Safety Analysis Method for Cooperative Driving Systems

Dajsuren, Yanja; Loupias, Guido

doi:10.1109/icsa.2019.00027

Cited by 6 publications

(5 citation statements)

References 28 publications

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“…In our case study, we found 15 FSRs from the cooperative perspective, making up 48% of all FSRs. Our results corroborate the existing body of knowledge [17,38,46] in showing that the current safety standard misses FSRs from the cooperative perspective.…”

Section: Interpretation Of Resultssupporting

confidence: 89%

“…Clearly, replications are required to verify the generalizability and scalability of our method. Nonetheless, our results corroborate the existing body of knowledge [17,38,46] in showing that the current safety standard FSRs from the cooperative perspective. The results of our case study show better coverage of safety goals by providing additional FSRs as compared to the ISO 26262 process [28].…”

Section: Interpretation Of Resultssupporting

confidence: 89%

“…A majority of works on cooperative systems proposes a reference architecture from a system of systems viewpoint [40]. Some other solutions look at specific architecture components in specific cooperative scenarios, thereby missing high-level insights [17].…”

Section: Safety Engineeringmentioning

confidence: 99%

“…4 A majority of the cooperative driving functionalities are achieved by determining a vehicle's behavior for optimal traffic behavior according to the information received from other traffic participants. Such optimal behaviors are achieved (partially or fully) using software-controlled steering, acceleration, and braking [17]. Therefore, any problem in the software can lead to catastrophic effects not only to the vehicle itself but also to other traffic participants.…”

Section: Introductionmentioning

confidence: 99%

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A Functional Safety Assessment Method for Cooperative Automotive Architecture

Kochanthara¹,

Rood²,

Saberi³

et al. 2021

Preprint

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The scope of automotive functions has grown from a single vehicle as an entity to multiple vehicles working together as an entity, referred to as cooperative driving. The current automotive safety standard, ISO 26262, is designed for single vehicles. With the increasing number of cooperative driving capable vehicles on the road, it is now imperative to systematically assess the functional safety of architectures of these vehicles. Many methods are proposed to assess architectures with respect to different quality attributes in the software architecture domain, but to the best of our knowledge, functional safety assessment of automotive architectures is not explored in the literature. We present a method, that leverages existing research in software architecture and safety engineering domains, to check whether the functional safety requirements for a cooperative driving scenario are fulfilled in the technical architecture of a vehicle. We apply our method on a real-life academic prototype for a cooperative driving scenario, platooning, and discuss our insights.

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Section: Interpretation Of Resultssupporting

confidence: 89%

Section: Interpretation Of Resultssupporting

confidence: 89%

Section: Safety Engineeringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Functional Safety Assessment Method for Cooperative Automotive Architecture

Kochanthara¹,

Rood²,

Saberi³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

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“…The Model-Based Systems Engineering (MBSE) design methodology is a crucial lever for complex cooperative automated vehicle system design. In general, many errors come from the requirements phase of the Software Development Life Cycle (SDLC) [6]. In order to avoid requirement errors, good system software must be well designed.…”

Section: Introductionmentioning

confidence: 99%

Model-Based Systems Engineering to Design An Onboard Surround Vision System for Cooperative Automated Vehicles

Kemsaram

Das

Dubbelman

2021

2021 2nd International Informatics and Software Engineering Conference (IISEC)

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Cooperative automated vehicles have various electronic control units with multiple sensors running complex software algorithms to perceive and navigate their environment. Hence, there is a need to use advanced software engineering design methodology to reduce the software complexity and increase modularity. In this paper, we applied the SysCARS model-based systems engineering methodology to design an onboard surround vision system with a SysML modeling language using the IBM Rational Rhapsody modeling tool. The modeling methodology is described through various phases and steps with a modeling language to overcome the challenges. The modeling tool takes the information from the design model of the system and generates a skeletal code. The algorithm is written for each generated skeletal code, compiled with a C++ compiler on the host Desktop PC (Ubuntu 16.04 LTS), and deployed on the target Nvidia Drive PX2 embedded hardware platform. The designed solution fulfills the requirements of the onboard surround vision system.

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