27,906 research outputs found

    Paving the Roadway for Safety of Automated Vehicles: An Empirical Study on Testing Challenges

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    The technology in the area of automated vehicles is gaining speed and promises many advantages. However, with the recent introduction of conditionally automated driving, we have also seen accidents. Test protocols for both, conditionally automated (e.g., on highways) and automated vehicles do not exist yet and leave researchers and practitioners with different challenges. For instance, current test procedures do not suffice for fully automated vehicles, which are supposed to be completely in charge for the driving task and have no driver as a back up. This paper presents current challenges of testing the functionality and safety of automated vehicles derived from conducting focus groups and interviews with 26 participants from five countries having a background related to testing automotive safety-related topics.We provide an overview of the state-of-practice of testing active safety features as well as challenges that needs to be addressed in the future to ensure safety for automated vehicles. The major challenges identified through the interviews and focus groups, enriched by literature on this topic are related to 1) virtual testing and simulation, 2) safety, reliability, and quality, 3) sensors and sensor models, 4) required scenario complexity and amount of test cases, and 5) handover of responsibility between the driver and the vehicle.Comment: 8 page

    THE ROLE OF ARTIFICIAL INTELLIGENCE IN PUSHING THE BOUNDARIES OF U.S. REGULATION: A SYSTEMATIC REVIEW

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    Artificial Intelligenceโ€™s (AI) growing catalog of applications and methods has the potential to profoundly affect public policy by generating instances where regulations are not adequate to confront the issues faced by society, also known as regulatory gaps. The objective of this article is to improve our understanding of how AI influences U.S. public policy. It does so by systematically exploring, for the first time, this technologyโ€™s role in the generation of regulatory gaps. Specifically, it addresses two research questions: What U.S. regulatory gaps exist due to AI methods and applications? When looking across all of the gaps identified in the first research question, what trends and insights emerge that can help stakeholders plan for the future? These questions are answered through a systematic review of four academic literature databases in the hard and social sciences. Its implementation is guided by a protocol that identified 5,240 candidate articles. A screening process reduced this sample to 241 articles (published between 1976 and February of 2018) relevant to answering the research questions. This article contributes to the literature by adapting the work of Bennett-Moses and Calo to effectively characterize regulatory gaps caused by AI in the U.S. In addition, it finds that most gaps: do not require new regulation or the creation of governance frameworks for their resolution, are found at the federal and state levels of government, and AI applications are recognized more often than methods as their cause

    Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS - a collection of Technical Notes Part 1

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    This report provides an introduction and overview of the Technical Topic Notes (TTNs) produced in the Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS (Tigars) project. These notes aim to support the development and evaluation of autonomous vehicles. Part 1 addresses: Assurance-overview and issues, Resilience and Safety Requirements, Open Systems Perspective and Formal Verification and Static Analysis of ML Systems. Part 2: Simulation and Dynamic Testing, Defence in Depth and Diversity, Security-Informed Safety Analysis, Standards and Guidelines

    A systematic literature review on the relationship between autonomous vehicle technology and traffic-related mortality.

