A method and system for dynamic simulation of steering performance of crawler bulldozer

Abstract

The present invention provides a method and system for dynamic simulation of steering performance of a crawler bulldozer, wherein the method comprises: based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route and the performance parameters of the crawler bulldozer, dynamic simulation of steering performance is performed to obtain simulation results; based on the simulation results, the best steering control strategy is determined; when the crawler bulldozer starts to travel on the turning route, the crawler bulldozer is subjected to corresponding steering control based on the best steering control strategy. The method and system for dynamic simulation of steering performance of a crawler bulldozer of the present invention ensure that the crawler bulldozer turns along the next turning route of the crawler bulldozer in the future with the best performance, improves the steering stability of the crawler bulldozer during operation, and improves the safety of the crawler bulldozer operation.

Description

Technical Field

[0001] The invention relates to the technical field of computer data processing, and in particular to a method and system for dynamic simulation of steering performance of a crawler bulldozer. Background Art

[0002] As one of the key types of construction machinery, crawler bulldozers are widely used in transportation, mining, farmland agriculture, water conservancy, urban and rural construction and other fields. Typical roads for crawler bulldozers include swamps, tidal flats and sandy loam. When operating on these roads, the stability of the crawler bulldozer in straight driving can be guaranteed. However, when turning, due to the high water content of these roads, the road surface may not continue to provide sufficient adhesion for the crawler bulldozer to turn, and it may slip or even roll over, seriously affecting the safety of the crawler bulldozer's operation.

[0003] Therefore, a solution is urgently needed. Summary of the invention

[0004] The present invention provides a method and system for dynamically simulating the steering performance of a crawler bulldozer. When the crawler bulldozer is operating, a dynamic simulation of the steering performance is performed based on the next turning route of the crawler bulldozer in the future, road condition information on the turning route, and performance parameters of the crawler bulldozer, and a simulation result is obtained. Based on the simulation result, an optimal steering control strategy is determined. When the crawler bulldozer starts to travel on the turning route, the crawler bulldozer is subjected to corresponding steering control based on the optimal steering control strategy, ensuring that the crawler bulldozer turns along the next turning route of the crawler bulldozer in the future with the best performance, thereby improving the steering stability of the crawler bulldozer during operation and improving the safety of the crawler bulldozer operation.

[0005] The present invention provides a method for dynamic simulation of steering performance of a crawler bulldozer, comprising:

[0006] Based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route and the performance parameters of the crawler bulldozer, a dynamic simulation of the steering performance is performed to obtain the simulation results;

[0007] Based on the simulation results, the optimal steering control strategy is determined;

[0008] When the crawler bulldozer starts to turn to the route, the crawler bulldozer is controlled accordingly based on the optimal steering control strategy.

[0009] Preferably, when performing the dynamic simulation of steering performance based on the next future turning route of the crawler bulldozer, the road condition information on the turning route and the performance parameters of the crawler bulldozer, the method further includes:

[0010] When the time for manual intervention comes, users can view the simulated entity;

[0011] When the viewing sequence of the simulated entity viewed by the user in the first time period meets the viewing sequence condition, feature extraction is performed on the visual content of the simulated entity at each first viewing angle in the viewing sequence and the attribute information of the user to obtain a plurality of feature values;

[0012] Based on each characteristic value, multiple viewing angle establishment conditions are generated;

[0013] Based on each perspective establishment condition, multiple second perspectives for viewing the simulated entity are established; each second perspective meets at least one perspective establishment condition;

[0014] In a second time period, guiding the user to view the simulated entity from each second viewing angle in sequence; the second time period is after the first time period;

[0015] When the user continuously views the simulated entity from any second viewing angle within a third time period, the user is provided with configurable simulated information corresponding to the visual content under the second viewing angle; the third time period is after the second time period;

[0016] Controlling the simulation entity to respond to simulation configuration instructions input by a user based on the configurable simulation information;

[0017] Among them, the opportunities for manual intervention include:

[0018] The remaining driving time of the turning route is greater than or equal to the time threshold;

[0019] And / or, the turning complexity jointly characterized by the turning route, the road condition information and the performance parameter is greater than or equal to a complexity threshold;

[0020] And / or, the user inputs a manual intervention request;

[0021] The view sequence conditions include:

[0022] The incremental simulation content generated by the visual simulation entity at the time of generating the i+1th first perspective under the overlapping perspective between the i+1th first perspective and the i-th perspective in the perspective sequence; i=1,2,3,…,N-1; N is the total number of first perspectives in the perspective sequence;

[0023] Furthermore, at least one pair of local perspective sequences in the perspective sequence are in reverse order.

