Simulation of the Impact of Connected and Automated Vehicles at a Signalized Intersection

Intersections are locations with higher likelihood of crash occurences and sources of traffic congestion as they act as bottlenecks compared with other parts of the roadway networks. Consequently, connected and automated vehicles (CAVs) can help to improve the efficiency of the roadways by reducing traffic congestion and traffic delays. Since CAVs are expected to take control from drivers (human control) in making many important decisions, thus they are expected to minimize driver (human) errors in driving tasks. Therefore, CAVs potential benefits of eliminating driver error include an increase in safety (crash reduction), smooth vehicle flow to reduce emissions, and reduce congestion in all roadway networks. Since CAV implementations are currently in early stages, researchers have found that the use of traffic modeling and simulation can assist decision makers by quantifying the impact of increasing levels of CAVs, helping to identify the effect this will have on future transportation facilities. The main objective of the current study was to simulate the potential impacts CAVs may have on traffic flow and delay at a typical urban signalized intersection. Essentially, to use a microscopic traffic simulation software to test future CAV technology within a virtual environment, by testing different levels of CAVs with their associated behaviors across several scenarios simulated. This study tested and simulated the impact of CAVs compared with conventional vehicles at a signalized intersection. Specifically, I analyzed and compared the operations of the signalized intersection when there are only conventional vehicles, conventional vehicles mixed with CAVs, and when there are only CAVs

Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks

The benefits of autonomous vehicles (AVs) are widely acknowledged, but there are concerns about the extent of these benefits and AV risks and unintended consequences. In this article, we first examine AVs and different categories of the technological risks associated with them. We then explore strategies that can be adopted to address these risks, and explore emerging responses by governments for addressing AV risks. Our analyses reveal that, thus far, governments have in most instances avoided stringent measures in order to promote AV developments and the majority of responses are non-binding and focus on creating councils or working groups to better explore AV implications. The US has been active in introducing legislations to address issues related to privacy and cybersecurity. The UK and Germany, in particular, have enacted laws to address liability issues, other countries mostly acknowledge these issues, but have yet to implement specific strategies. To address privacy and cybersecurity risks strategies ranging from introduction or amendment of non-AV specific legislation to creating working groups have been adopted. Much less attention has been paid to issues such as environmental and employment risks, although a few governments have begun programmes to retrain workers who might be negatively affected.Comment: Transport Reviews, 201

Selected Papers from the 5th International Electronic Conference on Sensors and Applications

This Special Issue comprises selected papers from the proceedings of the 5th International Electronic Conference on Sensors and Applications, held on 15–30 November 2018, on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups. In this 5th edition of the electronic conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Papers which attracted the most interest on the web or that provided a particularly innovative contribution were selected for publication in this collection. These peer-reviewed papers are published with the aim of rapid and wide dissemination of research results, developments, and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications

2nd Symposium on Management of Future motorway and urban Traffic Systems (MFTS 2018): Booklet of abstracts: Ispra, 11-12 June 2018

The Symposium focuses on future traffic management systems, covering the subjects of traffic control, estimation, and modelling of motorway and urban networks, with particular emphasis on the presence of advanced vehicle communication and automation technologies. As connectivity and automation are being progressively introduced in our transport and mobility systems, there is indeed a growing need to understand the implications and opportunities for an enhanced traffic management as well as to identify innovative ways and tools to optimise traffic efficiency. In particular the debate on centralised versus decentralised traffic management in the presence of connected and automated vehicles has started attracting the attention of the research community. In this context, the Symposium provides a remarkable opportunity to share novel ideas and discuss future research directions.JRC.C.4-Sustainable Transpor

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 159

This bibliography lists 257 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1976

Game Theory Relaunched

The game is on. Do you know how to play? Game theory sets out to explore what can be said about making decisions which go beyond accepting the rules of a game. Since 1942, a well elaborated mathematical apparatus has been developed to do so; but there is more. During the last three decades game theoretic reasoning has popped up in many other fields as well - from engineering to biology and psychology. New simulation tools and network analysis have made game theory omnipresent these days. This book collects recent research papers in game theory, which come from diverse scientific communities all across the world; they combine many different fields like economics, politics, history, engineering, mathematics, physics, and psychology. All of them have as a common denominator some method of game theory. Enjoy

GHG 배출에 따른 긍정적 파급효과가 있는 교차로 교통상황에 대한 핵심 정책요소로서의 스마트 신호등 기술에 대한 AHP 평가.