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ธ€๋กœ๋ฒŒํ–‰์ •์ „๊ณต, 2023. 2. ์ตœํƒœํ˜„.The society is anticipated to gain a lot from Autonomous Vehicles (AV), such as improved traffic flow and a decrease in accidents. They heavily rely on improvements in various Artificial Intelligence (AI) processes and strategies. Though some researchers in this field believe AV is the key to enhancing safety, others believe AV creates new challenges when it comes to ensuring the security of these new technology/systems and applications. The article conducts a systematic literature review on the relationship between autonomous vehicle technology and traffic-related mortality. According to inclusion and exclusion criteria, articles from EBSCO, ProQuest, IEEE Explorer, Web of Science were chosen, and they were then sorted. The findings reveal that the most of these publications have been published in advanced transport-related journals. Future improvements in the automobile industry and the development of intelligent transportation systems could help reduce the number of fatal traffic accidents. Technologies for autonomous cars provide effective ways to enhance the driving experience and reduce the number of traffic accidents. A multitude of driving-related problems, such as crashes, traffic, energy usage, and environmental pollution, will be helped by autonomous driving technology. More research is needed for the significant majority of the studies that were assessed. They need to be expanded so that they can be tested in real-world or computer-simulated scenarios, in better and more realistic scenarios, with better and more data, and in experimental designs where the results of the proposed strategy are compared to those of industry standards and competing strategies. Therefore, additional study with improved methods is needed. Another major area that requires additional research is the moral and ethical choices made by AVs. Government, policy makers, manufacturers, and designers all need to do many actions in order to deploy autonomous vehicles on the road effectively. The government should develop laws, rules, and an action plan in particular. It is important to create more effective programs that might encourage the adoption of emerging technology in transportation systems, such as driverless vehicles. In this regard, user perception becomes essential since it may inform designers about current issues and observations made by people. The perceptions of autonomous car users in developing countries like Azerbaijan haven't been thoroughly studied up to this point. The manufacturer has to fix the system flaw and needs a good data set for efficient operation. In the not-too-distant future, the widespread use of highly automated vehicles (AVs) may open up intriguing new possibilities for resolving persistent issues in current safety-related research. Further research is required to better understand and quantify the significant policy implications of Avs, taking into consideration factors like penetration rate, public adoption, technological advancements, traffic patterns, and business models. It only needs to take into account peer-reviewed, full-text journal papers for the investigation, but it's clear that a larger database and more documents would provide more results and a more thorough analysis.