CN-122027654-A - IVCPS confirmation method based on multidimensional mapping mechanism

CN122027654ACN 122027654 ACN122027654 ACN 122027654ACN-122027654-A

Abstract

The invention belongs to the technical field of intelligent network connection automobile network physical systems, and discloses a IVCPS confirmation method based on a multidimensional mapping mechanism, which comprises the following steps of S1, constructing a demand analysis model, extracting IVCPS a demand body, a demand element and an association relation of a typical reference system prototype, S2, constructing a mapping function based on depth fusion characteristics of IVCPS physical space and information space, mapping the demand body in the S1 into a quantifiable index system, S3, constructing an information physical multidimensional consistency assessment model, realizing self-adaption matching and dynamic correction of a consistency weight matrix, S4, calling the self-adaption consistency weight matrix, executing dimensional consistency assessment on the index system, and finally realizing integral confirmation of the IVCPS typical reference system prototype based on weighted convergence judgment of each dimensional consistency result. The invention realizes progressive full-element confirmation of system prototype function, logic and performance, and provides scientific basis for the systematic verification of IVCPS.

Inventors

LIN JINGDONG
LI JINRUI
SU XIN
LI LONG
CHEN TINGTING
LI ZIHANG
GUO XIANGYU

Assignees

重庆大学

Dates

Publication Date: 20260512
Application Date: 20260211

Claims (6)

