Decision-making plan generation, evaluation methods, equipment and media based on situation analysis

Abstract

This invention proposes a method, device, and medium for generating and evaluating decision-making schemes based on situational analysis. The method for generating decision-making schemes based on situational analysis includes: acquiring environmental information; extracting a first target location from the environmental information; using the first target location as a starting point; determining the changes in a first influence range according to a first constraint condition over time to obtain the environmental situation; and making a decision based on the environmental situation to obtain a decision scheme. This invention can improve the accuracy of environmental situational analysis and the reliability of decision-making schemes.

Description

Technical Field

[0001] This invention relates to the field of situational awareness, and in particular to a method, device, and medium for generating and evaluating decision-making schemes based on situational analysis. Background Technology

[0002] In daily life, we are constantly perceiving our surroundings and making corresponding decisions. Accurately predicting the situation in our environment helps us make correct decisions. For example, in unmanned control systems, the surrounding environment is perceived to execute tasks. Summary of the Invention

[0003] This invention proposes a method, equipment, and medium for generating and evaluating decision-making schemes based on situation analysis, which helps to improve the accuracy of predicting changes in the situation and the reliability of decision-making schemes.

[0004] In a first aspect, the present invention provides a method for generating decision-making schemes based on situational analysis, comprising:

[0005] Obtain environmental information;

[0006] Extract the first target location from the environmental information, and using the first target location as the starting point, determine the changes in the first influence range according to the first constraint condition and the time process to obtain the environmental situation.

[0007] Decisions are made based on the described environmental situation, resulting in a decision-making plan.

[0008] In an optional implementation, the decision-making scheme generation method based on situational analysis, after determining the changes in the first influence range according to the first constraint condition over time, further includes:

[0009] Extract the second target location from the environmental information, and using the second target location as the starting point, determine the change of the second influence range according to the second constraint conditions over time.

[0010] The environmental situation is determined based on the changes in the first and second areas of influence.

[0011] In an optional implementation, the decision-making scheme generation method based on situational analysis, wherein determining the change of the first influence range according to the first constraint condition and the first target location as the starting point over time includes:

[0012] Based on the first constraint and the time period, determine one or more valid movement paths and calculate the probability of each valid movement path.

[0013] Obtain the initial influence range, and determine the first influence range and influence degree based on the effective movement path, the probability of the effective movement path, and the initial influence range;

[0014] The coordinates of the initial influence range satisfy the calculation formula:

[0015] [(x-x0) 2 +(y-y0) 2 ]≤ρ1r+ρ2vcosθ

[0016] x and y are the x and y coordinates of a position in the scene, x0 and y0 are the x and y coordinates of the current position of the target object, ρ1 and ρ2 are the first and second coefficients used to adjust the ratio between r and vcosθ, r is a preset value and is related to the performance attributes of the target object. v is the velocity of the target object, and θ is the angle between the velocity of the target object and the line containing the position (x, y) and the position (x0, y0).

[0017] In an optional implementation, the decision-making scheme generation method based on situational analysis, wherein determining one or more effective movement paths based on a first constraint and a time period, and calculating the probability of each effective movement path, includes:

[0018] Obtain multiple candidate movement paths connected to the first target location;

[0019] Extract the performance parameters of the target object from the first constraint condition, and select one or more candidate movement paths from the multiple candidate movement paths based on the performance parameters of the target object to obtain the effective movement path;

[0020] Based on the target object's speed and the attribute information of the effective movement path, obtain the target object's movement loss and the path value of the current effective movement path;

[0021] Calculate the probability of each effective movement path based on the target object's movement loss and the path value of the current effective movement path;

[0022] The probability of an effective movement path is calculated as follows: p = λe αa-βb

[0023] p is the probability of an effective movement path, λ is the normalization coefficient, a is the path value of the current effective movement path, b is the movement loss, and α and β are the first and second coefficients, respectively.

