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A method for obtaining test cases of an intelligent driving system

A technology for intelligent driving and system testing, applied in software testing/debugging, biological neural network models, etc., can solve problems such as the lack of test library formation methods, and achieve the effect of ensuring scalability

Active Publication Date: 2021-12-31
TONGJI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is no good method for forming a test library for a certain type of intelligent vehicle characteristics at present.

Method used

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  • A method for obtaining test cases of an intelligent driving system
  • A method for obtaining test cases of an intelligent driving system
  • A method for obtaining test cases of an intelligent driving system

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Embodiment Construction

[0022] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. Apparently, the described embodiments are some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0023] Such as figure 1 As shown, the present invention relates to a method for obtaining an intelligent driving system test case, the method comprising the following steps:

[0024] Step 1: Use the perception system of the intelligent driving system to acquire pictures.

[0025] Step 2: Set up an attack target in the obtained pictures for the errors that the neural network of the intelligent driving system needs to implement.

[0026] Step 3. Determine whether the model structure of the neural network is a known structure. If so, ...

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Abstract

The invention relates to a method for obtaining test cases of an intelligent driving system. The method formalizes the attack problem of the neural network model into an optimization problem for the problem of image classification; and utilizes an evolutionary algorithm for iterative operation to realize black-box confrontation of the neural network model, and at the same time , using neural network-based adversarial sample guidance to generate a test library for smart cars. Compared with the prior art, the invention can automatically obtain an effective test case library, and has the advantages of ensuring the attack target model with a 100% success rate and ensuring the expandability of the attack strategy.

Description

technical field [0001] The invention relates to the technical field of intelligent driving, in particular to a method for acquiring test cases of an intelligent driving system. Background technique [0002] The hot development of intelligent driving is inseparable from the progress of artificial intelligence technology, and the research on neural network is the most prominent. Based on the neural network model, a real-time, high-precision, end-to-end environment perception system can be realized. But at the same time, the model also has considerable potential risks. For example, in some scenarios, some changes that are very small to humans may cause serious perception errors. How to automatically and efficiently generate effective test cases for specific models is the key to whether smart cars can be quickly implemented. [0003] For the intelligent driving unit using the neural network model, especially the perception system, the existing research on generating test sampl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/36G06N3/02
Inventor 罗怡桂杨瑞嘉王逸偲沙威
Owner TONGJI UNIV
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