A vehicle control method, apparatus, device, and medium

Abstract

The application discloses a vehicle control method, device, equipment and medium, and relates to the technical field of intelligent driving, and comprises the following steps: determining a target function and a target constraint according to target variables related to vehicle decision and vehicle planning; wherein, the target variables comprise variables related to vehicle motion state, variables related to vehicle lane-changing state, variables related to obstacles and variables related to vehicle driving area; optimizing the values of the target variables according to the target constraint to obtain target values of the target variables under the target constraint; and controlling the vehicle according to the target values to realize vehicle control for overall optimization of the vehicle decision and the vehicle planning. As can be seen from the above, the application takes the vehicle decision and the vehicle planning as an overall optimization target, applies a target constraint and performs optimization solving, so that the real-time performance and stability of vehicle control are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent driving technology, and in particular to a vehicle control method, device, equipment and medium. Background Technology

[0002] See Figure 1 As shown, on existing autonomous driving platforms, considering real-time performance and cost-effectiveness, the decision-making and planning modules are typically separated into two independent modules that interact with each other via internal module communication. This makes it difficult to obtain the optimal result that holistically considers both decision-making and planning. Latest technologies consider using deep reinforcement learning for optimal processing, but this faces certain cost pressures and deployment challenges.

[0003] Therefore, the aforementioned technical problems urgently need to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a vehicle control method, device, equipment, and medium that can realize vehicle control that takes into account the overall decision-making and planning. The specific solution is as follows:

[0005] In a first aspect, this application discloses a vehicle control method, comprising:

[0006] The objective function and objective constraints are determined based on the objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane change state, variables related to obstacles, and variables related to vehicle driving area;

[0007] The values ​​of the target variable are optimized according to the target constraints to obtain the target values ​​of the target variable under the target constraints.

[0008] The vehicle is controlled according to the target value to achieve overall optimization of vehicle decision-making and vehicle planning.

[0009] Optionally, determining the objective function based on target variables related to vehicle decision-making and vehicle planning includes:

[0010] Determine the actual distance the vehicle travels from the start time to the current time, and determine the planned distance the vehicle travels along the target navigation line from the start time to the current time. Then, determine the first target item based on the actual distance traveled and the planned distance traveled.

[0011] Determine a first lateral distance between the center line of the lane where the vehicle is currently located and the target navigation line, and determine a second lateral distance between the vehicle and the lane center line. Then, determine a second target item based on the first lateral distance and the second lateral distance.

[0012] A third target item is determined based on the vehicle's acceleration at the current moment; a fourth target item is determined based on the vehicle's lateral velocity at the current moment; and a fifth target item is determined based on the vehicle's target lane change value at the current moment; wherein different lane change directions correspond to different target lane change values;

[0013] The sixth target item is determined based on the first lateral distance and the upper limit threshold of the first lateral distance, and the seventh target item is determined based on the target relaxation value of the target obstacle at the current time.

[0014] Wherein, the target relaxation value is the sum of the first relaxation value of the target obstacle in the direction of the lane centerline and the second relaxation value of the target obstacle in the direction perpendicular to the lane centerline;

[0015] The objective function is determined based on the first objective item, the second objective item, the third objective item, the fourth objective item, the fifth objective item, the sixth objective item, and the seventh objective item.

[0016] Optionally, target constraints are determined based on target variables related to vehicle decision-making and vehicle planning, including:

[0017] The vehicle's lateral and longitudinal speed constraints are determined based on the vehicle's turning radius at the current moment, the distance between the vehicle's center of gravity and the rear wheel center, and the vehicle's minimum turning radius.

[0018] The difference between the second lateral distance and the first lateral distance is controlled within a preset range to obtain lane change constraints; wherein, the preset range is a difference range determined based on the lane width;

[0019] The target relaxation value of the target obstacle is controlled between a lower relaxation value threshold and an upper relaxation value threshold to obtain collision constraints;

[0020] The lower limit threshold and the upper limit threshold of the first lateral distance are determined based on the target driving area and the target traffic rules, and the first lateral distance is controlled between the lower limit threshold and the upper limit threshold to obtain traffic rule constraints.

