A Method for Generating Test Samples of Intelligent Traffic Data Based on Comprehensible Feature Variation

A technology for intelligent transportation and data testing, which is used in traffic flow detection, traffic control systems for road vehicles, traffic control systems, etc.

Active Publication Date: 2022-01-28
深圳慕智科技有限公司
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

Utilizing the present invention, intelligent transportation V2X testing units and individuals can efficiently solve the following important problems:

Method used

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  • A Method for Generating Test Samples of Intelligent Traffic Data Based on Comprehensible Feature Variation
  • A Method for Generating Test Samples of Intelligent Traffic Data Based on Comprehensible Feature Variation
  • A Method for Generating Test Samples of Intelligent Traffic Data Based on Comprehensible Feature Variation

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Embodiment Construction

[0033]Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.

[0034] Such as figure 1 As shown, in the overall schematic diagram of the present invention: it contains 2 main parts, and is continuously optimized based on the iterative process:

[0035] 1 Extraction of external semantic features and transformation relations of the system. In order to capture the transformation rules in a specific intelligent transportation application scenario, it is first necessary to obtain relevant raw data in the specific intelligent transportation software field to divide the most basic transformation rules. For example, for the V2X road weather environment, a large number of images or other sensor data containing weather elements are required. Next, for different transformation rules, it is necessary to ma...

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Abstract

The present invention provides a method for generating intelligent traffic data test samples based on intelligible feature variation. The method mainly includes the generation of V2X scene variation rules and the construction and application of variation models. These steps can be specifically divided into intelligent traffic V2X scene data Collection, construction of semantic mutation rules, construction of mutation model and implementation of semantic mutation. By using the present invention, intelligent transportation V2X testing units and individuals can efficiently solve the problem of insufficient semantic diversity of traffic data in intelligent transportation V2X standard application scenarios, expand semantic variation test samples, and finally improve the reliability of intelligent transportation system software.

Description

technical field [0001] The invention belongs to the technical field of intelligent software testing, especially for the expansion of test samples in the external input state space of complex software systems represented by vehicle systems in intelligent transportation V2X test scenarios, and is a test sample generation based on externally understandable semantic feature variation The technical framework maintains the software reliability of the intelligent transportation V2X system by constructing a large number of high-scenario feature coverage test cases. Background technique [0002] There are many differences between intelligent transportation V2X software and traditional software in terms of system construction function logic implementation. The internal algorithm models that "smart" implementation relies on, such as machine learning, intelligent communication algorithms or models, have no boundary concept in the general sense. In addition, in actual operation There are...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/36G06V10/82G06V20/54G06V10/764G06K9/62G06N3/08G08G1/01
CPCG06F11/3684G06F11/3688G06N3/08G08G1/0125G06F18/24
Inventor 王晓冰夏志龙房春荣
Owner 深圳慕智科技有限公司
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