1. IVCPS confirmation method based on multidimensional mapping mechanism, which is characterized by comprising the following steps: s1, constructing a multi-view and domain ontology-based demand analysis model, namely adopting a multi-view-based interest-holder demand, application scene demand and functional demand extraction method, and extracting IVCPS a demand ontology, a demand element and an association relation of a typical reference system prototype by combining domain ontology knowledge and AI-enhanced cross-domain knowledge graph analysis technology; s2, executing a multi-scale, multi-level and multi-main body three-dimensional mapping mechanism, namely establishing a mapping function based on depth fusion characteristics of IVCPS physical space and information space, and mapping the demand ontology in the step S1 into a quantifiable index system; The index system comprises a multi-scale functional index, a multi-level logic index and a multi-main body functional and performance index; S3, constructing an information physical multidimensional consistency assessment model, namely identifying element combinations and random element appearances under multiple traffic conditions, and realizing self-adaptive matching and dynamic correction of a consistency weight matrix through an information physical multidimensional consistency assessment method; S4, executing a multidimensional progressive overall confirmation process, namely calling the adaptive coincidence weight matrix in the step S3 under the multi-traffic working condition environment, executing the dimensionality coincidence assessment on the index system generated by the mapping in the step S2, and finally, based on the weighted convergence judgment of the coincidence results of all the dimensionalities, realizing IVCPS the overall confirmation of the typical reference system prototype.
2. The method of IVCPS validation based on a multidimensional mapping mechanism according to claim 1, wherein said step S1 comprises the sub-steps of: S1.1, multi-view requirement extraction; Synchronously acquiring direct participant demand, treatment party demand, technology provider demand and derivative service party demand from stakeholders, urban road scene demand, expressway scene demand and other scene demands from application scenes, and fusion perception function demand, collaborative decision function demand and collaborative control function demand from functions S1.2, analyzing the demand elements and constructing an ontology; the field ontology knowledge is utilized to carry out standardized modeling and expression on the multi-view requirements, and various requirement concepts and attributes of IVCPS are defined; S1.3, knowledge graph completion and association analysis; An AI-enhanced cross-domain knowledge graph analysis technology is introduced, logic conflict and implicit semantic association between cross-domain visual angles and cross-domain requirements are identified and completed, and a requirement body, a requirement element and an association relation knowledge network of a typical reference system prototype are extracted and output IVCPS.
3. The IVCPS confirmation method based on the multidimensional mapping mechanism according to claim 2, wherein in step S2, the specific contents of the multidimensional mapping mechanism are as follows: Multiscale mapping using mapping functions Mapping the demand into a multi-scale function covering road network scale, road segment scale and vehicle-around scale, wherein, Is a multi-scale functional comprehensive compliance index, For each scale demand function, representing the function satisfaction corresponding to the demand R under the ith scale, Is the scale weight; Multi-level mapping using logical mapping models The requirements are mapped to multi-level logic covering the vehicle Lu Yun level, the road level, and the vehicle level, where, For a multi-level logical consistency assessment result, For the hierarchical logic coupling of operators, The interactive logic functions respectively correspond to the vehicle road cloud level, the vehicle road level and the vehicle level; Multi-body mapping using comprehensive performance mapping matrix Mapping the requirements to multi-body functions and performance indexes covering the cloud end, the road end and the vehicle end, wherein, For a multi-subject compliance assessment vector, To reflect the synergistic effect matrix of physical synergy and information interaction relationship between heterogeneous bodies, And the performance mapping vectors respectively represent the cloud end, the road end and the vehicle end.
4. The IVCPS confirmation method based on the multidimensional mapping mechanism according to claim 3, wherein in step S3, the adaptive matching logic of the coincidence weight coefficient specifically includes: s3.1, decoupling working condition elements and extracting features; disassembling multiple traffic conditions into road component attributes Environment component attributes Traffic flow component attributes Multiple traffic condition feature sets Recognizing the random element emerging state caused by environmental openness in real time, converting the random element emerging state into a working condition characteristic vector, and inputting the working condition characteristic vector into an evaluation model; S3.2, constructing a dynamic scale judgment matrix; According to the working condition characteristic set Invoking a preset scale transformation rule to generate a dynamic scale judgment matrix Wherein the element is Representing the index under the current working condition Relative to the index Is a ratio of importance levels of (a); s3.3, self-adaptive weight solving; Solving self-adaptive coincidence weight matrix by utilizing characteristic root method The calculation formula is as follows: In the formula, Is a matrix Is the maximum eigenvalue of (2); To correspond to Is normalized to be used as a final self-adaptive coincidence weight matrix; S3.4, dynamically correcting and coupling the weight; the weight is optimized by using a working condition correction operator, and the complete expression formula is as follows: ; In the formula, Initial weight vectors for elements defined by the demand ontology of step S1; Is Hadamard product; The current working condition is calculated by a concentration mechanism as a working condition influence factor matrix And the demand body The strength of the association between them; is a normalization function.
5. The IVCPS confirmation method based on the multidimensional mapping mechanism according to claim 4, wherein the specific contents of step S4 are as follows: s4.1, multi-scale function confirmation: Dividing IVCPS typical reference system prototype multi-scale functions into road network scale functions, road section scale functions and Zhou Che scale functions, injecting test vectors under the multi-traffic working condition, collecting functional response data under each scale in real time, and calling the self-adaptive coincidence weight matrix generated in the step S3 Comparing the measured data with a preset functional boundary value in the requirement body in the step S1, calculating a weighted functional deviation vector, and summarizing to generate a multi-scale functional compliance confirmation result; S4.2 multi-level logic validation: Dividing IVCPS typical reference system prototype multi-level logic into vehicle-road cloud level logic, vehicle-road level logic and vehicle-vehicle level logic, establishing a logic constraint model based on a time automaton or formal language, formally modeling interaction time sequences and communication logic of each level, respectively evaluating logic compliance of each level under multiple traffic conditions, and combining the self-adaptive compliance weight matrix described in step S3 Determining whether the system operation time sequence logic violates the association relation constraint in the demand body by utilizing a consistency detection operator, and summarizing to generate a multi-level logic consistency confirmation result; s4.3, multi-main body function and performance confirmation: Dividing IVCPS typical reference system prototype main bodies into cloud end, road end and vehicle end, setting performance standard covering calculation time delay, perception precision and execution reliability, and applying the self-adaptive coincidence weight matrix in step S3 under multiple traffic conditions Dynamically weighting the performance index of each subject, utilizing the synergistic effect matrix Analyzing performance damage among heterogeneous subjects in the physical coordination and information exchange process, quantitatively evaluating contribution degree of each subject to the overall target of the system, and summarizing to generate a multi-subject compliance confirmation result; S4.4 overall confirmation: summarizing the dimensionality compliance assessment scores of the steps S4.1 to S4.3, and establishing a demand-based ontology Is an overall evaluation function of (2) Comparing the comprehensive score with a qualified threshold preset by the demand ontology in the step S1, and if the judgment condition is met, realizing IVCPS integral confirmation of the typical reference system prototype; In the formula, The overall importance coefficient is used for adjusting the weights of three dimensions of the scale, the hierarchy and the main body in the overall evaluation; the overall evaluation function value is the final integrated score of the multi-dimensional consistency evaluation, and the integrated confirmation score is used for evaluating the multi-dimensional consistency Qualified threshold preset with demand body Comparing, if And each key performance index meets the safety envelope constraint, then the typical reference system prototype of IVCPS is determined through the whole element overall confirmation, and a final confirmation report is output.
6. A computer-readable storage medium storing a computer program, wherein the computer program is configured to implement the method according to any one of claims 1 to 5 when executed by a processor.

