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Centre for Assuring Autonomy
HomeCentre for Assuring AutonomyAbout CfAAAAIPBody of Knowledge

Body of Knowledge

The Body of Knowledge helps to support the development of safe autonomous systems by providing practical guidance on assurance and regulation.

Use the coloured boxes below to explore the Body of Knowledge or use the links further down this page to go straight to some of the guidance that is already in place:

Section 1

Section 2

Section 3

Section 4

Direct links to practical guidance

1.1 Identifying hazards

1.1 - practical guidance for 'identifying hazards':

  • healthcare
1.1.2 Defining the operating environment

1.1.2 - practical guidance for 'defining the operating environment':

1.1.3 Defining operating scenarios

1.1.3 - practical guidance for 'defining operating scenarios':

1.2 Identifying hazardous system behaviour

1.2 - practical guidance for 'identifying hazardous system behaviour':

1.2.1 Considering human/machine interactions

1.2.1 - practical guidance for 'considering human/machine interactions':

1.3.1 Validation of safety requirements

1.3.1 - practical guidance for 'validation of safety requirements':

 

1.4 Impact of security on safety

1.4 - practical guidance for 'impact of security on safety':

2.1 System-level verification

2.1 - practical guidance for 'system-level verification':

2.2.1.1 Defining sensing requirements

2.2.1.1 - practical guidance for 'defining sensing requirements':

2.2.1.2 Defining understanding requirements

2.2.1.2 - practical guidance for 'defining understanding requirements':

2.2.4.1 Verification of sensing requirements

2.2.4.1 - practical guidance for 'verification of sensing requirements':

2.2.4.2 Verification of understanding requirements

2.2.4.2 - practical guidance for 'verification of understanding requirements':

  • cross-domain and maritime
2.2.4.3 Verification of deciding requirements

2.2.4.3 - practical guidance for 'verification of deciding requirements':

2.3 Implementing requirements using ML

2.3 - practical guidance for 'implementing requirements using ML':

2.3.1 Sufficiency of training data

2.3.1 - practical guidance for 'sufficiency of training data':

2.3.2 Sufficiency of the learning process

2.3.2 - practical guidance for 'sufficiency of the learning process':

2.3.3 Verification of the learned model

2.3.3 - practical guidance for 'verification of the learned model':

2.4 Controlling interactions with other systems

2.4 - practical guidance for 'Controlling interactions with other systems':

  • Cross-domain guidance on assurance objective: Identify how interactions between the RAS and other systems may give rise to unsafe behaviour.
  • Cross-domain guidance on assurance objective: Manage interactions between the RAS and other systems to ensure they do not result in unsafe behaviour.
2.6 Handling change during operation

2.6 - practical guidance for 'handling change during operation':

2.6.1 Monitoring RAS operation

2.6.1 - practical guidance for 'monitoring RAS operation':

2.7 Using simulation

2.7 - practical guidance for 'using simulation':

2.8 Explainability

2.8 - practical guidance on:

3 Understanding and controlling deviations from required behaviour

3.0 - practical guidance on 'understanding and controlling deviations from required behaviour':

3.1 Identifying potential deviation from required behaviour

3.1 practical guidance for 'identifying potential deviations from required behaviour':

  • cross-domain
3.1.1 Identifying potential deviation from required behaviour

3.1.1 practical guidance for 'identifying sensing deviations':

3.2 Mitigating potential deviations

3.2 practical guidance for 'mitigating potential deviations':

4.1.1 Identifying applicable rules and regulations

4.1.1 - practical guidance for 'identifying applicable rules and regulations':

4.1.2 Understanding the requirements of rules and regulations

4.1.2 - practical guidance for 'understanding the requirements of rules and regulations':

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