A game equilibrium control system for coordinating adaptive cruise control and vehicle body stability

Abstract

This invention discloses a game-theoretic equilibrium control system for coordinating adaptive cruise control and vehicle stability, comprising an information acquisition module, a vehicle state assessment module, a system decision-making module, and an execution module. The information acquisition module collects information such as driving scenarios, vehicle state, and vehicle static conditions. The vehicle state assessment module uses the information acquired by the information acquisition module to determine the current vehicle control mode, which includes cruise control, adaptive cruise control, Stackelberg game-theoretic equilibrium control, and vehicle stability control. The system decision-making module establishes a vehicle control model and uses model predictive control theory to calculate the optimal control input for the vehicle's current control mode. The execution module obtains the desired longitudinal tire force based on the decision calculated by the system decision-making module, thereby improving vehicle stability during adaptive cruise control.

Description

Technical Field

[0001] This invention relates to the field of automotive intelligent interaction technology and vehicle autonomous driving safety technology. More specifically, it is a game-theoretic equilibrium control system that coordinates adaptive cruise control and vehicle stability, which is used to improve the control objectives and decision conflicts between the adaptive cruise control system and the vehicle stability control system during adaptive cruise, thereby improving vehicle driving safety. Background Technology

[0002] With the development of various intelligent driving assistance technologies, the new challenges of dynamic stability in autonomous driving have become another research focus and hot topic. When vehicles are performing longitudinal dynamic control, they are prone to skidding or rollover in situations with extremely poor road conditions, such as split-level roads, leading to serious injuries and economic losses. As a key factor in the safe and stable operation of vehicles, the vehicle stability control system plays a crucial role. However, the control decisions of the vehicle stability control system can significantly impact the performance of the adaptive cruise control system. Therefore, this invention proposes a game-theoretic equilibrium control system that coordinates adaptive cruise control and vehicle stability, improving the control objectives and decision-making conflicts between the vehicle stability control system and the adaptive cruise control system, thereby enhancing vehicle safety during actual driving. Summary of the Invention

[0003] The purpose of this invention is to provide a game-theoretic balance control system that coordinates adaptive cruise control and vehicle stability to solve the above-mentioned technical problems.

[0004] To solve the above-mentioned technical problems, the specific technical solution of the present invention is as follows:

[0005] A game-theoretic balance control system that coordinates adaptive cruise control and vehicle stability includes an information acquisition module, a vehicle status assessment module, a system decision-making module, and an execution module.

[0006] The information acquisition module includes a driving scene acquisition unit, a vehicle status information acquisition unit, and a vehicle information database. The driving scene information acquisition unit includes a binocular camera, a millimeter-wave radar, and a lidar. These are respectively installed below the rearview mirror, in the middle of the front bumper, and above the windshield. They are used to acquire information about the vehicle ahead, surrounding vehicles, and the scene. The information about the vehicle ahead includes the longitudinal speed and acceleration of the vehicle ahead, the relative distance between the vehicle and the vehicle ahead, and the relative speed between the vehicle and the vehicle ahead. The information about the surrounding vehicles and the scene includes the road surface level, the vehicle density level of the current lane and surrounding lanes, and the weather condition level. The vehicle status information acquisition unit includes four photoelectric wheel speed sensors and an inertial measurement unit. The four photoelectric wheel speed sensors are respectively installed on the four wheel hubs, and the inertial measurement unit is installed in the center of the vehicle chassis. It is used to acquire and estimate wheel speed, vehicle longitudinal speed, vehicle body roll angle, vehicle longitudinal acceleration, center of gravity sideslip angle, and unsprung mass roll angle.

[0007] The vehicle status assessment module uses driving scenario information and vehicle status information collected by the information acquisition module to determine the current vehicle control mode. The vehicle control modes include cruise control mode, adaptive cruise control mode, Stackelberg game equilibrium control mode, and vehicle stability control mode. The cruise control mode includes level one, level two, and level three cruise control modes, and determines the level of cruise control the vehicle is in by calculating a cruise control factor. The adaptive cruise control mode includes level one, level two, and level three adaptive cruise control modes, and determines the level of adaptive cruise control the vehicle is in by calculating an adaptive cruise control factor. The vehicle stability control mode includes level one and level two vehicle stability control modes, and determines whether the vehicle is in a Stackelberg game equilibrium control mode or a vehicle stability control mode by calculating a vehicle stability factor.

[0008] If there are no vehicles ahead in the current lane, the vehicle status assessment module determines that the vehicle has entered cruise control mode and calculates the cruise control factor. To determine the vehicle's cruise control mode, cruise control factor. It can be calculated using the following formula:

[0009] ,

[0010] In the formula, , , , These are weighting coefficients. , Indicates the road surface grade; when driving on slippery asphalt or concrete roads. When driving on dry asphalt or cement roads, ; This indicates the vehicle density level of the current lane and surrounding lanes; its value depends on the vehicle density levels of both the current lane and the surrounding lanes. In the formula, , These are weighting coefficients. , This indicates the current lane vehicle density level, categorized into low density, low-medium density, medium density, and medium-high density levels based on hourly traffic volume. When hourly traffic volume is less than 100 vehicles, the current lane vehicle density level is low density. When the hourly traffic flow is between 100 and 200 vehicles, the current lane's vehicle density level is considered low to medium. When the hourly traffic flow is between 200 and 300 vehicles, the current lane's vehicle density level is medium density. When the hourly traffic flow is between 300 and 400 vehicles, the current lane's vehicle density level is medium to high density. ; This indicates the vehicle density level of the surrounding lanes, which is also divided into low density, low-medium density, medium density, and medium-high density levels based on hourly traffic flow. When the hourly traffic flow is less than 100 vehicles, the vehicle density level of the surrounding lanes is low density. When the hourly traffic volume is between 100 and 200 vehicles, the vehicle density level of the surrounding lanes is low to medium. When the hourly traffic volume is between 200 and 300 vehicles, the vehicle density level of the surrounding lanes is medium density. When the hourly traffic volume is between 300 and 400 vehicles, the vehicle density level of the surrounding lanes is medium to high density. ; This indicates the weather condition level, and its value depends on the wind force level and weather phenomena. In the formula, , These are weighting coefficients. , This indicates the wind force level. When the wind force is level 0-2, When the wind force is 3-4, When the wind force is 5-6, , Indicates a weather phenomenon, on a sunny day. On cloudy days, On days with light rain or slight haze, During moderate rain or moderate smog, ; This indicates the vehicle's braking ability level, and its value depends on the vehicle's braking distance from 100 km / h. When the vehicle's braking distance from 100 km / h is less than 35 meters... When the braking distance of a vehicle from 100 km / h is greater than 35 meters but less than 50 meters, When the braking distance of a vehicle from 100 km / h is greater than 50 meters but less than 100 meters, When the braking distance of a vehicle from 100 km / h exceeds 100 meters, ; Cruise control factor The factors to consider include: road surface conditions (icy or snowy); traffic flow in the current or surrounding lanes between 400 and 600 vehicles per hour; wind speeds of 7-12; heavy rain; severe fog or snow. In other driving scenarios, .

