broken line). That is, the vehicle traveling under the control of the comparative example system has a distance deviation z greater than 10 centimeters particularly at a location where a straight line and a curved road switch or on a curved road with a large curvature, and cannot follow the target path B.

[0048] FIG. 6 is a schematic diagram of the traveling locus E2 of the vehicle A traveling under the control of the control system S according to the present embodiment. As shown in FIG. 6, the traveling locus E2 is entirely filled with dark gray and there is no portion filled with light gray. In other words, the distance deviation z of the vehicle A traveling under the control of the control system S was always 10 centimeters or less.

[0049] The control system S can predict the sideslip angle β corresponding to the change in the yaw rate by using a prediction model based on the transfer function of the sideslip angle β with respect to the yaw rate. In other words, the prediction model is a model that predicts the change in the sideslip angle β when the yaw rate is changed. Then, the yaw rate that minimizes the evaluation function J including the distance deviation z, the azimuth angle deviation θ, and the yaw rate based on the prediction model as parameters is a yaw rate that reduces the distance deviation z and the azimuth angle deviation θ, and is a yaw rate that can generate a sideslip angle that turns the vehicle A along the target path B.

[0050] That is, by setting the yaw rate of the vehicle A to the target yaw rate r determined by the control system S, a sideslip angle β that enables the vehicle A to turn along the target path B is generated in the vehicle A, so that the vehicle A starts to turn along the target path B. As a result, since the vehicle A starts to travel along the target path B, the control system S can improve the followability of the vehicle A to the target path B with a large curvature.

[0051] [Process for Controlling Travel] FIG. 7 is a flowchart showing an example of a process for controlling the travel of the vehicle A. The process for controlling the travel of the vehicle A is executed during the travel of the vehicle A.

[0052] The acquisition unit 121 acquires information about the vehicle A (step S1). Specifically, the acquisition unit 121 acquires the distance deviation z between the path point D of the target path B of the vehicle A and the vehicle A, the azimuth deviation θ of the first azimuth angle ψ and the second azimuth angle φ, the sideslip angle β, and the yaw rate. Further, the acquisition unit 121 acquires the yaw inertia moment l z of the vehicle A, the weight m of the vehicle A, the first distance l from the center of gravity of the vehicle A to the axis of the front wheels of the vehicle A f of the vehicle A, the second distance l from the center of gravity point of the vehicle A to the axis of the rear wheels of the vehicle A r of the vehicle A, the vehicle length l of the vehicle A, and the rear wheel cornering stiffness K r of the vehicle A.

[0053] The generation unit 122 generates a prediction model for predicting the change in the sideslip angle β (step S2). Specifically, the generation unit 122 generates a continuous-time prediction model for predicting the changes in the distance deviation z, the azimuth deviation θ, the sideslip angle β, and the second azimuth angle φ based on the distance deviation z, the azimuth deviation θ, the vehicle speed V, the sideslip angle β, the yaw rate, the first azimuth angle ψ, and the transfer function represented by Equation (8). More specifically, the generation unit 122 generates a continuous-time state equation represented by Equation (9) as the prediction model.

[0054] The yaw rate determination unit 123 determines the target yaw rate that is represented by Expression (28) and minimizes the evaluation function J corresponding to the prediction model (step S3). Specifically, the yaw rate determination unit 123 includes the estimated distance deviation z, the estimated azimuth angle deviation, and the target yaw rate r predicted from the prediction model as parameters, and determines the target yaw rate that minimizes the evaluation function into which the acquired distance deviation z, azimuth angle deviation, and yaw rate are input as the target yaw rate r.

[0055] The steering angle determination unit 124 outputs a target steering angle δ corresponding to the target yaw rate r determined by the yaw rate determination unit 123 (step S4). Specifically, the steering angle determination unit 124 substitutes the yaw rate acquired by the acquisition unit 121 and the target yaw rate r determined by the yaw rate determination unit 123 into the relational expression for determining the target steering angle of the vehicle A, determines the target steering angle δ, and outputs the determined target steering angle δ to the steering control unit 125.

[0056] After the target steering angle δ is output, the acquisition unit 121 determines whether the vehicle A has stopped (step S5). If the vehicle A has stopped (Yes in step S5), the acquisition unit 121 ends the process of controlling the travel of the vehicle A. If the vehicle A is traveling (No in step S5), the acquisition unit 121 returns to step S1 to acquire information about the vehicle A. Note that when the stopped vehicle A starts to travel, the acquisition unit 121 starts the process of controlling the travel of the vehicle A.

[0057] [Effect of the control system S] As described above, the control system S acquires the distance deviation z between the path point D of the target path B of the vehicle A and the vehicle A, the azimuth deviation θ between the first azimuth angle ψ of the path point D and the second azimuth angle φ of the vehicle A, the yaw rate of the vehicle A, the vehicle speed V, and the sideslip angle β. Next, the control system S generates a transfer function that represents the relationship between the yaw rate and the sideslip angle β and outputs the sideslip angle β when the yaw rate is input. Subsequently, the control system S generates a prediction model that predicts the changes in each of the distance deviation z, the azimuth deviation θ, the sideslip angle β, and the second azimuth angle φ based on the generated transfer function, the distance deviation z, the azimuth deviation θ, the vehicle speed V, the sideslip angle β, the yaw rate, and the first azimuth angle ψ. Then, the control system S determines the target yaw rate r that minimizes the value of the evaluation function J into which the estimated distance deviation z, the estimated azimuth deviation θ, and the target yaw rate r predicted from the prediction model are included and the acquired distance deviation z, azimuth deviation θ, and yaw rate are input.

