Process method for applying a machine learning algorithm to automobile software development function safety

A technology of machine learning and automotive software, applied in the field of automotive software safety and machine learning, can solve problems such as difficult to clarify specifications, lack of interpretability, guarantee obstacles to functional safety, etc., achieve good application prospects, improve development efficiency and safety sexual effect

Pending Publication Date: 2019-06-25
上海工业控制安全创新科技有限公司
View PDF0 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Because the software development of many types of advanced functions (such as automatic driving system) needs to perceive the environment, and the existing functional software cannot be fully standardized description; for example, what is the specification for identifying pedestrians? Using specifications (such as necessary and sufficient conditions) can only partially specify these conditions. In practical applications, data samples are also needed to help describe functions; since functions like perception are difficult to specify clearly, it is necessary to use machine learning-based methods to implement software Components, implementing software components by training from samp

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Process method for applying a machine learning algorithm to automobile software development function safety
  • Process method for applying a machine learning algorithm to automobile software development function safety
  • Process method for applying a machine learning algorithm to automobile software development function safety

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] figure 1 As shown in , a machine learning algorithm is applied to the process method of automotive software development functional safety, including seven steps, step 1: project start-up phase, using machine learning decision gate; step 2: software safety requirements phase, standardized description of safety requirements ; Step 3: software architecture design stage, using fault-tolerant design method; Step 4: software development stage, data collection; Step 5: software development stage, model selection; Step 6: software development stage, model realization; Step 7: software integration stage , verified and tested.

[0046] figure 1 As shown in , in step 1, the developer determines whether the security requirement is likely to be implemented programmatically to resolve the failure, and conducts an evaluation to determine whether the security requirement must be implemented by a machine learning component, or can be implemented using a programmatic programming compone...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

A process method for applying a machine learning algorithm to automobile software development function safety comprises the following seven steps: step 1, a project starting stage: adopting a machinelearning decision-making door; 2, a software security requirement stage: standardizing and describing security requirements; Step 3, a software architecture design stage: adopting a fault-tolerant design method; 4, a software development stage: collecting data; 5, a software development stage and model selection; 6, a software development stage and model implementation are carried out; And 7, a software integration stage, verification and testing. According to the method, in the development process of automobile electronic software, the property of partial standardized description is clear, analgorithm feature selection model based on various machine learning is facilitated, and then the development efficiency and safety are improved. Based on the above, the method has a good applicationprospect.

Description

technical field [0001] The invention relates to the technical fields of automotive software safety and machine learning, in particular to a process method for applying machine learning algorithms to functional safety of automotive software development. Background technique [0002] With the development of technology, there are more and more software applications for various functions of automobiles, such as advanced driver assistance systems (ADAS) and automatic driving systems (ADS). In the development process of automotive software, machine learning plays an increasingly important role, ensuring the development and application of software. Security is a major concern in automotive software development. ISO 26262 (an international safety standard for automobiles) is based on a systematic approach to safety issues from the perspective of industrial practice. This standard defines the safety life cycle of automobiles and the methods to achieve safety at each stage; The safe...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F8/20G06F8/60G06F11/36
Inventor 王高翃刘虹蒲戈光
Owner 上海工业控制安全创新科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products