Comparison of hazard analysis methods with regard to the series development of autonomous vehicles

Author(s):  
Greta Carlotta Kolln ◽  
Michael Klicker ◽  
Stephan Schmidt
Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1220
Author(s):  
Chee Wei Lee ◽  
Stuart Madnick

Urban mobility is in the midst of a revolution, driven by the convergence of technologies such as artificial intelligence, on-demand ride services, and Internet-connected and self-driving vehicles. Technological advancements often lead to new hazards. Coupled with the increased levels of automation and connectivity in the new generation of autonomous vehicles, cybersecurity is emerging as a key threat affecting these vehicles. Traditional hazard analysis methods treat safety and security in isolation and are limited in their ability to account for interactions among organizational, sociotechnical, human, and technical components. In response to these challenges, the cybersafety method, based on System Theoretic Process Analysis (STPA and STPA-Sec), was developed to meet the growing need to holistically analyze complex sociotechnical systems. We applied cybersafety to coanalyze safety and security hazards, as well as identify mitigation requirements. The results were compared with another promising method known as Combined Harm Analysis of Safety and Security for Information Systems (CHASSIS). Both methods were applied to the Mobility-as-a-Service (MaaS) and Internet of Vehicles (IoV) use cases, focusing on over-the-air software updates feature. Overall, cybersafety identified additional hazards and more effective requirements compared to CHASSIS. In particular, cybersafety demonstrated the ability to identify hazards due to unsafe/unsecure interactions among sociotechnical components. This research also suggested using CHASSIS methods for information lifecycle analysis to complement and generate additional considerations for cybersafety. Finally, results from both methods were backtested against a past cyber hack on a vehicular system, and we found that recommendations from cybersafety were likely to mitigate the risks of the incident.


2020 ◽  
Vol 214 ◽  
pp. 107773
Author(s):  
Xiang-Yu Zhou ◽  
Zheng-Jiang Liu ◽  
Feng-Wu Wang ◽  
Zhao-Lin Wu ◽  
Ren-Da Cui

2013 ◽  
Vol 423-426 ◽  
pp. 1308-1311
Author(s):  
Qiang Hui Song ◽  
X. L. Li ◽  
Y. Y. Li ◽  
Y. Wu

As an important part of landslide risk assessment, hazard analysis which is based on the probability analysis of landslide stability have caught more and more attentions from researchers and engineers. While in landslide engineering, the uncertainties such as the variability and uncertainty inherent in the geotechnical properties are complex and different, so a single Factor of Safety calculated by traditional deterministic analyses methods can not represent the landslide stability exactly. To provide a more rational mathematical framework to incorporate different types of uncertainties in the landslide stability estimation, some practical probability analysis methods for stability of landslide were proposed, then the user-friendly implementing softwares were recommended. Finally, an application case was described to illustrate the approaches adopted and proved the correctness and feasibility of the proposed methods. The results show the proposed techniques can be applied widely.


Author(s):  
Nanda Anugrah Zikrullah ◽  
Hyungju Kim ◽  
Meine JP van der Meulen ◽  
Gunleiv Skofteland ◽  
Mary Ann Lundteigen

A safety-critical system comprising several interacting and software-intensive systems must be carefully analyzed to detect whether new functional requirements are needed to ensure safety. This involves an analysis of the systemic properties of the system, which addresses the effect of the interaction between systems and system parts. The paper compares two hazard analysis methods, which are often considered well-suited for such software-intensive systems: the Functional Hazard Analysis (FHA) and Systems-Theoretic Process Analysis (STPA). The focus is on the selection and improvement of the best methods, based on the lesson learned from the comparison of FHA and STPA. The analyses cover the hazard analysis processes, systemic properties, and the criteria of requirements. The paper concludes that STPA is the better choice over FHA. Insights are obtained to align both STPA and FHA methods with the broader topic on risk management, that is, hazard analysis method improvement, cautionary thinking, uncertainty management, and resilience management.


2021 ◽  
Author(s):  
Marissa Torres ◽  
Norberto Nadal-Caraballo

The quantification of storm surge is vital for flood hazard assessment in communities affected by coastal storms. The astronomical tide is an integral component of the total still water level needed for accurate storm surge estimates. Coastal hazard analysis methods, such as the Coastal Hazards System and the StormSim Coastal Hazards Rapid Prediction System, require thousands of hydrodynamic and wave simulations that are computationally expensive. In some regions, the inclusion of astronomical tides is neglected in the hydrodynamics and tides are instead incorporated within the probabilistic framework. There is a need for a rapid, reliable, and accurate tide prediction methodology to provide spatially dense reconstructed or predicted tidal time series for historical, synthetic, and forecasted hurricane scenarios. A methodology is proposed to combine the tidal harmonic information from the spatially dense Advanced Circulation hydrodynamic model tidal database with a rapid tidal reconstruction and prediction program. In this study, the Unified Tidal Analysis program was paired with results from the tidal database. This methodology will produce reconstructed (i.e., historical) and predicted tidal heights for coastal locations along the United States eastern seaboard and beyond and will contribute to the determination of accurate still water levels in coastal hazard analysis methods.


2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Henry WW Potts ◽  
Janet E Anderson ◽  
Lacey Colligan ◽  
Paul Leach ◽  
Sheena Davis ◽  
...  

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