[0024] Preferably, the generating of multiple viewing angle establishing conditions based on each characteristic value includes:

[0025] Parse multiple eigenvalue types for each eigenvalue;

[0026] Determine multiple classification rules corresponding to each feature value type from a classification rule library;

[0027] Based on each classification rule, each eigenvalue is classified to obtain multiple eigenvalue sets;

[0028] Construct the feature description vector of each eigenvalue set;

[0029] Establishing a condition library from a perspective to determine a plurality of condition items corresponding to the feature description vectors of each feature value set;

[0030] Based on each condition item, multiple perspective establishing conditions are determined; each condition item serves as a perspective establishing condition.

[0031] Preferably, determining the optimal steering control strategy based on the simulation results includes:

[0032] Analyze multiple steering performance simulation information in simulation results;

[0033] Based on the standard evaluation system, each steering performance simulation information is evaluated to obtain a performance evaluation value of each steering performance simulation information;

[0034] Determine knowledge applicable conditions of multiple strategic decision knowledge from a strategic decision knowledge base;

[0035] The optimal steering control strategy is determined based on the strategy decision knowledge corresponding to the knowledge applicable conditions that the steering performance simulation information of the maximum performance evaluation value meets.

[0036] Preferably, the crawler bulldozer steering performance dynamic simulation method further includes:

[0037] Update the road condition information on the turning route and the performance parameters of the crawler bulldozer;

[0038] Based on the next future turning route of the crawler bulldozer, the updated road condition information on the turning route and the updated performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance is re-performed.

[0039] The present invention provides a crawler bulldozer steering performance dynamic simulation system, comprising:

[0040] A simulation module is used to perform a dynamic simulation of the steering performance based on the next future turning route of the crawler bulldozer, the road condition information on the turning route, and the performance parameters of the crawler bulldozer to obtain a simulation result;

[0041] A determination module, for determining an optimal steering control strategy based on simulation results;

[0042] The control module is used to perform corresponding steering control on the crawler bulldozer based on the optimal steering control strategy when the crawler bulldozer starts to turn to the route.

[0043] Preferably, when the simulation module performs a dynamic simulation of the steering performance based on the next future turning route of the crawler bulldozer, the road condition information on the turning route, and the performance parameters of the crawler bulldozer, the simulation module also performs the following steps:

[0044] When the time for manual intervention comes, users can view the simulated entity;

[0045] When the viewing sequence of the simulated entity viewed by the user in the first time period meets the viewing sequence condition, feature extraction is performed on the visual content of the simulated entity at each first viewing angle in the viewing sequence and the attribute information of the user to obtain a plurality of feature values;

[0046] Based on each characteristic value, multiple viewing angle establishment conditions are generated;

[0047] Based on each perspective establishment condition, multiple second perspectives for viewing the simulated entity are established; each second perspective meets at least one perspective establishment condition;

[0048] In a second time period, guiding the user to view the simulated entity from each second viewing angle in sequence; the second time period is after the first time period;

[0049] When the user continuously views the simulated entity from any second viewing angle within a third time period, the user is provided with configurable simulated information corresponding to the visual content under the second viewing angle; the third time period is after the second time period;

[0050] Controlling the simulation entity to respond to simulation configuration instructions input by a user based on the configurable simulation information;

[0051] Among them, the opportunities for manual intervention include:

[0052] The remaining driving time of the turning route is greater than or equal to the time threshold;

[0053] And / or, the turning complexity jointly characterized by the turning route, the road condition information and the performance parameter is greater than or equal to a complexity threshold;

[0054] And / or, the user inputs a manual intervention request;

[0055] The view sequence conditions include:

[0056] The incremental simulation content generated by the visual simulation entity at the time of generating the i+1th first perspective under the overlapping perspective between the i+1th first perspective and the i-th perspective in the perspective sequence; i=1,2,3,…,N-1; N is the total number of first perspectives in the perspective sequence;

[0057] Furthermore, at least one pair of local perspective sequences in the perspective sequence are in reverse order.

[0058] Preferably, the simulation module generates a plurality of viewing angle establishment conditions based on each characteristic value, including:

[0059] Parse multiple eigenvalue types for each eigenvalue;

[0060] Determine multiple classification rules corresponding to each feature value type from a classification rule library;

[0061] Based on each classification rule, each eigenvalue is classified to obtain multiple eigenvalue sets;

[0062] Construct the feature description vector of each eigenvalue set;

[0063] Establishing a condition library from a perspective to determine a plurality of condition items corresponding to the feature description vectors of each feature value set;

[0064] Based on each condition item, multiple perspective establishing conditions are determined; each condition item serves as a perspective establishing condition.