[0024] In an optional implementation, the decision-making scheme generation method based on situational analysis, wherein obtaining the path value of the currently effective movement path includes:

[0025] A preset number of location points are randomly obtained on the current valid movement path to obtain sampling points;

[0026] Calculate the value density of each sampling point, wherein the value density is negatively correlated with the value distance, and the value distance is the distance between the current sampling point and the value center;

[0027] The path value of the current effective movement path is obtained by summing the value densities of each sampling point.

[0028] In an optional implementation, the decision-making scheme generation method based on situational analysis, wherein making a decision based on the environmental situation and executing the decision includes:

[0029] Based on the probability of effective movement paths in the described environmental situation, target areas with a cumulative occurrence probability greater than or equal to a preset probability are obtained.

[0030] Plan a decision path that is close to or far from the target area, and move according to the decision path.

[0031] Secondly, the present invention provides a control method, comprising:

[0032] Obtain the decision scheme generated by the situation analysis-based decision scheme generation method described above;

[0033] Movement control is performed according to the aforementioned decision-making scheme.

[0034] Thirdly, the present invention provides a performance evaluation method, comprising:

[0035] Obtain the decision scheme generated by the situation analysis-based decision scheme generation method described above;

[0036] The effectiveness is evaluated based on the number of decision options.

[0037] Fourthly, the present invention provides an electronic device including a memory and a processor, wherein the memory stores a computer program executable on the processor, wherein when the processor executes the program, it implements the steps of the situation analysis-based decision-making scheme generation method as described above, or the steps of the control method as described above, or the steps of the performance evaluation method as described above.

[0038] Fifthly, the present invention provides a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the situation analysis-based decision-making scheme generation method as described above, or the steps of the control method as described above, or the steps of the performance evaluation method as described above.

[0039] The decision-making scheme generation method based on situational analysis of the present invention can extract the first target location from the environmental information, take the first target location as the starting point, and constrain the change of the first influence range through the first constraint condition, so that the first influence range evolves according to the constraint requirements, thereby obtaining the change of the first influence range over time, thereby predicting the environmental situation over a period of time, which is conducive to a comprehensive analysis of the environmental situation and improves the reliability of the decision-making scheme. Attached Figure Description

[0040] Various other advantages and benefits of the present invention will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0041] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0042] Figure 1 This is a flowchart of a decision scheme generation method based on situational analysis according to an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of sampling the current valid movement path according to an embodiment of the present invention;

[0044] Figure 3 This is a schematic diagram of the structure of a decision-making scheme generation system based on situational analysis according to an embodiment of the present invention;

[0045] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention.

[0046] Figure 5 The figure shows the simulation test results of one embodiment of the present invention. Detailed Implementation

[0047] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0049] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0050] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0051] Example 1

[0052] In a vehicle navigation scenario, it is necessary to perceive the surrounding environment. Therefore, this embodiment provides a decision-making scheme generation method based on situational analysis. This method can be applied to mobile devices such as smartphones and laptops, as well as fixed devices such as desktop computers and televisions, to perform situational analysis of the surrounding environment and assist users in making decisions.

[0053] Figure 1 This is a flowchart illustrating the decision-making scheme generation method based on situational analysis in this implementation. Please refer to [link / reference]. Figure 1 The present invention provides a method for generating decision schemes based on situational analysis, which includes steps 10, 20 and 30.

[0054] Step 10: Obtain environmental information.

[0055] Environmental information refers to information that can be used for situational analysis. Examples include the location and speed of target vehicles.

[0056] Step 20: Extract the location of the first target from the environmental information. Using the location of the first target as the starting point, determine the changes in the first area of ​​influence according to the first constraint conditions over time to obtain the environmental situation.

[0057] Optionally, the first target location is the location of the target object at the current time point. For example, the first target location is the location of the target vehicle at the current time point.