[0011] If cruise control factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 cruise control mode. If the cruise control factor... satisfy The vehicle status assessment module determines that the vehicle is in level two cruise control mode. If the cruise control factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 3 cruise control mode. If the cruise control factor... The vehicle status assessment module forces the vehicle to exit cruise control mode; when the vehicle is in Level 1 cruise control mode, the cruise speed... When the vehicle is in Level 2 cruise control mode, the cruising speed is... When the vehicle is in Level 3 cruise control mode, the cruising speed is... ,in It is a cruise control adjustment factor that the driver can select. It is divided into five levels: A, B, C, D, and E, with corresponding values ​​of 1, 0.5, 0, -0.5, and 1, respectively.

[0012] If there is a trackable vehicle ahead in the current lane, the vehicle status assessment module determines that the vehicle has entered adaptive cruise mode and calculates an adaptive cruise factor to determine the adaptive cruise mode in which the vehicle is in. The adaptive cruise factor can be calculated according to the following formula:

[0013]

[0014] In the formula, , , , These are weighting coefficients. , , , The meaning is the same as above. This indicates the vehicle's performance level, and its value depends on the vehicle's 0-100km / h acceleration time and 100km / h braking distance. In the formula, , These are weighting coefficients. , This indicates the vehicle's 0-100km / h acceleration time. When the vehicle's 0-100km / h acceleration time is less than 5 seconds, When a vehicle's 0-100km / h acceleration time is greater than 5 seconds but less than 12 seconds, When a vehicle's 0-100km / h acceleration time is greater than 12 seconds, , This indicates the vehicle's braking distance at 100 km / h, and its meaning is the same as described above. Adaptive cruise factor The factors to consider include: road surface conditions (icy or snowy); traffic flow in the current or surrounding lanes between 400 and 600 vehicles per hour; wind speeds of 7-12; heavy rain; severe fog or snow. In other driving scenarios, .

[0015] If adaptive cruise factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 adaptive cruise control mode. If the adaptive cruise factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 2 adaptive cruise control mode. If the adaptive cruise factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 3 adaptive cruise control mode. If the adaptive cruise factor... The vehicle status assessment module forces the vehicle to exit adaptive cruise control mode.

[0016] The system status assessment module calculates the vehicle stability factor. To determine whether the vehicle is in Stackelberg game equilibrium control mode or vehicle stability control mode, the vehicle stability factor is used. It can be calculated using the following formula:

[0017]

[0018] In the formula, , , These are weighting coefficients. , Vehicle stability factor The trade-off factors Vehicle stability factor Regulatory factors, The initial vehicle body stability factor is calculated. This is the final normalized vehicle body stability factor. This indicates the vehicle's sideslip angle, measured in degrees (deg). This indicates the side tilt angle of the carriage, measured in degrees (deg). This indicates the unsprung mass tilt angle, expressed in deg.

[0019] Vehicle stability factor satisfy The vehicle status assessment module determines whether the vehicle is in cruise control mode or adaptive cruise control mode; if the vehicle stability factor... satisfy The vehicle state assessment module determines that the vehicle is in a Stackelberg game equilibrium control mode; if the vehicle stability factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 vehicle stability control mode; if the vehicle stability factor... satisfy The vehicle status assessment module determines that the vehicle is in the secondary vehicle stability control mode.

[0020] When the vehicle is in adaptive cruise control mode, the system decision module establishes a vehicle adaptive cruise model and uses a model predictive control algorithm to calculate the optimal longitudinal acceleration and deceleration. The non-negative weight matrix in the model predictive control algorithm... Based on adaptive cruise factor If the vehicle is in Level 1 adaptive cruise control mode, that is... , , If the vehicle is in Level 2 adaptive cruise control mode, that is... , , If the vehicle is in Level 3 adaptive cruise control mode, that is... , , In the formula, , , , , , The weighting coefficients are the weighting coefficients of the non-negative weight matrix. , , and Non-negative weight matrix The trade-off factors.

[0021] When the vehicle is in Stackelberg game equilibrium control mode, the system decision module establishes a game control model for adaptive cruise control and vehicle stability control. It uses a model predictive control algorithm to calculate the Stackelberg game equilibrium between adaptive cruise control and vehicle stability control, i.e., to calculate the optimal longitudinal acceleration / deceleration and the optimal longitudinal tire force. The algorithm includes a non-negative weight matrix. and Based on adaptive cruise factor and vehicle stability factor Obtain , , , , In the formula, , , , , Non-negative weight matrix and The weighting coefficients, , , Non-negative weight matrix The trade-off factors.

[0022] When the vehicle is in vehicle stability control mode, the system decision module establishes a vehicle stability control model and uses a model predictive control algorithm to calculate the optimal longitudinal tire force. The non-negative weight matrix in the model predictive control algorithm... According to vehicle stability factor If the vehicle is in Level 1 vehicle stability control mode, that is... , , , If the vehicle is in Level 2 vehicle stability control mode, i.e. , , , In the formula, , , , , , Non-negative weight matrix The weighting coefficients, , , .

[0023] The execution module obtains the final expected tire force based on the decision calculated by the system decision module, thereby achieving safe driving of the vehicle.

[0024] When the vehicle is in adaptive cruise control mode, the system decision module includes the following:

[0025] S1.1 Establish a vehicle adaptive cruise control model and discretize it.

[0026]

[0027] In the formula, It is the state vector of the vehicle's adaptive cruise control system. , This represents the difference between the actual distance between the vehicle and the vehicle ahead detected by the sensors during adaptive cruise control, and the desired distance, expressed in meters (m). This indicates the speed difference between the vehicle and the target vehicle ahead during adaptive cruise control, expressed in m / s. This represents the vehicle's actual longitudinal acceleration, measured in m / s². 2 , , and This is the coefficient matrix of the vehicle's adaptive cruise control system. This is the input vector for the vehicle's adaptive cruise control system. , This represents the desired deceleration, expressed in m / s². 2 , This is the interference input vector for the vehicle's adaptive cruise control system. , The time distance between the front of the train is expressed in seconds (s). It is the delay constant;

[0028] Using Ts as a sample, the vehicle adaptive cruise control model is discretized to obtain the vehicle adaptive cruise discrete incremental model:

[0029]

[0030] In the formula,

[0031]

[0032] S1.2 Calculate the optimal longitudinal acceleration and deceleration using the model predictive control algorithm:

[0033] First, the vehicle's adaptive cruise control system control output is designed based on the requirements of adaptive cruise following other vehicles. ,

[0034]

[0035] In the formula,

[0036] Secondly, based on the control output of the vehicle's adaptive cruise control system Design a cost function for a vehicle adaptive cruise control system. ,

[0037]

[0038] In the formula,

[0039]

[0040]

[0041]

[0042] Next, the cost function of the vehicle's adaptive cruise control system will be... Rewritten as:

[0043]

[0044] In the formula,

[0045] Minimize the cost function of the vehicle's adaptive cruise control system Equivalent to the following formula:

[0046]

[0047] Finding the extreme value of this expression, we get:

[0048]

[0049] Therefore, we obtain expression:

[0050]

[0051] Furthermore, regarding the cost function Find the second derivative:

[0052]

[0053] Therefore, the optimal solution for the vehicle adaptive cruise control system is obtained. and optimal longitudinal acceleration and deceleration , :

[0054]

[0055] .

[0056] When the vehicle is in Stackelberg game equilibrium control mode, the system decision module includes the following:

[0057] S2.1 Establish a Stackelberg game equilibrium control model for coordinated adaptive cruise control and vehicle stability, and discretize it.