[0021] Optionally, determining the vehicle's lateral and longitudinal speed constraints based on the vehicle's turning radius at the current moment, the distance between the vehicle's center of gravity and the rear wheel center, and the vehicle's minimum turning radius includes:

[0022] The first ratio term is determined based on the ratio between the distance between the vehicle's center of gravity and the center of the rear wheel and the vehicle's minimum turning radius;

[0023] The second ratio term is determined based on the ratio between the distance between the vehicle's center of gravity and the center of the rear wheel and the vehicle's turning radius at the current moment;

[0024] Take the opposite of the sum of the first ratio term and the second ratio term to obtain a first result, and determine a second result based on the product of the first result and the longitudinal speed of the vehicle at the current moment;

[0025] A third result is determined based on the difference between the first ratio term and the second ratio term, and a fourth result is determined based on the product of the first result and the longitudinal velocity of the vehicle at the current moment.

[0026] The lateral velocity of the vehicle at the current moment is controlled between the second result and the fourth result to obtain the lateral and longitudinal velocity constraints of the vehicle.

[0027] Optionally, the vehicle control method further includes:

[0028] The target intermediate variable is determined based on the lane width and the target lane change value;

[0029] The first lateral distance of the vehicle at the current moment is determined based on the target intermediate variable and the first lateral distance of the vehicle at the previous moment.

[0030] Optionally, the vehicle control method further includes:

[0031] Obtain information about obstacles within a preset distance from the vehicle;

[0032] The lower limit threshold and the upper limit threshold of the relaxation value are determined based on the obstacle information.

[0033] Optionally, optimizing the value of the target variable based on the target constraint to obtain the target value of the target variable under the target constraint includes:

[0034] The objective variable is optimized by an objective solver according to the objective constraints to obtain the objective value of the objective variable under the objective constraints; wherein the objective value is the value that minimizes the function value of the objective function.

[0035] Secondly, this application discloses a vehicle control device, comprising:

[0036] The function and constraint determination module is used to determine the objective function and objective constraints based on the objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane change state, variables related to obstacles, and variables related to vehicle driving area;

[0037] The value optimization module is used to optimize the value of the target variable according to the target constraint, so as to obtain the target value of the target variable under the target constraint.

[0038] The vehicle control module is used to control the vehicle according to the target value, so as to achieve overall optimization of vehicle decision-making and vehicle planning.

[0039] Thirdly, this application discloses an electronic device, comprising:

[0040] Memory, used to store computer programs;

[0041] A processor is used to execute the computer program to implement the aforementioned vehicle control method.

[0042] Fourthly, this application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned vehicle control method.

[0043] As can be seen, this application proposes a vehicle control method, comprising: determining an objective function and objective constraints based on objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane-changing state, variables related to obstacles, and variables related to vehicle driving area; optimizing the values ​​of the objective variables according to the objective constraints to obtain target values ​​of the objective variables under the objective constraints; and controlling the vehicle according to the target values ​​to achieve vehicle control that optimizes the overall vehicle decision-making and vehicle planning. In summary, this application first determines an objective function and objective constraints based on objective variables related to vehicle decision-making and vehicle planning, and optimizes the values ​​of the objective variables according to the objective constraints to obtain target values ​​of the objective variables under the objective constraints. Compared to traditional technologies that separate the decision-making module and the planning module into two separate modules and then exchange data through internal module communication, this application treats vehicle decision-making and vehicle planning as a whole optimization objective, applies objective constraints, and performs optimization solutions, thereby improving the real-time performance and stability of vehicle control. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0045] Figure 1 This is a traditional vehicle control method;

[0046] Figure 2 This is a flowchart of a vehicle control method disclosed in this application;

[0047] Figure 3 This is a schematic diagram of a vehicle kinematics model in a curvilinear coordinate system disclosed in this application.

[0048] Figure 4 This is a schematic diagram of a specific driving road environment disclosed in this application;

[0049] Figure 5 This is a flowchart of a specific vehicle control method disclosed in this application;

[0050] Figure 6 This is a schematic diagram of the structure of a vehicle control device disclosed in this application;

[0051] Figure 7 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] On existing autonomous driving platforms, considering real-time performance and cost-effectiveness, the decision-making module and the planning module are usually separated into two separate modules and then interact with each other through internal module communication. This makes it difficult to obtain the optimal result by taking the decision-making and planning as a whole.