[0058] According to the time sequence, it refers to the chronological order of events. The first constraint condition is a condition that constrains the change of the first influence range, enabling the first influence range to change according to certain requirements to simulate the influence range generated by the actual target object. For example, based on the speed of the target vehicle, an area is demarcated around the target vehicle, which is designated as a danger zone. Objects in the danger zone have a relatively high probability (danger probability greater than or equal to a preset threshold) of colliding with the target vehicle.

[0059] Understandably, the primary area of ​​influence changes as the target object moves. Therefore, predicting the primary area of ​​influence helps improve the reliability of decision-making.

[0060] Step 30: Make a decision based on the environmental situation and obtain a decision plan.

[0061] Decision-making schemes are based on situational analysis of the surrounding environment and represent responses to environmental information. Their reliability directly impacts mission success. Decision-making schemes can be used to evaluate equipment performance and to execute tasks.

[0062] The decision-making options can be a movement plan that moves closer to the first area of ​​influence, such as approaching and entering the first area of ​​influence; or a movement plan that moves further away from the first area of ​​influence.

[0063] The decision-making scheme generation method based on situational analysis in this embodiment can extract the first target location from the environmental information, use the first target location as the starting point, and constrain the change of the first influence range through the first constraint condition, so that the first influence range evolves according to the constraint requirements, thereby obtaining the change of the first influence range over time, thus predicting the environmental situation over a period of time, which is conducive to a comprehensive analysis of the environmental situation and improves the reliability of the decision-making scheme.

[0064] In an optional implementation, the decision-making scheme generation method based on situational analysis further includes steps 201 and 202 after determining the changes in the first influence range according to the first constraint condition over time.

[0065] Step 201: Extract the location of the second target from the environmental information. Using the location of the second target as the starting point, determine the changes in the second influence range according to the second constraint conditions over time.

[0066] There can be multiple target objects for environmental information, corresponding to multiple target locations. The first and second target locations mentioned above are just examples.

[0067] Step 202: Based on the changes in the first and second areas of influence, obtain the environmental situation.

[0068] By predicting and superimposing the impact range of multiple target objects, the environmental situation can be obtained.

[0069] In one embodiment, a decision-making scheme generation method based on situational analysis includes steps 211 and 212, which take the first target location as the starting point and determine the change of the first influence range according to the first constraint condition over time.

[0070] Step 211: Based on the first constraint and the time period, determine one or more valid movement paths and calculate the probability of each valid movement path.

[0071] In the process of situational analysis and prediction, effective movement paths are determined and the probability of each effective movement path is calculated. This allows for the prediction of the target's location at future time points and the assessment of the probability of the target appearing at that location. The time interval between time points is called a time period.

[0072] The first constraint includes the performance parameters of the target object. Based on these parameters, one or more valid movement paths can be determined, and the probability of each valid movement path can be calculated. For example, if the target object is a vehicle, the vehicle's adaptability can be used to determine which road surfaces it can travel on. Then, based on the vehicle's speed performance, the furthest position the vehicle can reach within a time period can be determined, thus obtaining the valid movement path. The probability of each valid movement path is calculated based on the target object's goals, capabilities, and preferences.

[0073] The probability of a valid movement path is used to evaluate the likelihood that a target object will appear on that valid movement path. The higher the probability of a valid movement path, the more likely the target object is to appear on that path.

[0074] Step 212: Obtain the initial influence range. Based on the effective movement path, the probability of the effective movement path, and the initial influence range, determine the first influence range and the degree of influence.

[0075] Based on the effective movement paths and the probabilities of each effective movement path, the probability of the target object appearing on each effective movement path can be determined. The first influence range is obtained by superimposing the initial influence ranges corresponding to each effective movement path at the current time point, or by varying the coverage area formed by moving the initial influence range along the effective paths according to the target object's movement.

[0076] The impact degree of the corresponding location is then determined based on the probability of an effective movement path. For example, the impact degree is directly proportional to the probability of an effective movement path. The impact degree is used to predict the extent of the impact that location may have.