[0058] First, establish a vehicle body stability control model.

[0059]

[0060]

[0061]

[0062] In the formula, It is the state vector of the vehicle body stability control system. , This indicates the vehicle's yaw angle, measured in degrees (deg). and This is the coefficient matrix of the vehicle body stability control system. This is the input vector for the vehicle stability control system. , , , , These represent the longitudinal tire forces of the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, in N. This indicates the steering angle of the vehicle's front wheels, measured in degrees (deg). This indicates the total vehicle weight, expressed in kg. This indicates the longitudinal speed of the vehicle, expressed in m / s. This indicates the sprung mass, expressed in kg. This represents the height from the center of mass to the center of tilt, in meters (m). and These represent the distances from the vehicle's center of gravity to the front and rear axles, respectively, in meters (m). This indicates the vehicle's track width, in meters (m). This represents the yaw inertia of the entire vehicle, expressed in kgm. 2 , This represents the suspension roll damping coefficient, expressed in kN / rad. This indicates the suspension roll stiffness, expressed in Nm / rad. This represents the yaw-roll inertia product of a vehicle, measured in kg / m. 2 , This represents the vehicle's moment of inertia during roll, measured in kgm. 2 , This indicates the distance from the center of the roll to the ground, in meters (m). This indicates the unsprung mass, expressed in kg. This indicates the height of the unsprung mass's center of gravity, in meters (m). This represents the unsprung mass tilting stiffness, expressed in Nm / rad.

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071] Secondly, by combining the vehicle body stability control model and the vehicle adaptive cruise control model, a Stackelberg game equilibrium control model for coordinating adaptive cruise and vehicle body stability is obtained:

[0072]

[0073]

[0074] In the formula, It is the state vector of the Stackelberg game equilibrium control system that coordinates adaptive cruise control and vehicle stability. , , , and The Stackelberg game equilibrium control system coefficient matrix is ​​used to coordinate adaptive cruise control and vehicle stability. The Stackelberg game-theoretic equilibrium control system uses an interference input vector to coordinate adaptive cruise control and vehicle stability. ;

[0075] Then, using Ts as a sample, the Stackelberg game equilibrium control model of coordinated adaptive cruise control and vehicle stability is discretized to obtain the Stackelberg game equilibrium discrete incremental model of coordinated adaptive cruise control and vehicle stability:

[0076]

[0077] In the formula,

[0078]

[0079] S2.2 Calculate the Stackelberg game equilibrium between adaptive cruise control and vehicle stability control using model predictive control algorithms, including the following:

[0080] First, the control output of the vehicle's adaptive cruise control system is designed based on the requirements of adaptive cruise control and vehicle stability control. and vehicle stability control system control output The mathematical expression is as follows:

[0081]

[0082] In the formula,

[0083] Based on the control output of the vehicle adaptive cruise control system Control output with vehicle body stability control system Define their respective cost functions.

[0084]

[0085]

[0086] In the formula,

[0087]

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094] Next, the cost function of the vehicle's adaptive cruise control system will be... Rewritten as:

[0095]

[0096] In the formula,

[0097] Minimize the cost function of the vehicle's adaptive cruise control system Equivalent to the following formula:

[0098]

[0099] Finding the extreme value of this expression, we get:

[0100]

[0101] Therefore, we obtain expression:

[0102]

[0103] Furthermore, regarding the cost function Find the second derivative:

[0104]

[0105] Therefore, the optimal solution for the vehicle adaptive cruise control system is obtained. , :

[0106]

[0107] Similarly, the cost function of the vehicle body stability control system rewrite:

[0108]

[0109] In the formula,

[0110] Minimize the cost function of the vehicle stability control system Equivalent to the following formula:

[0111]

[0112] Finding the extreme value of this expression, we get:

[0113]

[0114] Therefore, we get expression:

[0115]

[0116] Furthermore, regarding the cost function Find the second derivative:

[0117]

[0118] This yields the optimal solution for the vehicle stability control system. , :

[0119]

[0120] Substitute the optimal solution for the vehicle's adaptive cruise control system ,

[0121]

[0122] The optimal solution for vehicle stability control system Substitute the optimal solution for the vehicle's adaptive cruise control system Ultimately, the Stackelberg game equilibrium solution for coordinating adaptive cruise control and vehicle stability is obtained. and The single-step optimal solution of the vehicle body stability control system Single-step optimal solution of vehicle adaptive cruise control system The relationship can be expressed by the following formula:

[0123]

[0124] In the formula, and These represent the mapping rules between the vehicle stability control system and the vehicle adaptive cruise control system, respectively.

[0125] When the vehicle is in vehicle stability control mode, the system decision module includes the following:

[0126] S3.1 Discretize the vehicle body stability control model using Ts as a sample to obtain the discrete incremental model of vehicle body stability control:

[0127]

[0128] In the formula,

[0129]

[0130] S3.2 Calculate the optimal longitudinal tire force using the model predictive control algorithm:

[0131] First, the control output of the vehicle stability control system is designed based on the vehicle stability control requirements. ,

[0132]

[0133] In the formula, ,

[0134] Secondly, based on the control output of the vehicle body stability control system Cost function for designing a vehicle body stability control system ,

[0135]

[0136] In the formula,

[0137]

[0138]

[0139] Next, the cost function of the vehicle stability control system is... Rewritten as:

[0140]

[0141] In the formula,

[0142] Minimize the cost function of the vehicle body stability control system Equivalent to the following formula:

[0143]

[0144] Finding the extreme value of this expression, we get:

[0145]

[0146] Therefore, we obtain expression:

[0147]

[0148] Furthermore, regarding the cost function Find the second derivative:

[0149]

[0150] This yields the optimal solution for the vehicle stability control system. and optimal tire longitudinal force , :

[0151]

[0152] .

[0153] The execution module includes the following:

[0154] The expected longitudinal tire force calculated based on the system decision module With the desired longitudinal acceleration Calculate the final expected longitudinal force for each wheel. ,in, , ,

[0155]

[0156] In the formula, , , , These represent the final expected longitudinal forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0157] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0158] 1. The Stackelberg game equilibrium control system designed in this invention can coordinate the decisions of the adaptive cruise control system and the vehicle stability control system, and reduce the decision conflict caused by the different control tasks when the adaptive cruise control system and the vehicle stability system work simultaneously.

[0159] 2. The Stackelberg game equilibrium control system designed in this invention uses driving scenario information and vehicle state information to determine the vehicle's control mode, ensuring that the vehicle can efficiently complete control tasks under different states and driving scenarios, thereby improving the system's operating range.

[0160] 3. This invention comprehensively considers driving scenario information and vehicle status information, which helps to improve the safety of vehicles driving under different driving conditions. Attached Figure Description

[0161] The present invention will be further described below with reference to the accompanying drawings:

[0162] Figure 1 This is a system framework diagram of a game-theoretic equilibrium control system for coordinating adaptive cruise control and vehicle stability according to the present invention.

[0163] Figure 2 This is a schematic diagram illustrating the judgment process of the vehicle condition assessment module of the present invention. Detailed Implementation

[0164] The present invention will be further described in detail below with reference to the accompanying drawings. The following embodiments are only used to illustrate the technical solution of the present invention more clearly, and are therefore only examples and should not be used to limit the scope of protection of the present invention.