[0054] Therefore, this application proposes a vehicle control scheme that enables vehicle control that takes into account both decision-making and planning as a whole.

[0055] This application discloses a vehicle control method. See also Figure 2 As shown, the method includes:

[0056] Step S11: Determine the objective function and objective constraints based on the objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane change state, variables related to obstacles, and variables related to vehicle driving area.

[0057] In this embodiment, the perception module acquires the motion trajectories of obstacles around the vehicle, map information, and current traffic rules and rule changes. The map information includes lane centerlines, lane widths, and road curvature, while the traffic rules include traffic light information and speed limits. Furthermore, a decision-making and programming model based on MIP (mixed-integer programming) is established based on the above information.

[0058] First, a linearized vehicle kinematics model is established in a curvilinear coordinate system. (See...) Figure 3 As shown, p s (i+1)=p s (i)+T s v s (i); v s (i+1)=v s (i)+T s a s (i); p n (i+1)=p n (i)+T s v n (i); where p s (i+1) represents the distance the vehicle travels from the starting time to time i+1, T s Indicates the preset sampling period, v s (i) represents the longitudinal velocity at time i, a s (i) represents the acceleration at time i, p n (i+1) represents the lateral distance from the vehicle to the lane centerline at time i+1, v n (i) represents the lateral velocity at time i. Furthermore, Figure 3 p in x and p y These represent the two coordinate axes of the coordinate system.

[0059] Furthermore, the objective function is determined based on target variables related to vehicle decision-making and vehicle planning. The specific process includes: determining the actual driving distance of the vehicle from the start time to the current time, and determining the planned driving distance of the vehicle along the target navigation line from the start time to the current time; then determining a first objective item based on the actual driving distance and the planned driving distance; determining a first lateral distance between the lane centerline of the vehicle's current lane and the target navigation line, and determining a second lateral distance between the vehicle and the lane centerline; then determining a second objective item based on the first lateral distance and the second lateral distance; determining a third objective item based on the vehicle's acceleration at the current time; and determining a third objective item based on the vehicle's acceleration at the current time. The fourth objective is determined by the lateral velocity at a given time; the fifth objective is determined by the target lane change value of the vehicle at the current time; wherein different lane change directions correspond to different target lane change values; the sixth objective is determined by the first lateral distance and the upper limit threshold of the first lateral distance; and the seventh objective is determined by the target relaxation value of the target obstacle at the current time; wherein the target relaxation value is the sum of the first relaxation value of the target obstacle in the direction of the lane centerline and the second relaxation value of the target obstacle in the direction perpendicular to the lane centerline; and the objective function is determined by the first objective, the second objective, the third objective, the fourth objective, the fifth objective, the sixth objective, and the seventh objective.

[0060] In some embodiments, the objective function is Expand to get Wherein, the first target item is w1 represents the first weight, p s (i) represents the actual distance traveled by the vehicle from the start time to time i. This represents the planned travel distance of the vehicle along the target navigation line from the starting time to time i. The second objective term is the square of the L2 norm; w2 represents the second weight, p n (i) represents the second lateral distance between the vehicle and the lane centerline at time i. The first lateral distance between the lane centerline of the vehicle's current lane at time i and the target navigation line is represented; the third target item is w3a. s (i) 2 w3 represents the third weight, a s (i) represents the acceleration of the vehicle at time i; the fourth objective term is w4v n (i) 2 w4 represents the fourth weight, v n(i) represents the lateral velocity of the vehicle at time i; the fifth objective term represents w5δ c (i), w5 represents the fifth weight, δ c (i) represents the target lane change value of the vehicle at time i. The value is 1 when changing lanes to the left and 0 when changing lanes to the right. The value is 0 when changing lanes to the left and 1 when changing lanes to the right; the sixth target item is... w6 represents the sixth weight. This represents the upper limit threshold of the first lateral distance; the seventh target item is w7v. c (i), w7 represents the seventh weight, v c (i) represents the target relaxation value of the target obstacle at time i.