์ž์œจ์ฃผํ–‰์ฐจ(AV)๋ฅผ ํ†ตํ•ด ๊ตํ†ต ํ๋ฆ„์ด ๊ฐœ์„ ๋˜๊ณ  ์‚ฌ๊ณ ๊ฐ€ ์ค„์–ด๋“œ๋Š” ๋“ฑ ์‚ฌํšŒ๊ฐ€ ์–ป๋Š” ๊ฒƒ์ด ๋งŽ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋œ๋‹ค. ๊ทธ๋“ค์€ ๋‹ค์–‘ํ•œ ์ธ๊ณต์ง€๋Šฅ(AI) ํ”„๋กœ์„ธ์Šค์™€ ์ „๋žต์˜ ๊ฐœ์„ ์— ํฌ๊ฒŒ ์˜์กดํ•œ๋‹ค. ์ด ๋ถ„์•ผ์˜ ์ผ๋ถ€ ์—ฐ๊ตฌ์ž๋“ค์€ AV๊ฐ€ ์•ˆ์ „์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ์—ด์‡ ๋ผ๊ณ  ๋ฏฟ์ง€๋งŒ, ๋‹ค๋ฅธ ์—ฐ๊ตฌ์ž๋“ค์€ AV๊ฐ€ ์ด๋Ÿฌํ•œ ์ƒˆ๋กœ์šด ๊ธฐ์ˆ /์‹œ์Šคํ…œ ๋ฐ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ๋ณด์•ˆ์„ ๋ณด์žฅํ•˜๋Š” ๊ฒƒ๊ณผ ๊ด€๋ จํ•˜์—ฌ ์ƒˆ๋กœ์šด ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•œ๋‹ค๊ณ  ๋ฏฟ๋Š”๋‹ค. ์ด ๋…ผ๋ฌธ์€ ์ž์œจ์ฃผํ–‰์ฐจ ๊ธฐ์ˆ ๊ณผ ๊ตํ†ต ๊ด€๋ จ ์‚ฌ๋ง๋ฅ  ์‚ฌ์ด์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์ฒด๊ณ„์ ์ธ ๋ฌธํ—Œ ๊ฒ€ํ† ๋ฅผ ์ˆ˜ํ–‰ํ•œ๋‹ค. ํฌํ•จ ๋ฐ ์ œ์™ธ ๊ธฐ์ค€์— ๋”ฐ๋ผ EBSCO, ProQuest, IEEE Explorer ๋ฐ Web of Science์˜ ๊ธฐ์‚ฌ๋ฅผ ์„ ํƒํ•˜๊ณ  ๋ถ„๋ฅ˜ํ–ˆ๋‹ค.์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ์ด๋Ÿฌํ•œ ์ถœํŒ๋ฌผ์˜ ๋Œ€๋ถ€๋ถ„์ด ๊ณ ๊ธ‰ ์šด์†ก ๊ด€๋ จ ์ €๋„์— ๊ฒŒ์žฌ๋˜์—ˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋ฏธ๋ž˜์˜ ์ž๋™์ฐจ ์‚ฐ์—…์˜ ๊ฐœ์„ ๊ณผ ์ง€๋Šฅํ˜• ๊ตํ†ต ์‹œ์Šคํ…œ์˜ ๊ฐœ๋ฐœ์€ ์น˜๋ช…์ ์ธ ๊ตํ†ต ์‚ฌ๊ณ ์˜ ์ˆ˜๋ฅผ ์ค„์ด๋Š” ๋ฐ ๋„์›€์ด ๋  ์ˆ˜ ์žˆ๋‹ค. ์ž์œจ์ฃผํ–‰ ์ž๋™์ฐจ ๊ธฐ์ˆ ์€ ์šด์ „ ๊ฒฝํ—˜์„ ํ–ฅ์ƒ์‹œํ‚ค๊ณ  ๊ตํ†ต ์‚ฌ๊ณ ์˜ ์ˆ˜๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๋Š” ํšจ๊ณผ์ ์ธ ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•œ๋‹ค. ์ถฉ๋Œ, ๊ตํ†ต, ์—๋„ˆ์ง€ ์‚ฌ์šฉ, ํ™˜๊ฒฝ ์˜ค์—ผ๊ณผ ๊ฐ™์€ ์ˆ˜๋งŽ์€ ์šด์ „ ๊ด€๋ จ ๋ฌธ์ œ๋“ค์€ ์ž์œจ ์ฃผํ–‰ ๊ธฐ์ˆ ์— ์˜ํ•ด ๋„์›€์„ ๋ฐ›์„ ๊ฒƒ์ด๋‹ค. ํ‰๊ฐ€๋œ ๋Œ€๋ถ€๋ถ„์˜ ์—ฐ๊ตฌ์— ๋Œ€ํ•ด ๋” ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์‹ค์ œ ๋˜๋Š” ์ปดํ“จํ„ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์‹œ๋‚˜๋ฆฌ์˜ค, ๋” ์ข‹๊ณ  ํ˜„์‹ค์ ์ธ ์‹œ๋‚˜๋ฆฌ์˜ค, ๋” ์ข‹๊ณ  ๋” ๋งŽ์€ ๋ฐ์ดํ„ฐ, ๊ทธ๋ฆฌ๊ณ  ์ œ์•ˆ๋œ ์ „๋žต ๊ฒฐ๊ณผ๊ฐ€ ์‚ฐ์—… ํ‘œ์ค€ ๋ฐ ๊ฒฝ์Ÿ ์ „๋žต์˜ ๊ฒฐ๊ณผ์™€ ๋น„๊ต๋˜๋Š” ์‹คํ—˜ ์„ค๊ณ„์—์„œ ํ…Œ์ŠคํŠธ๋  ์ˆ˜ ์žˆ๋„๋ก ํ™•์žฅ๋˜์–ด์•ผ ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐœ์„ ๋œ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ์ถ”๊ฐ€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์ถ”๊ฐ€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ ๋˜ ๋‹ค๋ฅธ ์ฃผ์š” ๋ถ„์•ผ๋Š” AV์˜ ๋„๋•์ , ์œค๋ฆฌ์  ์„ ํƒ์ด๋‹ค. ์ •๋ถ€, ์ •์ฑ… ์ž…์•ˆ์ž, ์ œ์กฐ์—…์ฒด ๋ฐ ์„ค๊ณ„์ž๋Š” ๋ชจ๋‘ ์ž์œจ ์ฃผํ–‰ ์ฐจ๋Ÿ‰์„ ํšจ๊ณผ์ ์œผ๋กœ ๋„๋กœ์— ๋ฐฐ์น˜ํ•˜๊ธฐ ์œ„ํ•ด ๋งŽ์€ ์กฐ์น˜๋ฅผ ์ทจํ•ด์•ผ ํ•œ๋‹ค. ์ •๋ถ€๋Š” ํŠนํžˆ ๋ฒ•, ๊ทœ์น™, ์‹คํ–‰ ๊ณ„ํš์„ ๊ฐœ๋ฐœํ•ด์•ผ ํ•œ๋‹ค. ์šด์ „์ž ์—†๋Š” ์ฐจ๋Ÿ‰๊ณผ ๊ฐ™์€ ์šด์†ก ์‹œ์Šคํ…œ์—์„œ ์ƒˆ๋กœ์šด ๊ธฐ์ˆ ์˜ ์ฑ„ํƒ์„ ์žฅ๋ คํ•  ์ˆ˜ ์žˆ๋Š” ๋ณด๋‹ค ํšจ๊ณผ์ ์ธ ํ”„๋กœ๊ทธ๋žจ์„ ๋งŒ๋“œ๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ์ด์™€ ๊ด€๋ จํ•˜์—ฌ, ์„ค๊ณ„์ž์—๊ฒŒ ํ˜„์žฌ ์ด์Šˆ์™€ ์‚ฌ๋žŒ์— ์˜ํ•œ ๊ด€์ฐฐ์„ ์•Œ๋ ค์ค„ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ์‚ฌ์šฉ์ž ์ธ์‹์ด ํ•„์ˆ˜์ ์ด ๋œ๋‹ค.์ œ์กฐ์—…์ฒด๋Š” ์‹œ์Šคํ…œ ๊ฒฐํ•จ์„ ์ˆ˜์ •ํ•ด์•ผ ํ•˜๋ฉฐ ํšจ์œจ์ ์ธ ์ž‘๋™์„ ์œ„ํ•ด ์ข‹์€ ๋ฐ์ดํ„ฐ ์„ธํŠธ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ๋ฉ€์ง€ ์•Š์€ ๋ฏธ๋ž˜์—, ๊ณ ๋„๋กœ ์ž๋™ํ™”๋œ ์ฐจ๋Ÿ‰(AV)์˜ ๊ด‘๋ฒ”์œ„ํ•œ ์‚ฌ์šฉ์€ ํ˜„์žฌ์˜ ์•ˆ์ „ ๊ด€๋ จ ์—ฐ๊ตฌ์—์„œ ์ง€์†์ ์ธ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ํฅ๋ฏธ๋กœ์šด ์ƒˆ๋กœ์šด ๊ฐ€๋Šฅ์„ฑ์„ ์—ด์–ด์ค„ ์ˆ˜ ์žˆ๋‹ค. ๋ณด๊ธ‰๋ฅ , ๊ณต๊ณต ์ฑ„ํƒ, ๊ธฐ์ˆ  ๋ฐœ์ „, ๊ตํ†ต ํŒจํ„ด ๋ฐ ๋น„์ฆˆ๋‹ˆ์Šค ๋ชจ๋ธ๊ณผ ๊ฐ™์€ ์š”์†Œ๋ฅผ ๊ณ ๋ คํ•˜์—ฌ Avs์˜ ์ค‘์š”ํ•œ ์ •์ฑ… ์˜ํ–ฅ์„ ๋” ์ž˜ ์ดํ•ดํ•˜๊ณ  ์ •๋Ÿ‰ํ™”ํ•˜๊ธฐ ์œ„ํ•œ ์ถ”๊ฐ€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์กฐ์‚ฌ๋ฅผ ์œ„ํ•ด ๋™๋ฃŒ ๊ฒ€ํ† ๋ฅผ ๊ฑฐ์นœ ์ „๋ฌธ ์ €๋„ ๋…ผ๋ฌธ๋งŒ ๊ณ ๋ คํ•˜๋ฉด ๋˜์ง€๋งŒ, ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค๊ฐ€ ์ปค์ง€๊ณ  ๋ฌธ์„œ๊ฐ€ ๋งŽ์•„์ง€๋ฉด ๋” ๋งŽ์€ ๊ฒฐ๊ณผ์™€ ๋” ์ฒ ์ €ํ•œ ๋ถ„์„์ด ์ œ๊ณต๋  ๊ฒƒ์ด ๋ถ„๋ช…ํ•˜๋‹ค.Abstract 3 Table of Contents 6 List of Tables 7 List of Figures 7 List of Appendix 7 CHAPTER 1: INTRODUCTION 8 1.1. Background 8 1.2. Purpose of Research 13 CHAPTER 2: AUTONOMOUS VEHICLES 21 2.1. Intelligent Traffic Systems 21 2.2. System Architecture for Autonomous Vehicles 22 2.3. Key components in AV classification 27 CHAPTER 3: METHODOLOGY AND DATA COLLECTION PROCEDURE 35 CHAPTER 4: FINDINGS AND DISCUSSION 39 4.1. RQ1: Do autonomous vehicles reduce traffic-related deaths 40 4.2. RQ2: Are there any challenges to using autonomous vehicles 63 4.3. RQ3: As a developing country, how effective is the use of autonomous vehicles for reducing traffic mortality 72 CHAPTER 5: CONCLUSION 76 5.1. Summary 76 5.2. Implications and Recommendations 80 5.3. Limitation of the study 91 Bibliography 93 List of Tables Table 1: The 6 Levels of Autonomous Vehicles Table 2: Search strings Table 3: Inclusion and exclusion criteria List of Figures Figure 1: Traffic Death Comparison with Europe Figure 2: Research strategy and study selection process List of Appendix Appendix 1: List of selected articles์„

    A review on AI Safety in highly automated driving

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    Remarkable progress in the fields of machine learning (ML) and artificial intelligence (AI) has led to an increased number of applications of (data-driven) AI systems for the partial or complete control of safety-critical systems. Recently, ML solutions have been particularly popular. Such approaches are often met with concerns regarding their correct and safe execution, which is often caused by missing knowledge or intransparency of their exact functionality. The investigation and derivation of methods for the safety assessment of AI systems are thus of great importance. Among others, these issues are addressed in the field of AI Safety. The aim of this work is to provide an overview of this field by means of a systematic literature review with special focus on the area of highly automated driving, as well as to present a selection of approaches and methods for the safety assessment of AI systems. Particularly, validation, verification, and testing are considered in light of this context. In the review process, two distinguished classes of approaches have been identified: On the one hand established methods, either referring to already published standards or well-established concepts from multiple research areas outside ML and AI. On the other hand newly developed approaches, including methods tailored to the scope of ML and AI which gained importance only in recent years

    Enabling technologies for urban smart mobility: Recent trends, opportunities and challenges

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    The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encour-aging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobilityโ€asโ€aโ€service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope
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