[0165] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application should have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0166] like Figure 1 As shown, this embodiment of the invention provides a game-theoretic balance control system for coordinating adaptive cruise control and vehicle stability, comprising the following modules:

[0167] The system comprises an information collection module, a vehicle status assessment module, a system decision-making module, and an execution module.

[0168] The information acquisition module includes a driving scene acquisition unit, a vehicle status information acquisition unit, and a vehicle information database. The driving scene information acquisition unit includes a binocular camera, a millimeter-wave radar, and a lidar. These are respectively installed below the rearview mirror, in the middle of the front bumper, and above the windshield. They are used to acquire information about the vehicle ahead, surrounding vehicles, and the scene. The information about the vehicle ahead includes the longitudinal speed and acceleration of the vehicle ahead, the relative distance between the vehicle and the vehicle ahead, and the relative speed between the vehicle and the vehicle ahead. The information about the surrounding vehicles and the scene includes the road surface level, the vehicle density level of the current lane and surrounding lanes, and the weather condition level. The vehicle status information acquisition unit includes four photoelectric wheel speed sensors and an inertial measurement unit. The four photoelectric wheel speed sensors are respectively installed on the four wheel hubs, and the inertial measurement unit is installed in the center of the vehicle chassis. It is used to acquire and estimate wheel speed, vehicle longitudinal speed, vehicle body roll angle, vehicle longitudinal acceleration, center of gravity sideslip angle, and unsprung mass roll angle.

[0169] like Figure 2 As shown, the vehicle state assessment module uses driving scenario information and vehicle state information collected by the information acquisition module to determine the current vehicle control mode. The vehicle control modes include cruise control mode, adaptive cruise control mode, Stackelberg game equilibrium control mode, and vehicle stability control mode. The cruise control mode includes level one cruise control mode, level two cruise control mode, and level three cruise control mode, and determines the level of cruise control mode the vehicle is in by calculating a cruise control factor. The adaptive cruise control mode includes level one adaptive cruise control mode, level two adaptive cruise control mode, and level three adaptive cruise control mode, and determines the level of adaptive cruise control mode the vehicle is in by calculating an adaptive cruise control factor. The vehicle stability control mode includes level one vehicle stability control mode and level two vehicle stability control mode, and determines whether the vehicle is in a Stackelberg game equilibrium control mode or a vehicle stability control mode by calculating a vehicle stability factor.

[0170] If there are no vehicles ahead in the current lane, the vehicle status assessment module determines that the vehicle has entered cruise control mode and calculates the cruise control factor. To determine the vehicle's cruise control mode, cruise control factor. It can be calculated using the following formula:

[0171] ,

[0172] In the formula, , , , These are weighting coefficients. , Indicates the road surface grade; when driving on slippery asphalt or concrete roads. When driving on dry asphalt or cement roads, ; This indicates the vehicle density level of the current lane and surrounding lanes; its value depends on the vehicle density levels of both the current lane and the surrounding lanes. In the formula, , These are weighting coefficients. , This indicates the current lane vehicle density level, categorized into low density, low-medium density, medium density, and medium-high density levels based on hourly traffic volume. When hourly traffic volume is less than 100 vehicles, the current lane vehicle density level is low density. When the hourly traffic flow is between 100 and 200 vehicles, the current lane's vehicle density level is considered low to medium. When the hourly traffic flow is between 200 and 300 vehicles, the current lane's vehicle density level is medium density. When the hourly traffic flow is between 300 and 400 vehicles, the current lane's vehicle density level is medium to high density. ; This indicates the vehicle density level of the surrounding lanes, which is also divided into low density, low-medium density, medium density, and medium-high density levels based on hourly traffic flow. When the hourly traffic flow is less than 100 vehicles, the vehicle density level of the surrounding lanes is low density. When the hourly traffic volume is between 100 and 200 vehicles, the vehicle density level of the surrounding lanes is low to medium. When the hourly traffic volume is between 200 and 300 vehicles, the vehicle density level of the surrounding lanes is medium density. When the hourly traffic volume is between 300 and 400 vehicles, the vehicle density level of the surrounding lanes is medium to high density. ; This indicates the weather condition level, and its value depends on the wind force level and weather phenomena. In the formula, , These are weighting coefficients. , This indicates the wind force level. When the wind force is level 0-2, When the wind force is 3-4, When the wind force is 5-6, , Indicates a weather phenomenon, on a sunny day. On cloudy days, On days with light rain or slight haze, During moderate rain or moderate smog, ; This indicates the vehicle's braking ability level, and its value depends on the vehicle's braking distance from 100 km / h. When the vehicle's braking distance from 100 km / h is less than 35 meters... When the braking distance of a vehicle from 100 km / h is greater than 35 meters but less than 50 meters, When the braking distance of a vehicle from 100 km / h is greater than 50 meters but less than 100 meters, When the braking distance of a vehicle from 100 km / h exceeds 100 meters, ; Cruise control factor The factors to consider include: road surface conditions (icy or snowy); traffic flow in the current or surrounding lanes between 400 and 600 vehicles per hour; wind speeds of 7-12; heavy rain; severe fog or snow. In other driving scenarios, .

[0173] If cruise control factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 cruise control mode. If the cruise control factor... satisfy The vehicle status assessment module determines that the vehicle is in level two cruise control mode. If the cruise control factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 3 cruise control mode. If the cruise control factor... The vehicle status assessment module forces the vehicle to exit cruise control mode; when the vehicle is in Level 1 cruise control mode, the cruise speed... When the vehicle is in Level 2 cruise control mode, the cruising speed is... When the vehicle is in Level 3 cruise control mode, the cruising speed is... ,in It is a cruise control adjustment factor that the driver can select. It is divided into five levels: A, B, C, D, and E, with corresponding values ​​of 1, 0.5, 0, -0.5, and 1, respectively.

[0174] If there is a trackable vehicle ahead in the current lane, the vehicle status assessment module determines that the vehicle has entered adaptive cruise mode and calculates an adaptive cruise factor to determine the adaptive cruise mode in which the vehicle is in. The adaptive cruise factor can be calculated according to the following formula:

[0175]

[0176] In the formula, , , , These are weighting coefficients. , , , The meaning is the same as above. This indicates the vehicle's performance level, and its value depends on the vehicle's 0-100km / h acceleration time and 100km / h braking distance. In the formula, , These are weighting coefficients. , This indicates the vehicle's 0-100km / h acceleration time. When the vehicle's 0-100km / h acceleration time is less than 5 seconds, When a vehicle's 0-100km / h acceleration time is greater than 5 seconds but less than 12 seconds, When a vehicle's 0-100km / h acceleration time is greater than 12 seconds, , This indicates the vehicle's braking distance at 100 km / h, and its meaning is the same as described above. Adaptive cruise factor The factors to consider include: road surface conditions (icy or snowy); traffic flow in the current or surrounding lanes between 400 and 600 vehicles per hour; wind speeds of 7-12; heavy rain; severe fog or snow. In other driving scenarios, .

[0177] If adaptive cruise factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 adaptive cruise control mode. If the adaptive cruise factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 2 adaptive cruise control mode. If the adaptive cruise factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 3 adaptive cruise control mode. If the adaptive cruise factor... The vehicle status assessment module forces the vehicle to exit adaptive cruise control mode.