[0061] It should be noted that the weights mentioned above were set by the operators based on their past experience. Furthermore, the first objective is to minimize the error between the actual driving distance and the planned driving distance; the second objective is to minimize the distance between the vehicle and the lane centerline; the third, fourth, and fifth objective are used to penalize excessive lateral speed, acceleration, and frequent lane changes, thereby ensuring driving comfort; the sixth objective is used to minimize the error between the lane centerline and the target navigation line; and the seventh objective is used to penalize the target slack variable of the target obstacle in collision detection to prevent the target slack variable from becoming too large.

[0062] Finally, target constraints are determined based on target variables related to vehicle decision-making and vehicle planning, including vehicle lateral and longitudinal speed constraints, lane change constraints, collision constraints, and traffic rule constraints.

[0063] In a first specific implementation, the lateral and longitudinal speed constraints of the vehicle are determined based on the turning radius of the vehicle at the current moment, the distance between the center of gravity of the vehicle and the center of the rear wheel, and the minimum turning radius of the vehicle.

[0064] For example, considering that a certain turning radius needs to be met during the turning process of a vehicle, this embodiment imposes the following constraints on the vehicle's lateral and longitudinal speeds: α represents the first ratio term. R This represents the second ratio term. Indicates the first result. Indicates the second result. Indicates the third result. This represents the fourth result, where R(i) represents the turning radius at time i, and l r R represents the distance between the vehicle's center of gravity and the center of the rear wheels. min This indicates the minimum turning radius.

[0065] In a second specific implementation, a target intermediate variable is determined based on the lane width and the target lane change value, and the first lateral distance of the vehicle at the current moment is determined based on the target intermediate variable and the first lateral distance of the vehicle at the previous moment. Further, the difference between the second lateral distance and the first lateral distance is controlled within a preset difference range to obtain the lane change constraint; wherein, the preset difference range is a difference range determined based on the lane width.

[0066] For example, first determine the target intermediate variable Δ c The range of (i): Where w represents the lane width, Know This represents the target lane change value, which has already been explained in the preceding process and will not be repeated here. Thus, we can obtain... Furthermore, the first lateral distance and lane change count are updated based on the target intermediate variable, thereby obtaining... Know Where, n LC (i+1) represents the number of lane changes at time n+1. Since Therefore, this embodiment ensures that only one lane-changing direction is allowed at a time. Furthermore, this embodiment constrains the vehicle to its current lane, thus obtaining the lane-changing constraint as follows: Furthermore, in this embodiment, the lane change reset time t is set. c And set the calculation method for lane change reset time as follows: Then, a minimum reset interval time t is given. min , t min ≤t c (i) In this way, by constraining the lane change interval, the bad driving experience caused by frequent lane changes can be avoided.

[0067] In a third specific implementation, obstacle information within a preset range from the vehicle is obtained, and a lower limit threshold and an upper limit threshold for relaxation value are determined based on the obstacle information. Then, the target relaxation value of the target obstacle is controlled between the lower limit threshold and the upper limit threshold to obtain the collision constraint.

[0068] Specifically, in this embodiment, the target obstacle is expanded into a rectangle according to the target relaxation value, and the vehicle is constrained outside the rectangle, thereby avoiding a collision between the vehicle and the target obstacle. In some embodiments, the preset range can be 10 meters, etc. It should be noted that the preset range can be set according to the actual situation and is not limited here.

[0069] In a fourth specific implementation, the lower limit threshold and the upper limit threshold of the first lateral distance are determined based on the road environment of the target driving area and the target traffic rules; the first lateral distance is controlled between the lower limit threshold and the upper limit threshold to obtain the traffic rule constraints corresponding to the target road environment.

[0070] Specifically, roads in different driving areas have different traffic rules. In this embodiment, the map can be divided into multiple segments according to a certain length of area. For each road segment, the lower limit threshold of the first lateral distance is determined based on the target road environment and target traffic rules. And the upper limit threshold of the lateral distance is By controlling This is to ensure that the lane centerline does not deviate too far from the target navigation line. Figure 4 It refers to a specific road environment.