[0077] Optionally, the coordinates of the initial influence range satisfy the calculation formula:

[0078] [(x-x0) 2 +(y-y0) 2 ]≤ρ1r+ρ2vcosθ

[0079] Where x and y are the x and y coordinates of a position on the effective path, x0 and y0 are the x and y coordinates of the current position of the target object, and ρ1 and ρ2 are the first and second coefficients used to adjust the ratio between r and vcosθ. r is a preset value related to the performance attributes of the target object. v is the velocity of the target object, and θ is the angle between the velocity of the target object and the straight line containing positions (x, y) and (x0, y0).

[0080] This formula is merely an example used to simulate the relationship between the range of influence and the speed of the target object.

[0081] In one embodiment, a decision-making scheme generation method based on situational analysis is provided, wherein one or more effective movement paths are determined according to a first constraint and a time period, and the probability of each effective movement path is calculated, including steps 221, 222, 223, and 224.

[0082] Step 221: Obtain multiple candidate movement paths connected to the first target location.

[0083] For example, there are 5 routes to the first target location.

[0084] Step 222: Extract the performance parameters of the target object from the first constraint condition, and select one or more candidate movement paths from multiple candidate movement paths based on the performance parameters of the target object to obtain the effective movement path.

[0085] The performance parameters of the target object under the first constraint include the requirement that the target object needs to travel on the road. Therefore, four routes that meet the requirements are selected from five routes to the first target location to obtain an effective movement path.

[0086] Step 223: Based on the target object's speed and the attribute information of the effective movement path, obtain the target object's movement loss and the path value of the current effective movement path.

[0087] Mobility loss refers to the negative impact of movement on a target object, such as fuel consumption, cost, and distance.

[0088] Path value refers to the positive impact of movement on a target object, and is typically related to preferences. For example, path value is related to the smoothness of the road surface, preferred amenities, and other things or objects that attract the target object.

[0089] Step 224: Calculate the probability of each effective movement path based on the movement loss of the target object and the path value of the current effective movement path.

[0090] The probability of an effective movement path is negatively correlated with movement loss and positively correlated with path value. Optionally, the probability of an effective movement path is calculated as: p = λe αa-βb

[0091] p represents the probability of an effective movement path, λ is the normalization coefficient, a is the path value of the current effective movement path, b is the movement loss, and α and β are the first and second coefficients, respectively. The normalization coefficient is used to adjust the sum of probabilities of all possible scenarios for the current node to 1. The first and second coefficients can be determined by inductive reasoning from historical data.

[0092] In one embodiment, the decision-making scheme generation method based on situational analysis includes obtaining the path value of the current effective movement path, which includes steps 231, 232, and 233.

[0093] Step 231: Randomly obtain a preset number of location points on the current valid movement path to obtain sampling points.

[0094] like Figure 2 As shown, a preset number of location points are randomly obtained on the current valid movement path 501 to obtain sampling point 502.

[0095] In addition, sampling is performed at preset intervals to obtain a preset number of sampling points.

[0096] Step 232: Calculate the value density of each sampling point. The value density is negatively correlated with the value distance, which is the distance between the current sampling point and the value center.

[0097] Value density can be used to measure the attractiveness of the current sampling point to the target object. In some scenarios, things that can attract the target object (things that can attract the target object are valuable objects or things) are not uniformly distributed in space, and are related to the distance of the valuable object. Generally, the closer to the valuable object, the higher the value density. That is, value density is negatively correlated with value distance, which is the distance between the current sampling point and the value center.

[0098] Step 233: Add up the value densities of each sampling point to obtain the path value of the current effective movement path.

[0099] When making movement path decisions, the movement path can be divided into segments, and the path value of each effective movement path segment can be calculated separately. For example, the path value of each effective movement path segment can be calculated separately by adding the value densities of each sampling point.