[0178] The system status assessment module calculates the vehicle stability factor. To determine whether the vehicle is in Stackelberg game equilibrium control mode or vehicle stability control mode, the vehicle stability factor is used. It can be calculated using the following formula:

[0179]

[0180] In the formula, , , These are weighting coefficients. , Vehicle stability factor The trade-off factors Vehicle stability factor Regulatory factors, The initial vehicle body stability factor is calculated. This is the final normalized vehicle body stability factor. This indicates the vehicle's sideslip angle, measured in degrees (deg). This indicates the side tilt angle of the carriage, measured in degrees (deg). This indicates the unsprung mass tilt angle, expressed in deg.

[0181] If vehicle stability factor satisfy The vehicle status assessment module determines whether the vehicle is in cruise control mode or adaptive cruise control mode; if the vehicle stability factor... satisfy The vehicle state assessment module determines that the vehicle is in a Stackelberg game equilibrium control mode; if the vehicle stability factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 vehicle stability control mode; if the vehicle stability factor... satisfy The vehicle status assessment module determines that the vehicle is in the secondary vehicle stability control mode.

[0182] When the vehicle is in adaptive cruise control mode, the system decision module establishes a vehicle adaptive cruise model and uses a model predictive control algorithm to calculate the optimal longitudinal acceleration and deceleration. The non-negative weight matrix in the model predictive control algorithm... Based on adaptive cruise factor If the vehicle is in Level 1 adaptive cruise control mode, that is... , , If the vehicle is in Level 2 adaptive cruise control mode, that is... , , If the vehicle is in Level 3 adaptive cruise control mode, that is... , , In the formula, , , , , , The weighting coefficients are the weighting coefficients of the non-negative weight matrix. , , and Non-negative weight matrix The trade-off factors.

[0183] When the vehicle is in Stackelberg game equilibrium control mode, the system decision module establishes a game control model for adaptive cruise control and vehicle stability control. It uses a model predictive control algorithm to calculate the Stackelberg game equilibrium between adaptive cruise control and vehicle stability control, i.e., to calculate the optimal longitudinal acceleration / deceleration and the optimal longitudinal tire force. The algorithm includes a non-negative weight matrix. and Based on adaptive cruise factor and vehicle stability factor Obtain , , , , In the formula, , , , , Non-negative weight matrix and The weighting coefficients, , , Non-negative weight matrix The trade-off factors.

[0184] When the vehicle is in vehicle stability control mode, the system decision module establishes a vehicle stability control model and uses a model predictive control algorithm to calculate the optimal longitudinal tire force. The non-negative weight matrix in the model predictive control algorithm... According to vehicle stability factor If the vehicle is in Level 1 vehicle stability control mode, that is... , , , If the vehicle is in Level 2 vehicle stability control mode, i.e. , , , In the formula, , , , , , Non-negative weight matrix The weighting coefficients, , , .

[0185] The execution module obtains the final expected tire force based on the decision calculated by the system decision module, thereby achieving safe driving of the vehicle.

[0186] When the vehicle is in adaptive cruise control mode, the system decision module includes the following:

[0187] S1.1 Establish a vehicle adaptive cruise control model and discretize it.

[0188]

[0189] In the formula, It is the state vector of the vehicle's adaptive cruise control system. , This represents the difference between the actual distance between the vehicle and the vehicle ahead detected by the sensors during adaptive cruise control, and the desired distance, expressed in meters (m). This indicates the speed difference between the vehicle and the target vehicle ahead during adaptive cruise control, expressed in m / s. This represents the vehicle's actual longitudinal acceleration, measured in m / s². 2 , , and This is the coefficient matrix of the vehicle's adaptive cruise control system. This is the input vector for the vehicle's adaptive cruise control system. , This represents the desired deceleration, expressed in m / s². 2 , This is the interference input vector for the vehicle's adaptive cruise control system. , The time distance between the front of the train is expressed in seconds (s). It is the delay constant;

[0190] Using Ts as a sample, the vehicle adaptive cruise control model is discretized to obtain the vehicle adaptive cruise discrete incremental model:

[0191]

[0192] In the formula,

[0193]

[0194] S1.2 Calculate the optimal longitudinal acceleration and deceleration using the model predictive control algorithm:

[0195] First, the vehicle's adaptive cruise control system control output is designed based on the requirements of adaptive cruise following other vehicles. ,

[0196]

[0197] In the formula,

[0198] Secondly, based on the control output of the vehicle's adaptive cruise control system Design a cost function for a vehicle adaptive cruise control system. ,

[0199]

[0200] In the formula,

[0201]

[0202]

[0203]

[0204] Next, the cost function of the vehicle's adaptive cruise control system will be... Rewritten as:

[0205]

[0206] In the formula,

[0207] Minimize the cost function of the vehicle's adaptive cruise control system Equivalent to the following formula:

[0208]

[0209] Finding the extreme value of this expression, we get:

[0210]

[0211] Therefore, we obtain expression:

[0212]

[0213] Furthermore, regarding the cost function Find the second derivative:

[0214]

[0215] Therefore, the optimal solution for the vehicle adaptive cruise control system is obtained. and optimal longitudinal acceleration and deceleration , :

[0216]

[0217] .

[0218] When the vehicle is in Stackelberg game equilibrium control mode, the system decision module includes the following:

[0219] S2.1 Establish a Stackelberg game equilibrium control model for coordinated adaptive cruise control and vehicle stability, and discretize it.

[0220] First, establish a vehicle body stability control model.

[0221]

[0222]

[0223] ,

[0224] In the formula, It is the state vector of the vehicle body stability control system. , This indicates the vehicle's yaw angle, measured in degrees (deg). and This is the coefficient matrix of the vehicle body stability control system. This is the input vector for the vehicle stability control system. , , , , These represent the longitudinal tire forces of the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, in N. This indicates the steering angle of the vehicle's front wheels, measured in degrees (deg). This indicates the total vehicle weight, expressed in kg. This indicates the longitudinal speed of the vehicle, expressed in m / s. This indicates the sprung mass, expressed in kg. This represents the height from the center of mass to the center of tilt, in meters (m). and These represent the distances from the vehicle's center of gravity to the front and rear axles, respectively, in meters (m). This indicates the vehicle's track width, in meters (m). This represents the yaw inertia of the entire vehicle, expressed in kgm. 2 , This represents the suspension roll damping coefficient, expressed in kN / rad. This indicates the suspension roll stiffness, expressed in Nm / rad. This represents the yaw-roll inertia product of a vehicle, measured in kg / m. 2 , This represents the vehicle's moment of inertia during roll, measured in kgm. 2 , This indicates the distance from the center of the roll to the ground, in meters (m). This indicates the unsprung mass, expressed in kg. This indicates the height of the unsprung mass's center of gravity, in meters (m). This represents the unsprung mass tilting stiffness, expressed in Nm / rad.