[0065] Preferably, the determination module determines the optimal steering control strategy based on the simulation results, including:

[0066] Analyze multiple steering performance simulation information in simulation results;

[0067] Based on the standard evaluation system, each steering performance simulation information is evaluated to obtain a performance evaluation value of each steering performance simulation information;

[0068] Determine knowledge applicable conditions of multiple strategic decision knowledge from a strategic decision knowledge base;

[0069] The optimal steering control strategy is determined based on the strategy decision knowledge corresponding to the knowledge applicable conditions that the steering performance simulation information of the maximum performance evaluation value meets.

[0070] Preferably, the crawler bulldozer steering performance dynamic simulation system further includes:

[0071] Updated simulation module to include:

[0072] Update the road condition information on the turning route and the performance parameters of the crawler bulldozer;

[0073] Based on the next future turning route of the crawler bulldozer, the updated road condition information on the turning route and the updated performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance is re-performed.

[0074] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0075] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0077] Figure 1 It is a flow chart of a method for dynamic simulation of steering performance of a crawler bulldozer in an embodiment of the present invention;

[0078] Figure 2 It is a schematic diagram of a dynamic simulation system for steering performance of a crawler bulldozer in an embodiment of the present invention. DETAILED DESCRIPTION

[0079] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0080] The present invention provides a method for dynamic simulation of steering performance of a crawler bulldozer. Figure 1 As shown, including:

[0081] Step S1, based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route and the performance parameters of the crawler bulldozer, a dynamic simulation of the steering performance is performed to obtain a simulation result;

[0082] Step S2: determining an optimal steering control strategy based on the simulation results;

[0083] Step S3: When the crawler bulldozer starts to turn to the route, the crawler bulldozer is subjected to corresponding steering control based on the optimal steering control strategy.

[0084] When the crawler bulldozer is working, it drives along the established working route. Therefore, the next turning route of the crawler bulldozer can be obtained, which is the route on the established working route where the crawler bulldozer will need to turn. The road condition information on the turning route includes: the type of driving road surface on the turning route, the terrain profile, the predicted moisture content, etc., which can be obtained by analyzing the road surface image of the driving road surface on the turning route. The performance parameters of the crawler bulldozer include: vehicle size and weight, power configuration parameters, crawler length and width, pressure center height, maximum turning radius, etc. Based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route and the performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance is carried out. During the simulation, the multi-body dynamics simulation software Recu The tracked vehicle subsystem Track(M) of rDyn establishes a three-dimensional model of the tracked bulldozer according to the performance parameters of the tracked bulldozer, and simulates the simulated road conditions represented by the road condition information on the turning route. The simulated three-dimensional model of the tracked bulldozer travels along the next turning route of the tracked bulldozer in the simulated road conditions in various working states; the simulation results include the steering performance information of the tracked bulldozer in various working states, such as: turning radius, steering angular velocity, etc.; based on the simulation results, the best steering control strategy is determined, and the best steering control strategy is a control strategy for controlling the tracked bulldozer to turn along the next turning route of the tracked bulldozer in the future with the best performance; when the tracked bulldozer starts to travel along the turning route, the tracked bulldozer is controlled accordingly based on the best steering control strategy.

[0085] When the crawler bulldozer is operating, the present application performs a dynamic simulation of the steering performance based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route, and the performance parameters of the crawler bulldozer, obtains the simulation results, and determines the optimal steering control strategy based on the simulation results. When the crawler bulldozer starts to travel on the turning route, the crawler bulldozer is subjected to corresponding steering control based on the optimal steering control strategy to ensure that the crawler bulldozer turns along the next turning route of the crawler bulldozer in the future with the best performance, thereby improving the steering stability of the crawler bulldozer during operation and improving the safety of the crawler bulldozer operation.

[0086] In one embodiment, the dynamic simulation of steering performance based on the next future turning route of the crawler bulldozer, the road condition information on the turning route and the performance parameters of the crawler bulldozer further includes:

[0087] When the time for manual intervention comes, users can view the simulated entity;

[0088] When the viewing sequence of the simulated entity viewed by the user in the first time period meets the viewing sequence condition, feature extraction is performed on the visual content of the simulated entity at each first viewing angle in the viewing sequence and the attribute information of the user to obtain a plurality of feature values;

[0089] Based on each characteristic value, multiple viewing angle establishment conditions are generated;

[0090] Based on each perspective establishment condition, multiple second perspectives for viewing the simulated entity are established; each second perspective meets at least one perspective establishment condition;

[0091] In a second time period, guiding the user to view the simulated entity from each second viewing angle in sequence; the second time period is after the first time period;