학위논문(석사) -- 서울대학교대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2023. 2. 황준석.기후변화는 전세계적으로 중요한 문제가 되었다. 오염, 특히 유해가스 배출에 의한 세계적인 기온 상승은 생물, 특히 2022년 기준 7십억 9천만명이 넘는 인간의 생존을 위협한다. 이러한 오염 경향은 1차 산업 혁명으로 거슬러 올라가며 자동차 산업에서 휘발유 첨가제를 도입하면서 전환점에 도달했다. 오늘날 차량 부문은 세계 첫번째 오염원이자 지구 기온 상승과 그에 따른 기후 변화의 주요 원인이다. 과학 전문지는 교통 역학을 분석하고 배출량 증가의 중요한 순간은 차량이 가장 효율적인 연료 소비 속도로 이동해야 하는 교통 혼잡 시간 동안임을 발견했다. 이를 바탕으로 교차로가 차량의 교통수요를 처리할 수 있는 실시간 대응기술이나 장치 부족으로 인한 교통체증의 가장 흔한 원인으로 판단된다. 이와 관련하여 중산층 및 고소득 국가는 교통 관리 시스템의 디지털 전환에 대한 대규모 투자를 통해 차량 교통 혼잡을 줄이기 위해 교통 및 도시 정책으로 인프라를 개선하고 도시를 스마트화하기 위해 여러 현대 기술을 도입하고 있다. 이 문제는 저소득 국가가 인구 요구를 우선하고 예산을 기후변화보다 식량, 주거, 건강, 교육, 안보, 교통에 할당할 때 발생한다. 그래서, 온실가스 오염으로 인한 교통 분야에 연관된 구조적 문제는 계속된다. 이 시나리오에서는 오염이 제거되거나 감소되거나 증가하든, 최종 영향은 세계적인 기온 변화에 달려 있다. 이 이슈를 더 철저하게 조사하기 위해서, 현재의 연구는 두 가지 논점을 제기한다. 첫번째는 이산화탄소 배출 증가와 교차로에서의 교통 정체가 연관되어 있는가?이고. 방법론으로서의 체계적인 문헌 검토를 사용했다. 135건 이상의 문서 스마트 교통신호와 온실가스 배출이. SLR 논문 데이터베이스에서 키워드 추출기가 구현되어 아키텍처, 플랫폼, 프레임워크, 시뮬레이터, 센서, 방법 및 알고리즘을 식별하고 각 항목에서 추출했다. 규화 단어 클라우드 방법을 사용하여, 총 241개의 서로 관련된 STL 기술을 확인하였고, 2단계에서 총 135개의 용어로 감소하였다. 관련 또는 밀접하게 관련된 기술을 조사한 후에는 분류 트리 맵을 사용하여 결과를 27 STL 주요 용어로 제한했다. 연구 질문은 Lu Jie, Watson, Bates 및 Kennedy, Towjua 및 Felix Isholab, Addy Majewski의 연구에 대한 SLR 식별으로 해결되었습니다; 그들 모두는 교통 체증과 정체 그리고 온실가스 배출 증가율 사이의 상관관계를 확인하기 위해 서로 다른 방법에 동의하고 제공했다. SLR의 집중적인 기술 설명, 추출 및 정규화를 통해 스마트 신호등 관련 기술, 아키텍처 및 프레임워크를 명확하게 식별할 수 있다.대체 계층 또는 차원을 제공함으로써 AHP 프로세스에서 중요한 단계 중 하나가 되도록 의도된 STL 기술 맵을 생성할 수 있습니다. 두 번째 연구 질문: "STL 시스템 기술의 SLR 식별을 바탕으로 교통 흐름을 개선하고 GHG-Co2 배출량을 줄이는 것을 목표로 예산 제약 하에서 교차로(신호등)의 교통 인프라 요소로 구현하기에 가장 적합한 기술은 무엇입니까?" 의사결정자와 정책 입안자가 가장 적합한 것을 결정할 수 있도록 하기 위해 분석 계층 프로세스(AHP)에 기반한 다중 기준 의사결정 분석(MCDA)에 따라 연구되었다.교차로의 차량 정체 관리와 관련된 IR 기술. 1970년대 토마스 새티 교수가 개발한 AHP 방법론은 전형적으로 계층적이고 서로 자주 대립하는 다수의 선택 기준 또는 변수를 기반으로 많은 대안 중에서 선택하는 데 도움이 되는 다중 기준 결정 과정이다. 선택 기준과 하위 기준을 신중하게 선택하고, 이를 올바르게 정의하며, SLR 기술, 식별 및 분류를 통해 상호 배타적인 문제임을 확인하는 것이 프로세스의 필수 구성 요소 중 하나입니다. 새티 기본 척도는 조사 과정에서 쌍체 비교를 수행하는 데 사용됩니다. 계층 구조는 하향식입니다. 이 방법의 주제는 질적 측면을 양적 측면으로 전환할 수 있는 목표 > 치수(STL 기능, STL 비용 및 교통 배출) > 기준 > 대안, 다양한 대안 간의 비교를 상당히 용이하게 하고 보다 객관적이고 신뢰할 수 있는 결과를 도출한다. 전문가 설문조사 문항을 기반으로 한 AHP 분석에 따르면,기존 신호등 인프라 업그레이드를 위한 STL 기술을 구현하기 위해 비용 차원이 현재 45.79%로 가장 중요한 요소이며, 그 다음이 효율 차원(41.61%)이다. 대안 수준에서는 유도 루프 센서가 23.67% 동의로 GHG 저감과 함께 교차로 고도화 및 교통흐름 개선에 가장 적합한 기술로 파악됐으며 영상차량 감지 15.02%, GPS 기반 기술 13.37% 순으로 나타났다. 본 연구의 목적은 저소득층 정부가 디지털 전환이나 스마트화에 투자하지 못하게 하는 재정적 제약을 해결하는 것이다. 제안은 SLR을 구현하여 STL과 관련된 스마트 기술, IoT, AI의 최첨단 기술을 파악하고 도로 교차로의 트래픽과 GHG 배출량 증가 간의 상관관계 및 과학적 증거를 찾는 것이다. 그러나 이 연구는 과학적 근거를 식별하고 제공하려는 시도 외에도 교통 관리 전문가와 실무자의 관점에서 이러한 기술을 평가함으로써 결과에 대한 높은 수준의 신뢰성을 제공한다. 따라서 의사 결정자와 정책 입안자 모두 현재의 연구를 바탕으로 유도 루프 센서가 교차로의 교통 흐름을 개선하고 신호등에 실시간 정보를 공급하는 최고의 스마트 기술임을 결정할 수 있다, 단기적으로는 높은 비용으로 이해할 수 있지만 장기적으로는 효율성 측면에서 이점이 있는 초기 투자의 높은 비용에도 불구하고.Climate change has become a critical issue around the world. Rising global temperatures caused by pollution, specifically noxious gas emissions, is threatening the survival of all living species, particularly humans, who will number more than 7.9 billion by 2022. This contamination proclivity dates back to the first industrial revolution and reached a tipping point with the implementation of gasoline additives by the automotive industry. Nowadays, the vehicular sector is the world's first source of pollution and the primary cause of rising global temperatures and the subsequent consequences of climate change. Scientific literature analyzes transportation dynamics and finds that