[0225]

[0226]

[0227]

[0228]

[0229]

[0230]

[0231]

[0232]

[0233]

[0234] Secondly, by combining the vehicle body stability control model and the vehicle adaptive cruise control model, a Stackelberg game equilibrium control model for coordinating adaptive cruise and vehicle body stability is obtained:

[0235]

[0236] ,

[0237] In the formula, It is the state vector of the Stackelberg game equilibrium control system that coordinates adaptive cruise control and vehicle stability. , , , and The Stackelberg game equilibrium control system coefficient matrix is ​​used to coordinate adaptive cruise control and vehicle stability. The Stackelberg game-theoretic equilibrium control system uses an interference input vector to coordinate adaptive cruise control and vehicle stability. ;

[0238] Then, using Ts as a sample, the Stackelberg game equilibrium control model of coordinated adaptive cruise control and vehicle stability is discretized to obtain the Stackelberg game equilibrium discrete incremental model of coordinated adaptive cruise control and vehicle stability:

[0239]

[0240] In the formula,

[0241]

[0242] S2.2 Calculate the Stackelberg game equilibrium between adaptive cruise control and vehicle stability control using model predictive control algorithms, including the following:

[0243] First, the control output of the vehicle's adaptive cruise control system is designed based on the requirements of adaptive cruise control and vehicle stability control. and vehicle stability control system control output The mathematical expression is as follows:

[0244]

[0245] In the formula,

[0246] Based on the control output of the vehicle adaptive cruise control system Control output with vehicle body stability control system Define their respective cost functions.

[0247]

[0248]

[0249] In the formula,

[0250]

[0251]

[0252]

[0253]

[0254]

[0255]

[0256]

[0257] Next, the cost function of the vehicle's adaptive cruise control system will be... Rewritten as:

[0258]

[0259] In the formula,

[0260] Minimize the cost function of the vehicle's adaptive cruise control system Equivalent to the following formula:

[0261]

[0262] Finding the extreme value of this expression, we get:

[0263]

[0264] Therefore, we obtain expression:

[0265]

[0266] Furthermore, regarding the cost function Find the second derivative:

[0267]

[0268] Therefore, the optimal solution for the vehicle adaptive cruise control system is obtained. , :

[0269]

[0270] Similarly, the cost function of the vehicle body stability control system rewrite:

[0271]

[0272] In the formula,

[0273] Minimize the cost function of the vehicle stability control system Equivalent to the following formula:

[0274]

[0275] Finding the extreme value of this expression, we get:

[0276]

[0277] Therefore, we get expression:

[0278]

[0279] Furthermore, regarding the cost function Find the second derivative:

[0280]

[0281] This yields the optimal solution for the vehicle stability control system. , :

[0282]

[0283] Substitute the optimal solution for the vehicle's adaptive cruise control system ,

[0284]

[0285] The optimal solution for vehicle stability control system Substitute the optimal solution for the vehicle's adaptive cruise control system Ultimately, the Stackelberg game equilibrium solution for coordinating adaptive cruise control and vehicle stability is obtained. and The single-step optimal solution of the vehicle body stability control system Single-step optimal solution of vehicle adaptive cruise control system The relationship can be expressed by the following formula:

[0286]

[0287] In the formula, and These represent the mapping rules between the vehicle stability control system and the vehicle adaptive cruise control system, respectively.

[0288] When the vehicle is in vehicle stability control mode, the system decision module includes the following:

[0289] S3.1 Discretize the vehicle body stability control model using Ts as a sample to obtain the discrete incremental model of vehicle body stability control:

[0290]

[0291] In the formula,

[0292] , , , ,

[0293] S3.2 Calculate the optimal longitudinal tire force using the model predictive control algorithm:

[0294] First, the control output of the vehicle stability control system is designed based on the vehicle stability control requirements. ,

[0295]

[0296] In the formula, ,

[0297] Secondly, based on the control output of the vehicle body stability control system Cost function for designing a vehicle body stability control system ,

[0298]

[0299] In the formula,

[0300]

[0301]

[0302] Next, the cost function of the vehicle stability control system is... Rewritten as:

[0303]

[0304] In the formula,

[0305] Minimize the cost function of the vehicle body stability control system Equivalent to the following formula:

[0306]

[0307] Finding the extreme value of this expression, we get:

[0308]

[0309] Therefore, we obtain expression:

[0310]

[0311] Furthermore, regarding the cost function Find the second derivative:

[0312]

[0313] This yields the optimal solution for the vehicle stability control system. and optimal tire longitudinal force , :

[0314]

[0315] .

[0316] The execution module includes the following:

[0317] The expected longitudinal tire force calculated based on the system decision module With the desired longitudinal acceleration Calculate the final expected longitudinal force for each wheel. ,in, , ,

[0318] .

[0319] In the formula, , , , These represent the final expected longitudinal forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