[0092] When the user continuously views the simulated entity from any second viewing angle within a third time period, the user is provided with configurable simulated information corresponding to the visual content under the second viewing angle; the third time period is after the second time period;

[0093] Controlling the simulation entity to respond to simulation configuration instructions input by a user based on the configurable simulation information;

[0094] Among them, the opportunities for manual intervention include:

[0095] The remaining driving time of the turning route is greater than or equal to the time threshold;

[0096] And / or, the turning complexity jointly characterized by the turning route, the road condition information and the performance parameter is greater than or equal to a complexity threshold;

[0097] And / or, the user inputs a manual intervention request;

[0098] The view sequence conditions include:

[0099] The incremental simulation content generated by the visual simulation entity at the time of generating the i+1th first perspective under the overlapping perspective between the i+1th first perspective and the i-th perspective in the perspective sequence; i=1,2,3,…,N-1; N is the total number of first perspectives in the perspective sequence;

[0100] Furthermore, at least one pair of local perspective sequences in the perspective sequence are in reverse order.

[0101] The manual intervention opportunity refers to the opportunity when the user can intervene in the dynamic simulation process of steering performance; the simulation entity refers to multiple three-dimensional models of crawler bulldozer simulated driving based on the steering route, road condition information, and performance parameters, including: a crawler bulldozer three-dimensional model corresponding to the crawler bulldozer with performance parameters, a simulated driving road surface corresponding to the road condition corresponding to the road condition information, etc.; when entering the current manual intervention opportunity, the user can view the simulation entity, and the user can freely view the simulation entity. When the user views the simulation entity, a viewing perspective will be generated, and the viewing perspective forms a perspective sequence according to the viewing order; the first time period refers to an arbitrary time period of 200 seconds when the user views the simulation entity; when the perspective sequence meets the perspective sequence conditions, it means that the user wants to perform simulation configuration intervention on the simulation entity; the visual content of the simulation entity in the first perspective can be the simulation progress and simulation parameters of the simulation entity for dynamic simulation of steering performance; the user's attribute information can be the user's historical driving experience of driving a crawler bulldozer, the historical experience of manually performing dynamic simulation of steering performance of a crawler bulldozer, etc.; the visual content in each first perspective and the user's attribute information are used for feature extraction Take, obtain multiple characteristic values, generate multiple perspective establishment conditions based on each characteristic value, under the constraint of the perspective establishment conditions, the user can see the content that he wants / is capable of simulating configuration intervention when viewing the simulated entity at the created second perspective; the second time period is any time period of 100 seconds after the first time period; in the second time period, guide the user to view the simulated entity from each second perspective in turn, and when guiding, the corresponding perspective adjustment information can be displayed on the interface for the user to view the simulated entity; the third time period is any time period of 50 seconds after the second time period; when the user continues to view the simulated entity from any second perspective in the third time period, it means that the user wants to correspond to the visual content under the second perspective (the correspondence refers to the second perspective that the user continues to view the simulated entity in the third time period); the configurable simulation information is the visual content under the corresponding second perspective that can be configured with options, etc., for example, if the visual content under the corresponding second perspective is the turning radius of the three-dimensional model of the crawler bulldozer, the configurable simulation information is the size setting interface of the turning radius, etc.; the user can input simulation configuration instructions based on the configurable simulation information to control the response of the simulated entity.

[0102] At the time of manual intervention, the remaining driving time along the turning route refers to the remaining time for turning along the turning route, which can be predicted based on the distance between the current position of the crawler bulldozer and the starting point of the turning route and the driving speed of the crawler bulldozer; the time threshold can be, for example, 500 seconds; when the remaining driving time along the turning route is greater than or equal to the time threshold, it means that the user has enough time to intervene in the dynamic simulation process of steering performance; the steering complexity jointly characterized by the steering route, road condition information and performance parameters refers to the complexity of the dynamic simulation process of steering performance, for example, the longer the length of the turning route, the worse the road condition represented by the road condition information, and the worse the performance of the crawler bulldozer represented by the performance parameters, the greater the steering complexity jointly characterized by the three information. The steering complexity can be determined in advance by technical personnel by setting the steering complexity corresponding to different steering routes, road condition information and performance parameters, and it can be retrieved and determined when used; the complexity threshold can be, for example, 8; when the user enters a manual intervention request, it means that the user himself wants to intervene in the dynamic simulation process of steering performance.