Description

IVCPS confirmation method based on multidimensional mapping mechanism Technical Field The invention belongs to the technical field of intelligent network-connected automobile network physical systems, and particularly relates to a IVCPS confirmation method based on a multidimensional mapping mechanism. The method realizes systematic confirmation of the functional compliance, the logical compliance and the main body performance of IVCPS prototypes under complex dynamic traffic conditions through multi-view demand analysis and multi-dimensional mapping mechanisms, and belongs to the technical category of automatic driving and intelligent traffic system verification and evaluation. Background In recent years, architecture design and prototype development of intelligent network-connected automobile network physical system (IVCPS) become research hot spots in the intelligent traffic field. However, the conventional system confirmation method has the problems that the evaluation dimension is single and complex association relation is difficult to cover, and the consistency judgment is generally carried out only based on a single functional index, so that the deconstructment of the depth fusion characteristics of the physical space and the information space is lacking. In the conventional method, when facing to IVCPS typical reference system prototypes, the requirement ontology, the requirement elements and the multi-level and multi-main-body characteristics presented by the association relation of the requirement ontology and the requirement elements are difficult to effectively process, so that serious defects exist in the completeness of the confirmation process, and particularly in a random emerging scene of multi-traffic condition interweaving, an evaluation mechanism with fixed weight cannot adapt to a dynamic environment. Aiming at the technical pain point that the integrity of IVCPS is difficult to be integrally confirmed, the invention designs an integral confirmation method based on a multidimensional mapping mechanism, and realizes progressive full-element confirmation of the system prototype function, logic and performance by constructing a required knowledge graph, executing three-dimensional dimension mapping and applying a self-adaptive consistency evaluation model, thereby providing scientific basis for the systematic verification of IVCPS. Disclosure of Invention In view of the above, the present invention aims to provide a IVCPS confirmation method based on a multidimensional mapping mechanism, which aims to solve the technical problems that the completeness of the whole system confirmation is difficult and the evaluation weight is difficult to adapt to the dynamic working condition because IVCPS requirement ontology, requirement elements and association relation thereof have obvious multi-level and multi-main-body characteristics. The invention adopts the following technical scheme to solve the problems: IVCPS confirmation method based on multidimensional mapping mechanism includes the following steps: s1, constructing a multi-view and domain ontology-based demand analysis model, namely adopting a multi-view-based interest-holder demand, application scene demand and functional demand extraction method, and extracting IVCPS a demand ontology, a demand element and an association relation of a typical reference system prototype by combining domain ontology knowledge and AI-enhanced cross-domain knowledge graph analysis technology; s2, executing a multi-scale, multi-level and multi-main body three-dimensional mapping mechanism, namely establishing a mapping function based on depth fusion characteristics of IVCPS physical space and information space, and mapping the demand ontology in the step S1 into a quantifiable index system; The index system comprises a multi-scale functional index, a multi-level logic index and a multi-main body functional and performance index; S3, constructing an information physical multidimensional consistency assessment model, namely identifying element combinations and random element appearances under multiple traffic conditions, and realizing self-adaptive matching and dynamic correction of a consistency weight matrix through an information physical multidimensional consistency assessment method; S4, executing a multidimensional progressive overall confirmation process, namely calling the adaptive coincidence weight matrix in the step S3 under the multi-traffic working condition environment, executing the dimensionality coincidence assessment on the index system generated by the mapping in the step S2, and finally, based on the weighted convergence judgment of the coincidence results of all the dimensionalities, realizing IVCPS the overall confirmation of the typical reference system prototype. Further, the step S1 includes the following substeps: S1.1, multi-view requirement extraction; Synchronously acquiring direct participant demand, treatment party demand, technolog