[0058] In this way, by using the prediction model based on the transfer function of the sideslip angle β with respect to the yaw rate, the control system S can predict the sideslip angle β according to the change in the yaw rate. In the evaluation function J that includes the distance deviation z, the azimuth deviation θ, and the yaw rate calculated from the prediction model as parameters, the change in the sideslip angle β due to the change in the yaw rate is included. Therefore, the yaw rate that minimizes the evaluation function J is the yaw rate that reduces the distance deviation z between the center of gravity point C of the vehicle A and the path point D due to the sideslip angle β. In other words, the control system S can determine the target yaw rate r that causes the sideslip angle β that turns the vehicle A along the target path B. As a result, since the vehicle A travels along the target path B with a large curvature, the control system S can improve the followability of the vehicle A to the target path B.

[0059] As described above, the present invention has been described using embodiments. However, the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of the gist. For example, all or part of the device can be configured by being functionally or physically dispersed and integrated in any unit. Also, new embodiments resulting from any combination of a plurality of embodiments are included in the embodiments of the present invention. The effects of the new embodiments resulting from the combination have the effects of the original embodiments combined.

Explanation of Reference Numerals

[0060] 1 Vehicle control device 11 Storage unit 12 Control unit 121 Acquisition unit 122 Generation unit 123 Yaw rate determination unit 124 Steering angle determination unit 125 Steering control unit A Vehicle

Claims

1. An acquisition unit that acquires a distance deviation between a path point of a target path of a vehicle and the vehicle, an azimuth deviation between a first azimuth angle of the path point and a second azimuth angle of the vehicle, a yaw rate of the vehicle, a vehicle speed of the vehicle, and a sideslip angle of the vehicle; A generation unit that generates a prediction model for predicting changes in each of the distance deviation, the azimuth deviation, the sideslip angle, and the second azimuth angle based on the distance deviation, the azimuth deviation, the vehicle speed, the sideslip angle, the yaw rate, and a transfer function representing the relationship between the yaw rate and the sideslip angle; A yaw rate determination unit that determines the target yaw rate as the target yaw rate by minimizing the value of an evaluation function into which the estimated distance deviation, the estimated azimuth deviation, and the target yaw rate predicted from the prediction model are input, and the acquired distance deviation, azimuth deviation, and yaw rate are input; A control system having the above.

2. The generation unit Generates the continuous-time prediction model, By discretizing the generated continuous-time prediction model, a discrete-time prediction model for predicting changes in each of the distance deviation, the azimuth deviation, the sideslip angle, and the second azimuth angle one unit time ahead is generated. The control system according to claim 1.

3. The transfer function is a function corresponding to a canonical response model that represents the relationship between the yaw rate and the second azimuth angle and outputs the amount of change in the second azimuth angle when the yaw rate is input. The control system according to claim 2.

4. It has a steering angle determination unit that determines the target steering angle of the vehicle when the yaw rate and the determined target yaw rate are input, The yaw rate determination unit notifies the target yaw rate to the steering angle determination unit. The control system according to claim 1.

5. It has a steering control unit that operates the steering wheel of the vehicle to set the steering angle of the vehicle to the target steering angle, The acquisition unit acquires the distance deviation, the azimuth deviation, the vehicle speed, the sideslip angle, and the yaw rate after the steering control unit sets the steering angle to the target steering angle. The control system according to claim 4.

6. The acquisition unit acquires the yaw moment of inertia of the vehicle, the weight of the vehicle, a first distance from the center of gravity of the vehicle to the axis of the front wheels of the vehicle, a second distance from the center of gravity point of the vehicle to the axis of the rear wheels of the vehicle, the vehicle length of the vehicle, the rear wheel cornering stiffness, and the longitudinal vehicle speed in the traveling direction of the vehicle as the vehicle speed. The transfer function is the yaw moment of inertia, the product of the weight, the longitudinal vehicle speed, and the first distance, the ratio of the product of the rear wheel cornering stiffness, the second distance, and the vehicle length to the longitudinal vehicle speed, the second product of the weight, the longitudinal vehicle speed, and the first distance, the third product of the rear wheel cornering stiffness and the vehicle length, represented by the control system according to any one of claims 1 to 5. **Claim 7** executed by a processor mounted on a vehicle, a step of obtaining a distance deviation between a path point of a target path of the vehicle and the vehicle, an azimuth deviation between a first azimuth angle of the path point and a second azimuth angle of the vehicle, a yaw rate of the vehicle, a vehicle speed of the vehicle, and a sideslip angle of the vehicle; a step of generating a prediction model that predicts changes in each of the distance deviation, the azimuth deviation, the sideslip angle, and the second azimuth angle based on the distance deviation, the azimuth deviation, the vehicle speed, the sideslip angle, the yaw rate, and the first azimuth angle, and a transfer function that represents the relationship between the yaw rate and the sideslip angle and outputs the sideslip angle when the yaw rate is input; a step of determining a target yaw rate as a target yaw rate that minimizes a value of an evaluation function in which an estimated distance deviation, an estimated azimuth deviation, and a target yaw rate predicted from the prediction model are included as parameters and the obtained distance deviation, azimuth deviation, and yaw rate are input; A control method having

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