critical moments in emission boost are during the traffic congestion hours when the vehicles are obligated to transit at the most efficient fuel consumption speed. Based on this, it is determined that road intersections are the most common source of traffic congestion due to lack of real-time responsive technologies or devices to handle vehicular traffic demand. Middle-upper and high-income nations have been working on implementing several modern technologies along with city infrastructure upgrades on the back of transportation and urban policies to reduce vehicular traffic congestion through large investments in the digital transformation of traffic management systems and moving the cities towards smartification. The problem arises when low- or low-middle-income governments are required to prioritize the needs of their populations and allocate budgets to projects, positioning climate change far behind food, housing, health, education, security, and transportation. Thus, structural problems related to the transportation field continue, resulting in Green House Gas (GHG) contamination. In this scenario, no matter whether the contamination is reduced, diminished, increased, or augmented, the final effect is accounted for as a global temperature change. To delve deeper into these issues, the current study poses two research questions: If a relationship between increasing GHG-Co2 emissions and vehicular traffic congestion levels at intersections exists? Using a systematic literature review (SLR) as the methodology, over 135 documents related to Smart Traffic Light (STL) and GHG emissions were categorized and filtered, yielding a total of 13 key papers. From the SLR papers database, a keyword extractor was implemented to identify and extract the architecture, platforms, frameworks, simulators, sensors, methods, and algorithms from each entry. A total of two hundred forty-one STL related technologies were identified, by using a normalization word cloud method it was reduced the total to one hundred thirty-five terms. In a second stage the results were limited to twenty-seven STL terms using a categorization tree map the related or closely related technologies were examined. The research question was addressed by the SLR identification of studies by Lu Jie, Watson, Bates, and Kennedy, Towojua and Felix Isholab, (Table 1). All these studies provide different methods for identifying the correlation between traffic jams and congestion and increasing GHG emissions. SLR's intensive technology description, extraction, and normalization resulted in a clear identification of smart traffic light-related technologies, architectures, and frameworks, allowing the creation of a STL technology map, which is intended to be one of the critical steps in the Analytical Hierarchy Process (AHP) by providing an alternative layer or dimension. The second research question is: Based on the SLRs identification of STL system technologies, which of these technologies are the most suitable to be implemented as an element of the traffic infrastructure at intersections (traffic lights) under budget constraints, targeted at improving traffic flows and reducing GHG-Co2 emissions? This was studied under a multicriteria decision analysis (MCDA), based on an (AHP), aimed to allow decision-makers and policymakers to determine which were the most suitable Fourth Industrial Revolution (4IR) technologies related to vehicular traffic congestion management at intersections. Developed