[0100] In one embodiment, a decision-making scheme generation method based on situational analysis is provided, wherein making a decision based on the environmental situation and executing the decision includes: steps 301 and 302.

[0101] Step 301: Based on the probability of effective movement paths in the environmental situation, obtain the target area whose cumulative occurrence probability is greater than or equal to the preset probability.

[0102] In some scenarios, certain local areas have a higher probability of valid movement paths, while most areas have a lower probability. Therefore, these areas with higher probabilities of valid movement paths are extracted, and then the target area is obtained based on the movement patterns of the target object. Optionally, the probability of valid movement paths can be directly used as the probability of the target object appearing at the current moment. It can be understood that the target area is the region where the target object is likely to appear.

[0103] Step 302: Plan a decision path that is close to or far from the target area, and move according to the decision path.

[0104] In some scenarios, when a task requires meeting or encountering a target object, a decision path is planned to approach the target area. When a task requires escaping the target object, a decision path is planned to move away from the target area. Once the decision path is planned, movement is performed according to the decision path to complete the corresponding task. There are many methods for planning decision paths, which will not be exemplified here.

[0105] Example 2

[0106] The present invention provides a control method, including: step 410 and step 420.

[0107] Step 410: Obtain the decision scheme generated by the above situation analysis-based decision scheme generation method.

[0108] In a specific scenario, the decision-making scheme is a decision path. The decision path is generated according to the decision-making scheme generation method in Example 1. However, practical application scenarios are not limited to this.

[0109] Step 420: Perform movement control according to the decision plan.

[0110] In specific scenarios, control is achieved by combining various sensors to implement decision-making schemes, such as motion control.

[0111] Example 3

[0112] The present invention provides a performance evaluation method, which includes steps 430 and 440.

[0113] Step 430: Obtain the decision scheme generated by the above situation analysis-based decision scheme generation method.

[0114] In a specific scenario, the decision-making scheme is a decision path. The decision path is generated according to the decision-making scheme generation method in Example 1. However, practical application scenarios are not limited to this.

[0115] In performance evaluation methods, the decision-making options are all feasible (with evaluation criteria) options, therefore there can be multiple decision-making options. For example, to achieve access to a target area, multiple paths can be planned, resulting in multiple decision-making options.

[0116] Step 440: Evaluate the effectiveness based on the number of decision options.

[0117] Generally speaking, the more decision-making options there are, the stronger the feasibility and adaptability of the implementing entity, and the higher its effectiveness score.

[0118] Example 4

[0119] Figure 3 This is a schematic diagram of the structure of a situation analysis-based decision-making scheme generation system 60 in this embodiment, as shown below. Figure 3 As shown, the decision-making scheme generation system 60 based on situational analysis includes: an acquisition module 601, a determination module 602, and a generation module 603.

[0120] The acquisition module 601 is used to acquire environmental information.

[0121] The determination module 602 is used to extract the first target location from the environmental information, and using the first target location as the starting point, determine the changes in the first influence range according to the first constraint conditions in accordance with the time process to obtain the environmental situation.

[0122] The decision-making module is used to make decisions based on the environmental situation and obtain decision solutions.

[0123] The situation analysis-based decision generation system 60 of this embodiment can extract the first target location from the environmental information, use the first target location as the starting point, and constrain the change of the first influence range through the first constraint condition, so that the first influence range evolves according to the constraint requirements, thereby obtaining the change of the first influence range over time, thus predicting the environmental situation over a period of time, which is conducive to a comprehensive analysis of the environmental situation and improves the reliability of the decision-making scheme.

[0124] In one embodiment, the determining module 602 is further configured to extract the second target location from the environmental information, take the second target location as the starting point, determine the change of the second influence range according to the second constraint conditions in accordance with the time process, and obtain the environmental situation based on the change of the first influence range and the change of the second influence range.