[0071] In summary, this embodiment first establishes a kinematic model, then determines the objective function and objective constraints, thereby obtaining a decision-making and planning model.

[0072] Step S12: Optimize the value of the target variable according to the target constraint to obtain the target value of the target variable under the target constraint.

[0073] In this embodiment, the target variable includes a first variable. Second variable u = [a s v n δ c Δ c Furthermore, this embodiment transforms the decision-making and planning model into an optimization control problem. Specifically, the objective function is first transformed into the following form: Where H(i), q(i), and r(i) represent known parameter matrices, and T represents the transpose. Furthermore, the objective variable is optimized using an objective solver based on the objective constraints to find the minimum value of the objective function under the objective constraints.

[0074] It should be noted that, in addition to satisfying the above objective constraints, the target variable must also satisfy the following constraints: Know Where n1 represents the lane number, such as 1, 2, 3, etc. This indicates the lower limit threshold of longitudinal velocity. Indicates the upper limit threshold of longitudinal velocity. This indicates the lower limit threshold of acceleration. Indicates the upper limit threshold of acceleration. This indicates the lower limit threshold for lateral velocity. This indicates the upper limit threshold for lateral velocity.

[0075] It is understandable that the lower and upper thresholds mentioned above can be set according to the actual application scenario, and will not be elaborated here.

[0076] Step S13: Control the vehicle according to the target value to achieve overall optimization of vehicle decision-making and vehicle planning.

[0077] In this embodiment, the vehicle is controlled according to the target value to achieve overall optimization of vehicle decision-making and vehicle planning. See also... Figure 5 As shown, this embodiment treats decision-making and planning as a whole optimization objective, applies vehicle lateral and longitudinal speed constraints, lane change constraints, collision detection constraints, and traffic rule constraints, and then performs optimization to obtain the optimal objective value.

[0078] As can be seen, this application proposes a vehicle control method, comprising: determining an objective function and objective constraints based on objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane-changing state, variables related to obstacles, and variables related to vehicle driving area; optimizing the values ​​of the objective variables according to the objective constraints to obtain target values ​​of the objective variables under the objective constraints; and controlling the vehicle according to the target values ​​to achieve vehicle control that optimizes the overall vehicle decision-making and vehicle planning. In summary, this application first determines an objective function and objective constraints based on objective variables related to vehicle decision-making and vehicle planning, and optimizes the values ​​of the objective variables according to the objective constraints to obtain target values ​​of the objective variables under the objective constraints. Compared to traditional technologies that separate the decision-making module and the planning module into two separate modules and then exchange data through internal module communication, this application treats vehicle decision-making and vehicle planning as a whole optimization objective, applies objective constraints, and performs optimization solutions, thereby improving the real-time performance and stability of vehicle control.

[0079] Accordingly, this application also discloses a vehicle control device, see [link to relevant documentation]. Figure 6 As shown, the device includes:

[0080] The function and constraint determination module 11 is used to determine the objective function and objective constraints based on the objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane change state, variables related to obstacles, and variables related to vehicle driving area;

[0081] The value optimization module 12 is used to optimize the value of the target variable according to the target constraint, so as to obtain the target value of the target variable under the target constraint.

[0082] The vehicle control module 13 is used to control the vehicle according to the target value, so as to achieve overall optimization of vehicle decision-making and vehicle planning.

[0083] As can be seen, this application proposes a vehicle control method, comprising: determining an objective function and objective constraints based on objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane-changing state, variables related to obstacles, and variables related to vehicle driving area; optimizing the values ​​of the objective variables according to the objective constraints to obtain target values ​​of the objective variables under the objective constraints; and controlling the vehicle according to the target values ​​to achieve vehicle control that optimizes the overall vehicle decision-making and vehicle planning. In summary, this application first determines an objective function and objective constraints based on objective variables related to vehicle decision-making and vehicle planning, and optimizes the values ​​of the objective variables according to the objective constraints to obtain target values ​​of the objective variables under the objective constraints. Compared to traditional technologies that separate the decision-making module and the planning module into two separate modules and then exchange data through internal module communication, this application treats vehicle decision-making and vehicle planning as a whole optimization objective, applies objective constraints, and performs optimization solutions, thereby improving the real-time performance and stability of vehicle control.