[0103] In the perspective sequence conditions, the moment when the i+1th first perspective is generated refers to the moment when the user starts to view the simulated entity with the i+1th first perspective, and the incremental simulation content generated at this moment is the newly simulated change content on the simulated entity, such as the position change of the three-dimensional model of the crawler bulldozer; when the incremental simulation content of the visible simulated entity at the moment when the i+1th first perspective is generated under the overlapping perspective between the i+1th first perspective and the i-th perspective in the perspective sequence, it means that the user is tracking and viewing the latest simulation process of the simulated entity; at least one pair of local perspective sequences in the perspective sequence are in reverse order, for example, a pair of local perspective sequences are sequence A and sequence B, sequence A has perspective 1 and perspective 2 that are sorted in sequence, and sequence B has perspective 2 and perspective 1 that are to be sorted. When at least one pair of local perspective sequences in the perspective sequence are in reverse order, it means that the user has reviewed the pre-simulation state of the simulated entity. The combination of the two conditions can indicate that the user wants to re-simulate the simulated entity after changing the simulation configuration parameters.

[0104] The embodiment of the present invention first determines whether to enter the time of manual intervention. When entering, the user is allowed to view the simulation entity, thereby avoiding the user's unnecessary and ineffective intervention in the steering performance dynamic simulation process, improving rationality and being more humane; secondly, the perspective sequence condition is introduced, and whether to perform the next step of configuration perspective recommendation is determined based on whether the perspective sequence generated by the user in the first time period meets the perspective sequence condition, thereby realizing triggered configuration perspective recommendation, reducing the resources for perspective recommendation, and improving the applicability of the system; in addition, based on each characteristic value, multiple perspective establishment conditions are generated to ensure that the second perspective recommended as the configuration perspective can meet the user's actual intention, further improving the humaneness, and the user can view the configurable simulation information of the visual content under the second perspective, input the simulation configuration instructions, and complete the simulation configuration modification, thereby improving the convenience of the user's intervention in the steering performance dynamic simulation process.

[0105] In one embodiment, the generating of multiple viewing angle establishing conditions based on each characteristic value includes:

[0106] Parse multiple eigenvalue types for each eigenvalue;

[0107] Determine multiple classification rules corresponding to each feature value type from a classification rule library;

[0108] Based on each classification rule, each eigenvalue is classified to obtain multiple eigenvalue sets;

[0109] Construct the feature description vector of each eigenvalue set;

[0110] Establishing a condition library from a perspective to determine a plurality of condition items corresponding to the feature description vectors of each feature value set;

[0111] Based on each condition item, multiple perspective establishing conditions are determined; each condition item serves as a perspective establishing condition.

[0112] The characteristic value types include: the type and specific value of the above-mentioned simulation progress, the type and specific value of the simulation parameters, the experience type of the user's historical driving experience of driving a crawler bulldozer, and the experience type of the historical experience of manually performing dynamic simulation of the steering performance of a crawler bulldozer; the classification rule library has multiple classification rules corresponding to each characteristic value type, and the classification rule refers to classifying the characteristic values ​​of the characteristic value type that can jointly determine the content that the user wants / is capable of performing simulation configuration intervention into a set, for example, if the characteristic value type is the steering throttle size, the experience type of the user's historical driving experience of driving a crawler bulldozer is the steering throttle Control experience, the two types of eigenvalues ​​can be used to jointly determine that the user has the ability to reasonably determine the steering throttle, and the classification rule is to classify the eigenvalues ​​of the two types of eigenvalues ​​into a set; based on each classification rule, classify each eigenvalue to obtain multiple eigenvalue sets; construct the feature description vector of each eigenvalue set in the form of a vector; there are condition items corresponding to the feature description vector in the perspective establishment condition library, and the condition items are the eigenvalue sets that can be visually constructed into the feature description vector under the perspective and can jointly determine the conditions for the content that the user wants / is able to perform simulated configuration intervention; based on each condition item, determine multiple perspective establishment conditions.

[0113] When generating multiple perspective establishment conditions based on each feature value, the embodiment of the present invention introduces a classification rule library to quickly determine the classification rules for classifying feature values ​​of feature value types that can jointly determine the content that the user himself wants / is capable of simulating configuration intervention into a set, classifies each feature value, and constructs a feature description vector for each feature value set. The perspective establishment condition library is introduced to quickly determine the condition items to determine the perspective establishment conditions, thereby improving the rationality, accuracy and efficiency of the generation of perspective establishment conditions.

[0114] In one embodiment, determining the optimal steering control strategy based on the simulation results includes:

[0115] Analyze multiple steering performance simulation information in simulation results;

[0116] Based on the standard evaluation system, each steering performance simulation information is evaluated to obtain a performance evaluation value of each steering performance simulation information;

[0117] Determine knowledge applicable conditions of multiple strategic decision knowledge from a strategic decision knowledge base;

[0118] The optimal steering control strategy is determined based on the strategy decision knowledge corresponding to the knowledge applicable conditions that the steering performance simulation information of the maximum performance evaluation value meets.