[0125] In one embodiment, the determining module 602 is further configured to determine one or more valid movement paths based on the first constraint and the time period, and calculate the probability of each valid movement path; obtain the initial influence range, and determine the first influence range and the degree of influence based on the valid movement paths, the probability of the valid movement paths, and the initial influence range.

[0126] In one embodiment, the determining module 602 is further configured to: acquire multiple candidate movement paths connected to the first target location; extract the performance parameters of the target object from the first constraint conditions; select one or more of the candidate movement paths based on the performance parameters of the target object to obtain an effective movement path; acquire the movement loss of the target object and the path value of the current effective movement path based on the speed of the target object and the attribute information of the effective movement path; and calculate the probability of each effective movement path based on the movement loss of the target object and the path value of the current effective movement path.

[0127] In one embodiment, the determining module 602 is further configured to randomly obtain a preset number of location points on the current effective movement path to obtain sampling points; calculate the value density of each sampling point, wherein the value density is negatively correlated with the value distance, and the value distance is the distance between the current sampling point and the value center; and add the value densities of each sampling point to obtain the path value of the current effective movement path.

[0128] In one embodiment, the decision module is further configured to obtain a target area whose cumulative occurrence probability is greater than or equal to a preset probability based on the probability of an effective movement path in the environmental situation; plan a decision path that is close to or far from the target area; and move according to the decision path.

[0129] The situation analysis-based decision-making scheme generation system 60 in this embodiment is a system corresponding to the situation analysis-based decision-making scheme generation method. The operating principle of the situation analysis-based decision-making scheme generation system 60 can be referred to the aforementioned situation analysis-based decision-making scheme generation method, and will not be repeated here.

[0130] Example 5

[0131] Figure 4This is a schematic diagram of the structure of an electronic device according to the present invention. The electronic device includes a memory 701 and a processor 702. The memory 701 stores a computer program that can run on the processor 702. When the processor 702 executes the program, it implements the steps of the above-mentioned situation analysis-based decision-making scheme generation method, or the steps of the above-mentioned control method, or the steps of the above-mentioned performance evaluation method.

[0132] The electronic device includes a memory 701 and a processor 702 that are interconnected via a system bus 703. It should be noted that only an electronic device with components 701-703 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components may be implemented instead. Those skilled in the art will understand that the electronic device described herein is one capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0133] Electronic devices can be computing devices such as desktop computers, laptops, PDAs, and cloud servers. These devices can interact with users through keyboards, mice, remote controls, touchpads, or voice-activated devices.

[0134] The memory 701 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 701 may be an internal storage unit of the device, such as the hard disk or memory of the device. In other embodiments, the memory 701 may also be an external storage device of the device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on the device. Of course, the memory 701 may also include both internal storage units and external storage devices of the device. In this embodiment, the memory 701 is typically used to store the operating system and various application software installed on the device. In addition, the memory 701 may also be used to temporarily store various types of data that have been output or will be output.

[0135] In some embodiments, the processor may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor is typically used to control the overall operation of the device. In this embodiment, the processor is used to execute computer-readable instructions stored in memory or to process data.

[0136] Example 6

[0137] The present invention provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described situation analysis-based decision-making scheme generation method, or the steps of the above-described control method, or the steps of the above-described performance evaluation method.

[0138] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this application.

[0139] Example 7

[0140] The situational analysis-based decision generation scheme provides a route planning platform. This platform takes the probability of an effective movement path in the environmental situation as input, predicts and judges the position of the target vehicle on the map in the future time period, plans the movement path of the current vehicle according to the predicted position so that the current vehicle meets the target vehicle, and evaluates and improves the route planning platform by the meeting time.

[0141] In the route planning platform simulation test, Scheme 1 and Scheme 2 were compared. Scheme 1 plans the current vehicle's path based on the predicted location, while Scheme 2 plans the current vehicle's path based on the real-time location. Multiple tests were conducted with target vehicles at different maximum speeds, and the simulation test results are as follows. Figure 5 As shown.

