14,761 research outputs found

    Spartan Daily, March 7, 1997

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    Volume 108, Issue 31https://scholarworks.sjsu.edu/spartandaily/9107/thumbnail.jp

    Security of Cyber-Physical Systems

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    Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems

    Networking Transportation

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    Networking Transportation looks at how the digital revolution is changing Greater Philadelphia's transportation system. It recognizes several key digital transportation technologies: Artificial Intelligence, Big Data, connected and automated vehicles, digital mapping, Intelligent Transportation Systems, the Internet of Things, smart cities, real-time information, transportation network companies (TNCs), unmanned aerial systems, and virtual communications. It focuses particularly on key issues surrounding TNCs. It identifies TNCs currently operating in Greater Philadelphia and reviews some of the more innovative services around the world. It presents four alternative future scenarios for their growth: Filling a Niche, A Tale of Two Regions, TNCs Take Off, and Moore Growth. It then creates a future vision for an integrated, multimodal transportation network and identifies infrastructure needs, institutional reforms, and regulatory recommendations intended to help bring about this vision

    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„

    Mobile Car Rental System

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    This paper gives an overview of "M-commerce" approaches that allow car-rental companies in Malaysia to upgrade and optimize their business processes. First it addresses issues that are found in traditional car rental sector like slow turnaround and large amount of time needed to do reservation. Later it describes how these issues are solved using new mobile technology that provides true mobility, instant information and better customer service over traditional manual and wired online car rental business. To achieve a positive result author applied prototyping methodology tliroughout this project that quickly provides a system for the users to interact with. The successful result in the end of this project proved that mobile technology can easily and efficiently be applied to businesses that provide services, such as car rental companies. However drawbacks were also found, which are small memory, limited functionality and limited content of mobile devices that can be eliminated in future with new developments of wireless devices and communication infrastructures. Finally this project paper highlights the result of research and development activity that was carried out to develop new system, which will benefit car-rental companies in a way increasing number of customers, reducing operating cost and finally making them more competitive in our rushing world

    Public Bikesharing in North America During a Period of Rapid Expansion: Understanding Business Models, Industry Trends & User Impacts, MTI Report 12-29

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    Public bikesharingโ€”the shared use of a bicycle fleetโ€”is an innovative transportation strategy that has recently emerged in major cities around the world, including North America. Information technology (IT)-based bikesharing systems typically position bicycles throughout an urban environment, among a network of docking stations, for immediate access. Trips can be one-way, round-trip, or both, depending on the operator. Bikesharing can serve as a first-and-last mile connector to other modes, as well as for both short and long distance destinations. In 2012, 22 IT-based public bikesharing systems were operating in the United States, with a total of 884,442 users and 7,549 bicycles. Four IT-based programs in Canada had a total of 197,419 users and 6,115 bicycles. Two IT-based programs in Mexico had a total of 71,611 users and 3,680 bicycles. (Membership numbers reflect the total number of short- and long-term users.) This study evaluates public bikesharing in North America, reviewing the change in travel behavior exhibited by members of different programs in the context of their business models and operational environment. This Phase II research builds on data collected during our Phase I research conducted in 2012. During the 2012 research (Phase I), researchers conducted 14 expert interviews with industry experts and public officials in the United States and Canada, as well as 19 interviews with the manager and/or key staff of IT-based bikesharing organizations. For more information on the Phase I research, please see the Shaheen et al., 2012 report Public Bikesharing in North America: Early Operator and User Understanding. For this Phase II study, an additional 23 interviews were conducted with IT-based bikesharing organizations in the United States, Canada, and Mexico in Spring 2013. Notable developments during this period include the ongoing expansion of public bikesharing in North America, including the recent launches of multiple large bikesharing programs in the United States (i.e., Citi Bike in New York City, Divvy in Chicago, and Bay Area Bike Share in the San Francisco Bay Area). In addition to expert interviews, the authors conducted two kinds of surveys with bikesharing users. One was the online member survey. This survey was sent to all people for whom the operator had an email address.The population of this survey was mainly annual members of the bikesharing system, and the members took the survey via a URL link sent to them from the operator. The second survey was an on-street survey. This survey was designed for anyone, including casual users (i.e., those who are not members of the system and use it on a short-term basis), to take โ€œon-streetโ€ via a smartphone. The member survey was deployed in five cities: Montreal, Toronto, Salt Lake City, Minneapolis-Saint Paul, and Mexico City. The on-street survey was implemented in three cities: Boston, Salt Lake City, and San Antonio

    The Mobile Phone as a Globalising Artefact

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    This paper presents the findings from a qualitative study of mobile phones and youth culture in Melbourne, Australia. The focus is on how the social dynamic resulting from the use of such communications tools has created a paradigm shift that has changed the nature of inter-human relations. Mobile facilitated interaction is driving a fundamental change in social mores with respect to engagement and commitment, to notions of fluid time versus fixed time and ultimately to urban mobility. Connectivity is becoming central to what it means to have a social identity and users are responding to this by merging bits of data to create their โ€˜ideal digital selfโ€™ through which they communicate socially. This calls into question the nature of โ€˜digital identityโ€™, indicating it is not only about how much information can be restricted, but rather, what is revealed. While the results are based on a localized study, it is proposed that this phenomenon is happening across societies and that mobile phones themselves are becoming the globalizing icon of youth culture in the early 21st Century

    Road Accident Data Collection Systems in Developing and Developed Countries: A Review

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    The road accidents trigger major financial loss and casualties to the individual as well as the state as a whole. The intelligent safety systems are developed to provide all road users with a safe transport system. This approach acknowledges the sensitivity of individuals to extreme injury in road accidents and recognizes the need for the system for improvement. To establish a proper system for road accident prevention, records from prior accidents play a key role in the evaluation and prediction of the accident, damage, and consequences. Therefore, this study was performed to evaluate and comparing existing practices in developing and developed countries for collecting road accident data. Moreover, the manual and digital approaches of data collection are highlighted. Keeping this in mind, this review provides an overview of how developing countries currently collect their data and their data dissemination methods to extract such useful information, which could prove beneficial in deciding the road safety programs for the well-being of end-users

    Spartan Daily, May 14, 1993

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    Volume 100, Issue 68https://scholarworks.sjsu.edu/spartandaily/8426/thumbnail.jp

    Spartan Daily, March 4, 1994

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    Volume 102, Issue 26https://scholarworks.sjsu.edu/spartandaily/8526/thumbnail.jp
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