[0119] The steering performance simulation information includes steering radius, steering angular velocity, etc., and a performance evaluation is performed on each steering performance simulation information to obtain a performance evaluation value of each steering performance simulation information. When evaluating, it can be based on a standard evaluation system pre-set by technical personnel. For example, the smaller the fluctuation of the steering angular velocity when the crawler bulldozer is turning, the smaller the steering stability is, and the higher the corresponding performance evaluation value is set; there is a large amount of experience in steering control of crawler bulldozers in the strategy decision knowledge base, namely, strategy decision knowledge. Each strategy decision knowledge is preset with a knowledge applicability condition. When the steering performance simulation information meets the knowledge applicability condition, the corresponding strategy decision knowledge can be used to determine the steering control strategy. Generally, the knowledge applicability condition of the strategy decision knowledge is set to require that the steering performance simulation information and the steering control strategy represented by the strategy decision knowledge can bring the same performance to the crawler bulldozer after implementation; the larger the performance evaluation value, the better the turning performance. The best steering control strategy is determined based on the strategy decision knowledge corresponding to the knowledge applicability condition met by the steering performance simulation information with the maximum performance evaluation value.

[0120] The embodiment of the present invention determines the optimal steering control strategy based on simulation results, performs performance evaluation on each steering performance simulation information in the simulation results, obtains the performance evaluation value of each steering performance simulation information, introduces a strategy decision knowledge base, determines the knowledge applicability conditions of multiple strategy decision knowledge from the strategy decision knowledge base, and determines the optimal steering control strategy based on the strategy decision knowledge corresponding to the knowledge applicability conditions met by the steering performance simulation information with the maximum performance evaluation value, thereby improving the accuracy and rationality of determining the optimal steering control strategy and greatly improving the applicability of the system.

[0121] In one embodiment, the method for dynamic simulation of steering performance of a crawler bulldozer further includes:

[0122] Update the road condition information on the turning route and the performance parameters of the crawler bulldozer;

[0123] Based on the next future turning route of the crawler bulldozer, the updated road condition information on the turning route and the updated performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance is re-performed.

[0124] The road condition information on the turning route and the performance parameters of the crawler bulldozer may change. Therefore, based on the next turning route of the crawler bulldozer in the future, the road condition information on the updated turning route and the updated performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance can be re-performed to re-determine the steering control strategy of the crawler bulldozer.

[0125] The present invention provides a crawler bulldozer steering performance dynamic simulation system, such as Figure 2 As shown, including:

[0126] The simulation module 1 is used to perform a dynamic simulation of the steering performance based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route and the performance parameters of the crawler bulldozer to obtain the simulation results;

[0127] A determination module 2 is used to determine an optimal steering control strategy based on the simulation results;

[0128] The control module 3 is used to perform corresponding steering control on the crawler bulldozer based on the optimal steering control strategy when the crawler bulldozer starts to turn to the route.

[0129] The simulation module 1 performs the dynamic simulation of steering performance based on the next future steering route of the crawler bulldozer, the road condition information on the steering route and the performance parameters of the crawler bulldozer, and also executes the following steps:

[0130] When the time for manual intervention comes, users can view the simulated entity;

[0131] When the viewing sequence of the simulated entity viewed by the user in the first time period meets the viewing sequence condition, feature extraction is performed on the visual content of the simulated entity at each first viewing angle in the viewing sequence and the attribute information of the user to obtain a plurality of feature values;

[0132] Based on each characteristic value, multiple viewing angle establishment conditions are generated;

[0133] Based on each perspective establishment condition, multiple second perspectives for viewing the simulated entity are established; each second perspective meets at least one perspective establishment condition;

[0134] In a second time period, guiding the user to view the simulated entity from each second viewing angle in sequence; the second time period is after the first time period;

[0135] When the user continuously views the simulated entity from any second viewing angle within a third time period, the user is provided with configurable simulated information corresponding to the visual content under the second viewing angle; the third time period is after the second time period;

[0136] Controlling the simulation entity to respond to simulation configuration instructions input by a user based on the configurable simulation information;

[0137] Among them, the opportunities for manual intervention include:

[0138] The remaining driving time of the turning route is greater than or equal to the time threshold;

[0139] And / or, the turning complexity jointly characterized by the turning route, the road condition information and the performance parameter is greater than or equal to a complexity threshold;

[0140] And / or, the user inputs a manual intervention request;

[0141] The view sequence conditions include:

[0142] The incremental simulation content generated by the visual simulation entity at the time of generating the i+1th first perspective under the overlapping perspective between the i+1th first perspective and the i-th perspective in the perspective sequence; i=1,2,3,…,N-1; N is the total number of first perspectives in the perspective sequence;

[0143] Furthermore, at least one pair of local perspective sequences in the perspective sequence are in reverse order.