[0142] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A method for generating decision-making schemes based on situational analysis, characterized in that, include: Obtain environmental information; Extract the first target location from the environmental information, and using the first target location as the starting point, determine the changes in the first influence range according to the first constraint condition and the time process to obtain the environmental situation. Based on the described environmental situation, a decision-making plan is obtained; The step of determining the change of the first influence range based on the first constraint condition and taking the first target location as the starting point according to the time process includes: Based on the first constraint and the time period, determine one or more valid movement paths and calculate the probability of each valid movement path. Obtain the initial influence range, and determine the first influence range and influence degree based on the effective movement path, the probability of the effective movement path, and the initial influence range; The coordinates of the initial influence range satisfy the calculation formula: [(x-x0) 2 +(y-y0) 2 ]≤ρ1r+ρ2vcosθ x and y are the x and y coordinates of a position in the scene, x0 and y0 are the x and y coordinates of the current position of the target object, ρ1 and ρ2 are the first and second coefficients used to adjust the ratio between r and vcosθ, r is a preset value that is related to the performance attributes of the target object, v is the velocity of the target object, and θ is the angle between the velocity of the target object and the line containing the position (x, y) and the position (x0, y0). The step of determining one or more valid movement paths based on the first constraint and the time period, and calculating the probability of each valid movement path, includes: Obtain multiple candidate movement paths connected to the first target location; Extract the performance parameters of the target object from the first constraint condition, and select one or more candidate movement paths from the multiple candidate movement paths based on the performance parameters of the target object to obtain the effective movement path; Based on the target object's speed and the attribute information of the effective movement path, obtain the target object's movement loss and the path value of the current effective movement path; Calculate the probability of each effective movement path based on the target object's movement loss and the path value of the current effective movement path; The probability of an effective movement path is calculated as follows: p = λe αa-βb p is the probability of an effective movement path, λ is the normalization coefficient, a is the path value of the current effective movement path, b is the movement loss, and α and β are the first and second coefficients, respectively. Obtaining the path value of the currently valid mobile path includes: A preset number of location points are randomly obtained on the current valid movement path to obtain sampling points; Calculate the value density of each sampling point, wherein the value density is negatively correlated with the value distance, and the value distance is the distance between the current sampling point and the value center; The path value of the current effective movement path is obtained by summing the value densities of each sampling point.

2. The decision-making scheme generation method based on situational analysis according to claim 1, characterized in that, After determining the changes in the first scope of influence according to the first constraint condition over time, the method further includes: Extract the second target location from the environmental information, and using the second target location as the starting point, determine the change of the second influence range according to the second constraint conditions over time. The environmental situation is determined based on the changes in the first and second areas of influence.

3. The decision-making scheme generation method based on situational analysis according to claim 1, characterized in that, Making and executing decisions based on the environmental situation includes: Based on the probability of effective movement paths in the described environmental situation, target areas with a cumulative occurrence probability greater than or equal to a preset probability are obtained. Plan a decision path that is close to or far from the target area, and move according to the decision path.

4. A control method, characterized in that, include: Obtain the decision scheme generated by the situation analysis-based decision scheme generation method as described in any one of claims 1 to 3; Movement control is performed according to the aforementioned decision-making scheme.

5. A performance evaluation method, characterized in that, include: Obtain the decision scheme generated by the situation analysis-based decision scheme generation method as described in any one of claims 1 to 3; The effectiveness is evaluated based on the number of decision options.

6. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the decision-making scheme generation method based on situational analysis as described in any one of claims 1 to 3, or the steps of the control method as described in claim 4, or the steps of the performance evaluation method as described in claim 5.

7. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the decision-making scheme generation method based on situational analysis as described in any one of claims 1 to 3, or the steps of the control method as described in claim 4, or the steps of the performance evaluation method as described in claim 5.

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