Safety Assurance Strategies for Autonomous Vehicles

Wardziński, Andrzej

doi:10.1007/978-3-540-87698-4_24

Cited by 28 publications

(35 citation statements)

References 3 publications

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“…These are focused in this contribution. In accordance to [21] it is proposed to supplement the traditional safety methods by adding so called dynamic risk assessment. With the help of generalized cause-consequence dependencies the risk assessment dynamically generates limits.…”

Section: Safety Aspects Of Autonomous Systemsmentioning

confidence: 99%

“…In many cases, they have to collaborate with humans in a natural and intuitive way and adapt themselves to varying conditions [21]. Typical examples are autonomous service robots.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, autonomous systems are safety-critical systems that require a safety strategy in order to assure that no unacceptable risks exist [6], [2]. However, it seems to be impossible to foresee all complex interactions between autonomous technical system and the environment and therefore the derivation of a safety strategy and the realization of a satisfying risk assessment during the development phase also seems to be impossible [21]. Hence, if safety analysis cannot be established during the development phase sufficiently, it has to be ensured that the safety aspects are observed during operating time [21].…”

Section: Introductionmentioning

confidence: 99%

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Action planning for autonomous systems with respect to safety aspects

Ertle

Gamrad

Voos

et al. 2010

2010 IEEE International Conference on Systems, Man and Cybernetics

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Abstract-Autonomous systems are often needed to perform tasks in complex and dynamic environments. For this class of systems the traditional safety assuring methods are not satisfying because these systems cannot be analyzed completely during development phase. In order to realize a more flexible safety analysis the internal representation of the outside world that is learned by an autonomous Cognitive Technical System is used to identify hazardous situations. The so called safety principles are the hazard knowledge. These can be added to the system prior to operating time without losing the possibility of adjusting or expanding this hazard knowledge during operating time. How these safety principles are generally designed and implemented is explained in this contribution. Furthermore, as underlying Cognitive Technical System provides anticipation capabilities it is possible to expand the planning process in order to take hazard information into account. Finally, in a simulation example is shown how the autonomous system determines possible future actions and evaluates them with regard to hazards in order to provide a plan with acceptable risk.

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Section: Safety Aspects Of Autonomous Systemsmentioning

confidence: 99%

“…In many cases, they have to collaborate with humans in a natural and intuitive way and adapt themselves to varying conditions [21]. Typical examples are autonomous service robots.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Action planning for autonomous systems with respect to safety aspects

Ertle

Gamrad

Voos

et al. 2010

2010 IEEE International Conference on Systems, Man and Cybernetics

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“…This scheme is termed hereafter as Dynamic Risk Management. Already there are several domains that deal with the problem of Dynamic Risk Management in the field of robotics [14], financial critical decisions [15], security [16] and many others. However, such approaches need to address the key issue of providing compelling safety assurance required for certification and operation within 'safety-critical environments'.…”

Section: Dynamic Real-time On-line Risk Managementmentioning

confidence: 99%

“…Potential safety argument goals for high-fidelity simulation and modelling defined in [24] can be used to decompose such a safety argument goal. Safety requirements defined for the Situation Awareness Model defined in [14] also apply to the high-fidelity system model and contribute to decomposing goals G2, G3 and G4. Determining potential controller solution failures such as function derivatives and function output extremes will rely upon the effects exhibited by the high-fidelity model.…”

Section: Component (Controller) Solution Generatormentioning

confidence: 99%

Establishing a Framework for Dynamic Risk Management in ‘Intelligent’ Aero-Engine Control

Kurd

Kelly

McDermid

et al. 2009

Lecture Notes in Computer Science

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Abstract. The behaviour of control functions in safety critical software systems is typically bounded to prevent the occurrence of known system level hazards. These bounds are typically derived through safety analyses and can be implemented through the use of necessary design features. However, the unpredictability of real world problems can result in changes in the operating context that may invalidate the behavioural bounds themselves, for example, unexpected hazardous operating contexts as a result of failures or degradation. For highly complex problems it may be infeasible to determine the precise desired behavioural bounds of a function that addresses or minimises risk for hazardous operation cases prior to deployment. This paper presents an overview of the safety challenges associated with such a problem and how such problems might be addressed. A self-management framework is proposed that performs on-line risk management. The features of the framework are shown in context of employing intelligent adaptive controllers operating within complex and highly dynamic problem domains such as Gas-Turbine Aero Engine control. Safety assurance arguments enabled by the framework necessary for certification are also outlined.

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