[0144] The simulation module 1 generates a plurality of viewing angle establishment conditions based on each characteristic value, including:

[0145] Parse multiple eigenvalue types for each eigenvalue;

[0146] Determine multiple classification rules corresponding to each feature value type from a classification rule library;

[0147] Based on each classification rule, each eigenvalue is classified to obtain multiple eigenvalue sets;

[0148] Construct the feature description vector of each eigenvalue set;

[0149] Establishing a condition library from a perspective to determine a plurality of condition items corresponding to the feature description vectors of each feature value set;

[0150] Based on each condition item, multiple perspective establishing conditions are determined; each condition item serves as a perspective establishing condition.

[0151] The determination module 2 determines the optimal steering control strategy based on the simulation results, including:

[0152] Analyze multiple steering performance simulation information in simulation results;

[0153] Based on the standard evaluation system, each steering performance simulation information is evaluated to obtain a performance evaluation value of each steering performance simulation information;

[0154] Determine knowledge applicable conditions of multiple strategic decision knowledge from a strategic decision knowledge base;

[0155] The optimal steering control strategy is determined based on the strategy decision knowledge corresponding to the knowledge applicable conditions that the steering performance simulation information of the maximum performance evaluation value meets.

[0156] The crawler bulldozer steering performance dynamic simulation system also includes:

[0157] Updated simulation module to include:

[0158] Update the road condition information on the turning route and the performance parameters of the crawler bulldozer;

[0159] Based on the next future turning route of the crawler bulldozer, the updated road condition information on the turning route and the updated performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance is re-performed.

[0160] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for dynamic simulation of steering performance of a crawler bulldozer, characterized in that: include: Based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route and the performance parameters of the crawler bulldozer, a dynamic simulation of the steering performance is performed to obtain a simulation result; Based on the simulation results, determine the optimal steering control strategy; When the crawler bulldozer starts to turn to the route, the crawler bulldozer is controlled accordingly based on the optimal steering control strategy; Based on the next turning route of the crawler bulldozer in the future, the road condition information on the turning route and the performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance also includes: When the time for manual intervention comes, users can view the simulated entity; When the viewing sequence of the simulated entity viewed by the user in the first time period meets the viewing sequence condition, feature extraction is performed on the visual content of the simulated entity at each first viewing angle in the viewing sequence and the attribute information of the user to obtain a plurality of feature values; Based on each characteristic value, multiple viewing angle establishment conditions are generated; Based on each perspective establishment condition, multiple second perspectives for viewing the simulated entity are established; each second perspective meets at least one perspective establishment condition; In a second time period, guiding the user to view the simulated entity from each second viewing angle in sequence; the second time period is after the first time period; When the user continuously views the simulated entity from any second viewing angle within a third time period, the user is provided with configurable simulated information corresponding to the visual content under the second viewing angle; the third time period is after the second time period; Controlling the simulation entity to respond to simulation configuration instructions input by a user based on the configurable simulation information; Among them, the opportunities for manual intervention include: The remaining driving time of the turning route is greater than or equal to the time threshold; And / or, the turning complexity jointly characterized by the turning route, the road condition information and the performance parameter is greater than or equal to a complexity threshold; And / or, the user inputs a manual intervention request; The view sequence conditions include: The incremental simulation content generated by the visual simulation entity at the time of generating the i+1th first perspective under the overlapping perspective between the i+1th first perspective and the i-th first perspective in the perspective sequence; i=1, 2, 3, ..., N-1; N is the total number of first perspectives in the perspective sequence; Furthermore, at least one pair of local perspective sequences in the perspective sequence are in reverse order.

2. The method for dynamic simulation of steering performance of a crawler bulldozer according to claim 1, characterized in that: Based on each characteristic value, a plurality of viewing angle establishment conditions are generated, including: Parse multiple eigenvalue types for each eigenvalue; Determine multiple classification rules corresponding to each feature value type from a classification rule library; Based on each classification rule, each eigenvalue is classified to obtain multiple eigenvalue sets; Construct the feature description vector of each eigenvalue set; Establishing a condition library from a perspective to determine a plurality of condition items corresponding to the feature description vectors of each feature value set; Based on each condition item, multiple perspective establishing conditions are determined; each condition item serves as a perspective establishing condition.