Claims

1. A game-theoretic balance control system that coordinates adaptive cruise control and vehicle stability, characterized in that, Includes the following: The aforementioned game-theoretic equilibrium control system for coordinating adaptive cruise control and vehicle stability includes an information acquisition module, a vehicle status assessment module, a system decision-making module, and an execution module. The information acquisition module includes a driving scene acquisition unit, a vehicle status information acquisition unit, and a vehicle information database. The driving scene information acquisition unit includes a binocular camera, a millimeter-wave radar, and a lidar. These are respectively installed below the rearview mirror, in the middle of the front bumper, and above the windshield. They are used to acquire information about the vehicle ahead, surrounding vehicles, and the scene. The information about the vehicle ahead includes the longitudinal speed and acceleration of the vehicle ahead, the relative distance between the vehicle and the vehicle ahead, and the relative speed between the vehicle and the vehicle ahead. The information about the surrounding vehicles and the scene includes the road surface level, the vehicle density level of the current lane and surrounding lanes, and the weather condition level. The vehicle status information acquisition unit includes four photoelectric wheel speed sensors and an inertial measurement unit. The four photoelectric wheel speed sensors are respectively installed on the four wheel hubs, and the inertial measurement unit is installed in the center of the vehicle chassis. It is used to acquire and estimate wheel speed, vehicle longitudinal speed, vehicle body roll angle, vehicle longitudinal acceleration, center of gravity sideslip angle, and unsprung mass roll angle. The vehicle status assessment module uses driving scenario information and vehicle status information collected by the information acquisition module to determine the current vehicle control mode. The vehicle control modes include cruise control mode, adaptive cruise control mode, Stackelberg game equilibrium control mode, and vehicle stability control mode. The cruise control mode includes level one, level two, and level three cruise control modes, and determines the current cruise control level by calculating a cruise control factor. The adaptive cruise control mode includes level one, level two, and level three adaptive cruise control modes, and determines the current adaptive cruise control level by calculating an adaptive cruise control factor. The vehicle stability control mode includes level one and level two vehicle stability control modes, and determines whether the vehicle is in a Stackelberg game equilibrium control mode or a vehicle stability control mode by calculating a vehicle stability factor. If there are no vehicles ahead in the current lane, the vehicle status assessment module determines that the vehicle has entered cruise control mode and calculates the cruise control factor. To determine the vehicle's cruise control mode, cruise control factor. It can be calculated using the following formula: ， In the formula, , , , These are weighting coefficients. , Indicates the road surface grade; when driving on slippery asphalt or concrete roads. When driving on dry asphalt or cement roads, ; This indicates the vehicle density level of the current lane and surrounding lanes; its value depends on the vehicle density levels of both the current lane and the surrounding lanes. In the formula, , These are weighting coefficients. , This indicates the current lane vehicle density level, categorized into low density, low-medium density, medium density, and medium-high density levels based on hourly traffic volume. When hourly traffic volume is less than 100 vehicles, the current lane vehicle density level is low density. When the hourly traffic flow is between 100 and 200 vehicles, the current lane's vehicle density level is considered low to medium. When the hourly traffic flow is between 200 and 300 vehicles, the current lane's vehicle density level is medium density. When the hourly traffic flow is between 300 and 400 vehicles, the current lane's vehicle density level is medium to high density. ; This indicates the vehicle density level of the surrounding lanes, which is also divided into low density, low-medium density, medium density, and medium-high density levels based on hourly traffic flow. When the hourly traffic flow is less than 100 vehicles, the vehicle density level of the surrounding lanes is low density. When the hourly traffic volume is between 100 and 200 vehicles, the vehicle density level of the surrounding lanes is low to medium. When the hourly traffic volume is between 200 and 300 vehicles, the vehicle density level of the surrounding lanes is medium density. When the hourly traffic volume is between 300 and 400 vehicles, the vehicle density level of the surrounding lanes is medium to high density. ; This indicates the weather condition level, and its value depends on the wind force level and weather phenomena. In the formula, , These are weighting coefficients. , This indicates the wind force level. When the wind force is level 0-2, When the wind force is 3-4, When the wind force is 5-6, , Indicates a weather phenomenon, on a sunny day. On cloudy days, On days with light rain or slight haze, During moderate rain or moderate smog, ; This indicates the vehicle's braking ability level, and its value depends on the vehicle's braking distance from 100 km / h. When the vehicle's braking distance from 100 km / h is less than 35 meters... When the braking distance of a vehicle from 100 km / h is greater than 35 meters but less than 50 meters, When the braking distance of a vehicle from 100 km / h is greater than 50 meters but less than 100 meters, When the braking distance of a vehicle from 100 km / h exceeds 100 meters, ; Cruise control factor The factors to consider include: road surface conditions (icy or snowy); traffic flow in the current or surrounding lanes between 400 and 600 vehicles per hour; wind speeds of 7-12; heavy rain; severe fog or snow. In other driving scenarios, ; If cruise control factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 cruise control mode. If the cruise control factor... satisfy The vehicle status assessment module determines that the vehicle is in level two cruise control mode. If the cruise control factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 3 cruise control mode. If the cruise control factor... The vehicle status assessment module forces the vehicle to exit cruise control mode; when the vehicle is in Level 1 cruise control mode, the cruise speed... When the vehicle is in Level 2 cruise control mode, the cruising speed is... When the vehicle is in Level 3 cruise control mode, the cruising speed is... ,in It is a cruise control adjustment factor that the driver can select. It is divided into five levels: A, B, C, D, and E, with corresponding values ​​of 1, 0.5, 0, -0.5, and 1, respectively. If there is a trackable vehicle ahead in the current lane, the vehicle status assessment module determines that the vehicle has entered adaptive cruise mode and calculates an adaptive cruise factor to determine the adaptive cruise mode in which the vehicle is in. The adaptive cruise factor can be calculated according to the following formula: In the formula, , , , These are weighting coefficients. , , , The meaning is the same as above. This indicates the vehicle's performance level, and its value depends on the vehicle's 0-100km / h acceleration time and 100km / h braking distance. In the formula, , These are weighting coefficients. , This indicates the vehicle's 0-100km / h acceleration time. When the vehicle's 0-100km / h acceleration time is less than 5 seconds, When a vehicle's 0-100km / h acceleration time is greater than 5 seconds but less than 12 seconds, When a vehicle's 0-100km / h acceleration time is greater than 12 seconds, , This indicates the vehicle's braking distance at 100 km / h, and its meaning is the same as described above. Adaptive cruise factor The factors to consider include: road surface conditions (icy or snowy); traffic flow in the current or surrounding lanes between 400 and 600 vehicles per hour; wind speeds of 7-12; heavy rain; severe fog or snow. In other driving scenarios, ; If adaptive cruise factor satisfy The vehicle status assessment module determines that the vehicle is in Level 1 adaptive cruise control mode. If the adaptive cruise factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 2 adaptive cruise control mode. If the adaptive cruise factor... satisfy The vehicle status assessment module determines that the vehicle is in Level 3 adaptive cruise control mode. If the adaptive cruise factor... The vehicle status assessment module forces the vehicle to exit adaptive cruise control mode; The vehicle condition assessment module calculates the vehicle stability factor. To determine whether the vehicle is in Stackelberg game equilibrium control mode or vehicle stability control mode, the vehicle stability factor is used. It can be calculated using the following formula: In the formula, , , These are weighting coefficients. , Vehicle stability factor The trade-off factors Vehicle stability factor Regulatory factors, The initial vehicle body stability factor is calculated. This is the final normalized vehicle body stability factor. This indicates the vehicle's sideslip angle, measured in degrees (deg). This indicates the side tilt angle of the carriage, measured in degrees (deg). This indicates the unsprung mass tilt angle, in deg. If vehicle stability factor satisfy The vehicle status assessment module determines whether the vehicle is in cruise control mode or adaptive cruise control mode; if the vehicle stability factor... satisfy The vehicle state assessment module determines that the vehicle is in a Stackelberg game equilibrium control mode; if the vehicle stability factor satisfy The vehicle status assessment module determines that the vehicle is in the first-level vehicle stability control mode; If vehicle stability factor satisfy The vehicle status assessment module determines that the vehicle is in the secondary vehicle stability control mode; When the vehicle is in adaptive cruise control mode, the system decision module establishes a vehicle adaptive cruise model and uses a model predictive control algorithm to calculate the optimal longitudinal acceleration and deceleration. The non-negative weight matrix in the model predictive control algorithm... Based on adaptive cruise factor If the vehicle is in Level 1 adaptive cruise control mode, that is... , , If the vehicle is in Level 2 adaptive cruise control mode, that is... , , If the vehicle is in Level 3 adaptive cruise control mode, that is... , , In the formula, , , , , , The weighting coefficients are the weighting coefficients of the non-negative weight matrix. , , and Non-negative weight matrix The trade-off factors; When the vehicle is in Stackelberg game equilibrium control mode, the system decision module establishes a game control model for adaptive cruise control and vehicle stability control. It uses a model predictive control algorithm to calculate the Stackelberg game equilibrium between adaptive cruise control and vehicle stability control, i.e., to calculate the optimal longitudinal acceleration / deceleration and the optimal longitudinal tire force. The algorithm includes a non-negative weight matrix. and Based on adaptive cruise factor and vehicle stability factor Obtain , , , , In the formula, , , , , Non-negative weight matrix and The weighting coefficients, , , Non-negative weight matrix The trade-off factors; When the vehicle is in vehicle stability control mode, the system decision module establishes a vehicle stability control model and uses a model predictive control algorithm to calculate the optimal longitudinal tire force. The non-negative weight matrix in the model predictive control algorithm... According to vehicle stability factor If the vehicle is in Level 1 vehicle stability control mode, that is... , , , ; If the vehicle is in Level 2 vehicle stability control mode, i.e. , , , In the formula, , , , , , Non-negative weight matrix The weighting coefficients, , , ; The execution module obtains the final expected tire force based on the decision calculated by the system decision module, thereby achieving safe driving of the vehicle.

