Unsettled Domains Concerning Autonomous System Validation And Verification Processes


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Unsettled Domains Concerning Autonomous System Validation and Verification Processes


Unsettled Domains Concerning Autonomous System Validation and Verification Processes

Author: Fabio Alonso da Silva

language: en

Publisher: SAE International

Release Date: 2019-12-30


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The Federal Aviation Administration (FAA) and the Department of Transportation’s (DOT’s) National Highway Traffic Safety Administration (NHTSA) face similar challenges regarding the regulation of autonomous systems powered by artificial intelligence (AI) algorithms that replace the human factor in the decision-making process. Validation and verification (V&V) processes contribute to implementation of correct system requirements and the development life cycle - starting with the definition of regulatory, marketing, operational, performance, and safety requirements. The V&V process is one of the steps of a development life cycle starting with the definition of regulatory, marketing, operational, performance, and safety requirements. They define what a product is, and they flow down into lower level requirements defining control architectures, hardware, and software. The industry is attempting to define regulatory requirements and a framework to gain safety clearance of such products. This report suggests a regulatory text and a safety and V&V approach from an aerospace engineering perspective assessing the replacement of the human driver from the decision-making role by a computational system. It also suggests an approach where aerospace guidelines can be used alongside the International Organization for Standardization (ISO) standard ISO 26262 in order to define a viable and valuable framework for autonomous systems safety clearance (or certification). NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019012

Unsettled Technology Areas in Autonomous Vehicle Test and Validation


Unsettled Technology Areas in Autonomous Vehicle Test and Validation

Author: Rahul Razdan

language: en

Publisher: SAE International

Release Date: 2019-06-12


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Automated driving system (ADS) technology and ADS-enabled/operated vehicles - commonly referred to as automated vehicles and autonomous vehicles (AVs) - have the potential to impact the world as significantly as the internal combustion engine. Successful ADS technologies could fundamentally transform the automotive industry, civil planning, the energy sector, and more. Rapid progress is being made in artificial intelligence (AI), which sits at the core of and forms the basis of ADS platforms. Consequently, autonomous capabilities such as those afforded by advanced driver assistance systems (ADAS) and other automation solutions are increasingly becoming available in the marketplace. To achieve highly or fully automated or autonomous capabilities, a major leap forward in the validation of these ADS technologies is required. Without this critical cog, helping to ensure the safety and reliability of these systems and platforms, the full capabilities of ADS technology will not be realized. This paper explores the ADS validation challenge by reviewing existing approaches and examining the effectiveness of those approaches, presenting critical techniques required to bring safe and effective solutions to market, discussing unsettled topics, and suggesting next steps for industry stakeholders to consider as they work to advance the ADS ecosystem. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019001

Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes


Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes

Author: Mohsen Khalkhali

language: en

Publisher: SAE International

Release Date: 2020-06-03


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Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes discusses the unsettled issue of sharing the terabytes of driving data generated by Automated Vehicles (AVs) on a daily basis. Perception engineers use these large datasets to analyze and model the automated driving systems (ADS) that will eventually be integrated into future “self-driving” vehicles. However, the current industry practices of collecting data by driving on public roads to understand real-world scenarios is not practical and will be unlikely to lead to safe deployment of this technology anytime soon. Estimates show that it could take 400 years for a fleet of 100 AVs to drive enough miles to prove that they are as safe as human drivers. Yet, data-sharing can be developed – as a technology, culture, and business – and allow for rapid generation and testing of the billions of possible scenarios that are needed to prove practicality and safety of an ADS – resulting in lower research and development costs to the industry. Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes explores how this could lead to better regulation, insurance, public acceptance – and finally, shorter technology development cycles. Finding a business case and changing to an open data culture are not going to be easy tasks, but data sharing is the only way forward for the whole industry to move to the next phase of deployment after nearly a decade of intense research. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2020007