3. The method for dynamic simulation of steering performance of a crawler bulldozer according to claim 1, characterized in that: The method of determining the optimal steering control strategy based on the simulation results includes: Analyze multiple steering performance simulation information in simulation results; Based on the standard evaluation system, each steering performance simulation information is evaluated to obtain a performance evaluation value of each steering performance simulation information; Determine knowledge applicable conditions of multiple strategic decision knowledge from a strategic decision knowledge base; The optimal steering control strategy is determined based on the strategy decision knowledge corresponding to the knowledge applicable conditions that the steering performance simulation information of the maximum performance evaluation value meets.

4. The method for dynamic simulation of steering performance of a crawler bulldozer according to claim 1, characterized in that: Also includes: Update the road condition information on the turning route and the performance parameters of the crawler bulldozer; Based on the next future turning route of the crawler bulldozer, the updated road condition information on the turning route and the updated performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance is re-performed.

5. A dynamic simulation system for steering performance of a crawler bulldozer, characterized in that: include: A simulation module is used to perform a dynamic simulation of the steering performance based on the next future turning route of the crawler bulldozer, the road condition information on the turning route, and the performance parameters of the crawler bulldozer to obtain a simulation result; A determination module, for determining an optimal steering control strategy based on simulation results; A control module, used for performing corresponding steering control on the crawler bulldozer based on an optimal steering control strategy when the crawler bulldozer starts to turn to the route; The simulation module performs dynamic simulation of steering performance based on the next steering route of the crawler bulldozer, the road condition information on the steering route and the performance parameters of the crawler bulldozer, and also executes the following: When the time for manual intervention comes, users can view the simulated entity; When the viewing sequence of the simulated entity viewed by the user in the first time period meets the viewing sequence condition, feature extraction is performed on the visual content of the simulated entity at each first viewing angle in the viewing sequence and the attribute information of the user to obtain a plurality of feature values; Based on each characteristic value, multiple viewing angle establishment conditions are generated; Based on each perspective establishment condition, multiple second perspectives for viewing the simulated entity are established; each second perspective meets at least one perspective establishment condition; In a second time period, guiding the user to view the simulated entity from each second viewing angle in sequence; the second time period is after the first time period; When the user continuously views the simulated entity from any second viewing angle within a third time period, the user is provided with configurable simulated information corresponding to the visual content under the second viewing angle; the third time period is after the second time period; Controlling the simulation entity to respond to simulation configuration instructions input by a user based on the configurable simulation information; Among them, the opportunities for manual intervention include: The remaining driving time of the turning route is greater than or equal to the time threshold; And / or, the turning complexity jointly characterized by the turning route, the road condition information and the performance parameter is greater than or equal to a complexity threshold; And / or, the user inputs a manual intervention request; The view sequence conditions include: The incremental simulation content generated by the visual simulation entity at the time of generating the i+1th first perspective under the overlapping perspective between the i+1th first perspective and the i-th first perspective in the perspective sequence; i=1, 2, 3, ..., N-1; N is the total number of first perspectives in the perspective sequence; Furthermore, at least one pair of local perspective sequences in the perspective sequence are in reverse order.

6. The crawler bulldozer steering performance dynamic simulation system according to claim 5, characterized in that: The simulation module generates a plurality of viewing angle establishment conditions based on each characteristic value, including: Parse multiple eigenvalue types for each eigenvalue; Determine multiple classification rules corresponding to each feature value type from a classification rule library; Based on each classification rule, each eigenvalue is classified to obtain multiple eigenvalue sets; Construct the feature description vector of each eigenvalue set; Establishing a condition library from a perspective to determine a plurality of condition items corresponding to the feature description vectors of each feature value set; Based on each condition item, multiple perspective establishing conditions are determined; each condition item serves as a perspective establishing condition.

7. The crawler bulldozer steering performance dynamic simulation system according to claim 5, characterized in that: The determination module determines the optimal steering control strategy based on the simulation results, including: Analyze multiple steering performance simulation information in simulation results; Based on the standard evaluation system, each steering performance simulation information is evaluated to obtain a performance evaluation value of each steering performance simulation information; Determine knowledge applicable conditions of multiple strategic decision knowledge from a strategic decision knowledge base; The optimal steering control strategy is determined based on the strategy decision knowledge corresponding to the knowledge applicable conditions that the steering performance simulation information of the maximum performance evaluation value meets.

8. The crawler bulldozer steering performance dynamic simulation system according to claim 5, characterized in that: Also includes: Updated simulation module to include: Update the road condition information on the turning route and the performance parameters of the crawler bulldozer; Based on the next future turning route of the crawler bulldozer, the updated road condition information on the turning route and the updated performance parameters of the crawler bulldozer, the dynamic simulation of the steering performance is re-performed.

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