A Strategy for Assessing Safe Use of Sensors in Autonomous Road Vehicles

Alissa, Samieh; Bengtsson, Staffan; Bergenhem, Carl; Bridal, Olof; Cassel, Anders; Chen, DeJiu; Gassilewski, Martin; Nilsson, Jonas; Sandberg, Anders; Ursing, Stig; Warg, Fredrik; Werneman, Anders

doi:10.1007/978-3-319-66266-4_10

Cited by 5 publications

(4 citation statements)

References 1 publication

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“…Besides the approaches mentioned so far, there are also considerations on perception requirements that aim at complying with the traditional ISO 26262 functional safety standard. The sources [35,52,53] propose dynamically associating an Automotive Safety Integrity Level (ASIL) with a given driving situation such that for example, the perception is required to comply with the stricter ASIL D in high-risk situations and with the less strict ASIL A in low-risk situations. An example of how functional safety requirements for the perception subsystem can be derived based on a fault tree analysis (FTA) is given in Ref.…”

Section: Concrete Approaches Of Specifying Perceptionmentioning

confidence: 99%

“…[175]. Similarly, in the ISO 26262 context, it was proposed that the perception subsystem dynamically outputs one world model for each ASIL level such that the planner can dynamically take just that world model that it needs to comply with the ASIL requirement of the current driving situation [35,52,53]. In any of such applications, it is crucial to assure that the reported uncertainties are correctly calibrated (Sect.…”

Section: Uncertainty Tolerancementioning

confidence: 99%

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A Review of Testing Object-Based Environment Perception for Safe Automated Driving

2022

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Safety assurance of automated driving systems must consider uncertain environment perception. This paper reviews literature addressing how perception testing is realized as part of safety assurance. The paper focuses on testing for verification and validation purposes at the interface between perception and planning, and structures the analysis along the three axes (1) test criteria and metrics, (2) test scenarios, and (3) reference data. Furthermore, the analyzed literature includes related safety standards, safety-independent perception algorithm benchmarking, and sensor modeling. It is found that the realization of safety-oriented perception testing remains an open issue since challenges concerning the three testing axes and their interdependencies currently do not appear to be sufficiently solved.

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Section: Concrete Approaches Of Specifying Perceptionmentioning

confidence: 99%

Section: Uncertainty Tolerancementioning

confidence: 99%

A Review of Testing Object-Based Environment Perception for Safe Automated Driving

2022

View full text Add to dashboard Cite

show abstract

“…Besides the approaches mentioned so far, there are also considerations on perception requirements that aim at complying with the traditional ISO 26262 functional safety standard. The sources [35], [52], [53] propose dynamically associating an Automotive Safety Integrity Level (ASIL) with a given driving situation such that for example, the perception is required to comply with the stricter ASIL D in high-risk situations and with the less strict ASIL A in low-risk situations. An example of how functional safety requirements for the perception subsystem can be derived based on a fault tree analysis (FTA) is given in [122] in the context of automated valet parking.…”

Section: A Specification Of Requirements and Criteriamentioning

confidence: 99%

“…An overview of self-representation and monitoring of subsystems is given in [175]. Similarly, in the ISO 26262 context, it was proposed that the perception subsystem dynamically outputs one world model for each ASIL level such that the planner can dynamically take just that world model that it needs to comply to the ASIL requirement of the current driving situation [35], [52], [53]. In any of such applications, it is crucial to assure that the reported uncertainties are correctly calibrated (Sec.…”

Section: Further Safety Assurance Activities Regarding Perceptionmentioning

confidence: 99%

A Review of Testing Object-Based Environment Perception for Safe Automated Driving

Hoss,

Scholtes,

Eckstein

2021

Preprint

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Safety assurance of automated driving systems must consider uncertain environment perception. This paper reviews literature addressing how perception testing is realized as part of safety assurance. We focus on testing for verification and validation purposes at the interface between perception and planning, and structure our analysis along the three axes 1) test criteria and metrics, 2) test scenarios, and 3) reference data. Furthermore, the analyzed literature includes related safety standards, safetyindependent perception algorithm benchmarking, and sensor modeling. We find that the realization of safety-aware perception testing remains an open issue since challenges concerning the three testing axes and their interdependencies currently do not appear to be sufficiently solved.

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Design of a Knowledge-Base Strategy for Capability-Aware Treatment of Uncertainties of Automated Driving Systems

Chen

Östberg

Becker

et al. 2018

Lecture Notes in Computer Science

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A Strategy for Assessing Safe Use of Sensors in Autonomous Road Vehicles

Cited by 5 publications

References 1 publication

A Review of Testing Object-Based Environment Perception for Safe Automated Driving

A Review of Testing Object-Based Environment Perception for Safe Automated Driving

A Review of Testing Object-Based Environment Perception for Safe Automated Driving

Design of a Knowledge-Base Strategy for Capability-Aware Treatment of Uncertainties of Automated Driving Systems

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