[0084] Furthermore, embodiments of this application also provide an electronic device. Figure 7 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0085] Figure 7 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a display screen 23, an input / output interface 24, a communication interface 25, a power supply 26, and a communication bus 27. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the vehicle control method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0086] In this embodiment, the power supply 26 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 25 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 24 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0087] Furthermore, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored thereon may include computer programs 221, and the storage method may be temporary storage or permanent storage. The computer programs 221 may include, in addition to computer programs capable of performing the vehicle control method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, computer programs capable of performing other specific tasks.

[0088] Furthermore, embodiments of this application also disclose a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed vehicle control method.

[0089] For the specific steps of this method, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0090] The various embodiments in this application are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. For the same or similar parts between the various embodiments, refer to each other. As for the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and relevant parts can be referred to in the method section.

[0091] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0092] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0093] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0094] The above provides a detailed description of a vehicle control method, apparatus, device, and storage medium provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A vehicle control method, characterized in that, include: The objective function and objective constraints are determined based on the objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane change state, variables related to obstacles, and variables related to vehicle driving area; The values ​​of the target variable are optimized according to the target constraints to obtain the target values ​​of the target variable under the target constraints. The vehicle is controlled according to the target value to achieve overall optimization of vehicle decision-making and vehicle planning; The process of determining the objective function based on target variables related to vehicle decision-making and vehicle planning includes: Determine the actual distance the vehicle travels from the start time to the current time, and determine the planned distance the vehicle travels along the target navigation line from the start time to the current time. Then, determine the first target item based on the actual distance traveled and the planned distance traveled. Determine a first lateral distance between the center line of the lane where the vehicle is currently located and the target navigation line, and determine a second lateral distance between the vehicle and the lane center line. Then, determine a second target item based on the first lateral distance and the second lateral distance. A third target item is determined based on the vehicle's acceleration at the current moment; a fourth target item is determined based on the vehicle's lateral velocity at the current moment; and a fifth target item is determined based on the vehicle's target lane change value at the current moment; wherein different lane change directions correspond to different target lane change values; The sixth target item is determined based on the first lateral distance and the upper limit threshold of the first lateral distance, and the seventh target item is determined based on the target relaxation value of the target obstacle at the current time. Wherein, the target relaxation value is the sum of the first relaxation value of the target obstacle in the direction of the lane centerline and the second relaxation value of the target obstacle in the direction perpendicular to the lane centerline; The objective function is determined based on the first objective item, the second objective item, the third objective item, the fourth objective item, the fifth objective item, the sixth objective item, and the seventh objective item; Objective constraints are determined based on target variables related to vehicle decision-making and vehicle planning, including: The vehicle's lateral and longitudinal speed constraints are determined based on the vehicle's turning radius at the current moment, the distance between the vehicle's center of gravity and the rear wheel center, and the vehicle's minimum turning radius. The difference between the second lateral distance and the first lateral distance is controlled within a preset range to obtain lane change constraints; wherein, the preset range is a difference range determined based on the lane width; The target relaxation value of the target obstacle is controlled between a lower relaxation value threshold and an upper relaxation value threshold to obtain collision constraints; The lower limit threshold and the upper limit threshold of the first lateral distance are determined based on the target driving area and the target traffic rules, and the first lateral distance is controlled between the lower limit threshold and the upper limit threshold to obtain traffic rule constraints.

2. The vehicle control method according to claim 1, characterized in that, The determination of vehicle lateral and longitudinal speed constraints based on the vehicle's turning radius at the current moment, the distance between the vehicle's center of gravity and the rear wheel center, and the vehicle's minimum turning radius includes: The first ratio term is determined based on the ratio between the distance between the vehicle's center of gravity and the center of the rear wheel and the vehicle's minimum turning radius; The second ratio term is determined based on the ratio between the distance between the vehicle's center of gravity and the center of the rear wheel and the vehicle's turning radius at the current moment; Take the opposite of the sum of the first ratio term and the second ratio term to obtain a first result, and determine a second result based on the product of the first result and the longitudinal speed of the vehicle at the current moment; A third result is determined based on the difference between the first ratio term and the second ratio term, and a fourth result is determined based on the product of the first result and the longitudinal velocity of the vehicle at the current moment. The lateral velocity of the vehicle at the current moment is controlled between the second result and the fourth result to obtain the lateral and longitudinal velocity constraints of the vehicle.