2. The game-theoretic equilibrium control system for coordinating adaptive cruise control and vehicle stability according to claim 1, characterized in that: The vehicle is in adaptive cruise control mode, and the system decision module includes the following: S2.1 Establish a vehicle adaptive cruise control model and discretize it. In the formula, It is the state vector of the vehicle's adaptive cruise control system. , This represents the difference between the actual distance between the vehicle and the vehicle ahead detected by the sensors during adaptive cruise control, and the desired distance, expressed in meters (m). This indicates the speed difference between the vehicle and the target vehicle ahead during adaptive cruise control, expressed in m / s. This represents the vehicle's actual longitudinal acceleration, measured in m / s². 2 , , and This is the coefficient matrix of the vehicle's adaptive cruise control system. This is the input vector for the vehicle's adaptive cruise control system. , This represents the desired deceleration, expressed in m / s². 2 , This is the interference input vector for the vehicle's adaptive cruise control system. , The time distance between the front of the train is expressed in seconds (s). It is the delay constant; Using Ts as a sample, the vehicle adaptive cruise control model is discretized to obtain the vehicle adaptive cruise discrete incremental model: In the formula, S2.2 Calculate the optimal longitudinal acceleration and deceleration using the model predictive control algorithm: First, the vehicle's adaptive cruise control system control output is designed based on the requirements of adaptive cruise following other vehicles. , In the formula, Secondly, based on the control output of the vehicle's adaptive cruise control system Design a cost function for a vehicle adaptive cruise control system. , In the formula, Next, the cost function of the vehicle's adaptive cruise control system will be... Rewritten as: In the formula, Minimize the cost function of the vehicle's adaptive cruise control system Equivalent to the following formula: Finding the extreme value of this expression, we get: Therefore, we obtain expression: Furthermore, regarding the cost function Find the second derivative: Therefore, the optimal solution for the vehicle adaptive cruise control system is obtained. and optimal longitudinal acceleration and deceleration , : 。 3. The game-theoretic equilibrium control system for coordinating adaptive cruise control and vehicle stability according to claim 1, characterized in that: The vehicle is in a Stackelberg game equilibrium control mode, and the system decision module includes the following: S3.1 Establish a Stackelberg game equilibrium control model for coordinated adaptive cruise control and vehicle stability, and discretize it. First, establish a vehicle body stability control model. In the formula, It is the state vector of the vehicle body stability control system. , This indicates the vehicle's yaw angle, measured in degrees (deg). and This is the coefficient matrix of the vehicle body stability control system. This is the input vector for the vehicle stability control system. , , , , These represent the longitudinal tire forces of the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, in N. This indicates the steering angle of the vehicle's front wheels, measured in degrees (deg). This indicates the total vehicle weight, expressed in kg. This indicates the longitudinal speed of the vehicle, expressed in m / s. This indicates the sprung mass, expressed in kg. This represents the height from the center of mass to the center of tilt, in meters (m). and These represent the distances from the vehicle's center of gravity to the front and rear axles, respectively, in meters (m). This indicates the vehicle's track width, in meters (m). This represents the yaw inertia of the entire vehicle, expressed in kgm. 2 , This represents the suspension roll damping coefficient, expressed in kN / rad. This indicates the suspension roll stiffness, expressed in Nm / rad. This represents the yaw-roll inertia product of a vehicle, measured in kg / m. 2 , This represents the vehicle's moment of inertia during roll, measured in kgm. 2 , This indicates the distance from the center of the roll to the ground, in meters (m). This indicates the unsprung mass, expressed in kg. This indicates the height of the unsprung mass's center of gravity, in meters (m). This represents the unsprung mass tilting stiffness, expressed in Nm / rad. Secondly, by combining the vehicle body stability control model and the vehicle adaptive cruise control model, a Stackelberg game equilibrium control model for coordinating adaptive cruise and vehicle body stability is obtained: In the formula, It is the state vector of the Stackelberg game equilibrium control system that coordinates adaptive cruise control and vehicle stability. , , , and The Stackelberg game equilibrium control system coefficient matrix is ​​used to coordinate adaptive cruise control and vehicle stability. The Stackelberg game-theoretic equilibrium control system uses an interference input vector to coordinate adaptive cruise control and vehicle stability. ; Then, using Ts as a sample, the Stackelberg game equilibrium control model of coordinated adaptive cruise control and vehicle stability is discretized to obtain the Stackelberg game equilibrium discrete incremental model of coordinated adaptive cruise control and vehicle stability: In the formula, S3.2 Calculate the Stackelberg game equilibrium between adaptive cruise control and vehicle stability control using model predictive control algorithms, including the following: First, the control output of the vehicle's adaptive cruise control system is designed based on the requirements of adaptive cruise control and vehicle stability control. and vehicle stability control system control output The mathematical expression is as follows: In the formula, Based on the control output of the vehicle adaptive cruise control system Control output with vehicle body stability control system Define their respective cost functions. In the formula, Next, the cost function of the vehicle's adaptive cruise control system will be... Rewritten as: In the formula, Minimize the cost function of the vehicle's adaptive cruise control system Equivalent to the following formula: Finding the extreme value of this expression, we get: Therefore, we obtain expression: Furthermore, regarding the cost function Find the second derivative: Therefore, the optimal solution for the vehicle adaptive cruise control system is obtained. , : Similarly, the cost function of the vehicle body stability control system rewrite: In the formula, Minimize the cost function of the vehicle stability control system Equivalent to the following formula: Finding the extreme value of this expression, we get: Therefore, we get expression: Furthermore, regarding the cost function Find the second derivative: This yields the optimal solution for the vehicle stability control system. , : Substitute the optimal solution for the vehicle's adaptive cruise control system , The optimal solution for vehicle stability control system Substitute the optimal solution for the vehicle's adaptive cruise control system Ultimately, the Stackelberg game equilibrium solution for coordinating adaptive cruise control and vehicle stability is obtained. and The single-step optimal solution of the vehicle body stability control system Single-step optimal solution of vehicle adaptive cruise control system The relationship can be expressed by the following formula: In the formula, and These represent the mapping rules between the vehicle stability control system and the vehicle adaptive cruise control system, respectively.

4. The game-theoretic equilibrium control system for coordinating adaptive cruise control and vehicle stability according to claim 1, characterized in that: The vehicle is in vehicle stability control mode, and the system decision module includes the following: S4.1 Discretize the vehicle body stability control model using Ts as a sample to obtain the discrete incremental model of vehicle body stability control: In the formula, S4.2 Calculate the optimal longitudinal tire force using the model predictive control algorithm: First, the control output of the vehicle stability control system is designed based on the vehicle stability control requirements. , In the formula, , Secondly, based on the control output of the vehicle body stability control system Cost function for designing a vehicle body stability control system , In the formula, Next, the cost function of the vehicle stability control system is... Rewritten as: In the formula, Minimize the cost function of the vehicle body stability control system Equivalent to the following formula: Finding the extreme value of this expression, we get: Therefore, we obtain expression: Furthermore, regarding the cost function Find the second derivative: This yields the optimal solution for the vehicle stability control system. and optimal tire longitudinal force , : 。 5. The game-theoretic equilibrium control system for coordinating adaptive cruise control and vehicle stability according to claim 1, characterized in that: The execution module includes the following: The expected longitudinal tire force calculated based on the system decision module With the desired longitudinal acceleration Calculate the final expected longitudinal force for each wheel. ,in, , , In the formula, , , , These represent the final expected longitudinal forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

Images