3. The vehicle control method according to claim 1, characterized in that, Also includes: The target intermediate variable is determined based on the lane width and the target lane change value; The first lateral distance of the vehicle at the current time is determined based on the target intermediate variable and the first lateral distance of the vehicle at the previous time.

4. The vehicle control method according to claim 1, characterized in that, Also includes Obtain information about obstacles within a preset distance from the vehicle; The lower limit threshold and the upper limit threshold of the relaxation value are determined based on the obstacle information.

5. The vehicle control method according to any one of claims 1 to 4, characterized in that, The step of optimizing the value of the target variable according to the target constraint to obtain the target value of the target variable under the target constraint includes: The objective variable is optimized by an objective solver according to the objective constraints to obtain the objective value of the objective variable under the objective constraints; wherein the objective value is the value that minimizes the function value of the objective function.

6. A vehicle control device, characterized in that, include: The function and constraint determination module is used to determine the objective function and objective constraints based on the objective variables related to vehicle decision-making and vehicle planning; wherein, the objective variables include variables related to vehicle motion state, variables related to vehicle lane change state, variables related to obstacles, and variables related to vehicle driving area; The value optimization module is used to optimize the value of the target variable according to the target constraint, so as to obtain the target value of the target variable under the target constraint. The vehicle control module is used to control the vehicle according to the target value, so as to achieve overall optimization of vehicle decision-making and vehicle planning; The process of determining the objective function based on target variables related to vehicle decision-making and vehicle planning includes: Determine the actual distance the vehicle travels from the start time to the current time, and determine the planned distance the vehicle travels along the target navigation line from the start time to the current time. Then, determine the first target item based on the actual distance traveled and the planned distance traveled. Determine a first lateral distance between the center line of the lane where the vehicle is currently located and the target navigation line, and determine a second lateral distance between the vehicle and the lane center line. Then, determine a second target item based on the first lateral distance and the second lateral distance. A third target item is determined based on the vehicle's acceleration at the current moment; a fourth target item is determined based on the vehicle's lateral velocity at the current moment; and a fifth target item is determined based on the vehicle's target lane change value at the current moment; wherein different lane change directions correspond to different target lane change values; The sixth target item is determined based on the first lateral distance and the upper limit threshold of the first lateral distance, and the seventh target item is determined based on the target relaxation value of the target obstacle at the current time. Wherein, the target relaxation value is the sum of the first relaxation value of the target obstacle in the direction of the lane centerline and the second relaxation value of the target obstacle in the direction perpendicular to the lane centerline; The objective function is determined based on the first objective item, the second objective item, the third objective item, the fourth objective item, the fifth objective item, the sixth objective item, and the seventh objective item; Objective constraints are determined based on target variables related to vehicle decision-making and vehicle planning, including: The vehicle's lateral and longitudinal speed constraints are determined based on the vehicle's turning radius at the current moment, the distance between the vehicle's center of gravity and the rear wheel center, and the vehicle's minimum turning radius. The difference between the second lateral distance and the first lateral distance is controlled within a preset range to obtain lane change constraints; wherein, the preset range is a difference range determined based on the lane width; The target relaxation value of the target obstacle is controlled between a lower relaxation value threshold and an upper relaxation value threshold to obtain collision constraints; The lower limit threshold and the upper limit threshold of the first lateral distance are determined based on the target driving area and the target traffic rules, and the first lateral distance is controlled between the lower limit threshold and the upper limit threshold to obtain traffic rule constraints.

7. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the vehicle control method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Used to store a computer program; wherein, when the computer program is executed by a processor, it implements the vehicle control method as described in any one of claims 1 to 5.

Images