by Professor Thomas Saaty in the 1970s, the AHP methodology is a multicriteria decision process that helps in choosing from among many alternatives based on a number of selection criteria or variables that are typically hierarchical and frequently at odds with one another. Choosing the selection criteria and sub-criteria carefully, defining them correctly, and ensuring that they are mutually exclusive are issues that were addressed by the SLR technologies. Identification and categorization are essential components of the process. The Saaty Fundamental Scale is used in the survey to perform a paired comparison. The hierarchical structure is top-down: the subject of this method is Objectives> Dimensions (STL Functions, STL Costs, and Traffic Emissions)> Criteria> Alternatives, which allows the transformation of qualitative aspects into quantitative ones, significantly facilitating a comparison between the various alternatives and producing more objective and reliable results. According to an AHP analysis which was based on an expert survey questionnaire, the cost dimension is the most important factor in implementing STL technologies for upgrading existing traffic light infrastructure at 45.79 percent, followed by the efficiency dimension (41.61 percent). At the alternatives level, experts identified that Inductive Loop Sensors were the best technology for upgrading the intersections and obtaining traffic flow improvements along with a GHG reduction with 23.67 percent agreement, followed by Video Vehicle Detection at 15.02 percent, and GPS-based technologies at 13.37 percent. The current study aims to address low-income governments' financial constraints which prevent them from investing in digital transformation or smartification. The study uses a SLR to identify the smart technologies, Internet of Things (IoT), and Artificial Intelligence (AI) related to STL state of art to find a correlation and scientific evidence between the traffic at road intersections and the increase in GHG emissions. However, in addition to identifying and providing scientific evidence, the research goes further by evaluating those technologies from the perspective of traffic management experts and practitioners, providing a high degree of reliability of the outcomes. Thus, both decision-makers and policymakers can base their policies on the present study to determine that the Inductive Loop Sensor is the best smart technology for improving traffic flows at intersections and feeding traffic lights with real-time information, despite the high initial investments, which can be understood as a high cost in the short-run but with benefits in terms of efficiency in the long run.Chapter 1. Introduction 1 1.1 Research Background 1 1.1.1 Environmental background 1 1.1.2 Vehicle industry background 3 1.1.3 Developing countries backgrounds 7 1.2 Definitions 10 1.3 Motivation 16 1.4 Problem statement 16 1.5 Research objective 18 1.6 Research questions 19 1.7 Research methodology 19 1.8 Research contribution 21 1.9 Research novelty 22 1.10 Outline 23 Chapter 2. Literature Review 23 Chapter 3.Data and Methodology 26 3.1 Systematic Literature Review (SLR) 26 3.1.1 Journal search and indexing databases 27 3.1.2 SLR Methodology 30 3.2 The Analytic Hierarchy Process (AHP) 34 3.2.1 AHP Survey questionnaire 38 3.2.2 Criteria description 39 3.2.3 Data normalizing 41 3.2.4 The AHP Methodology 46 Chapter 4. Data 50 4.1 AHPs Objective 50 4.2 First Layer: Dimensions 51 4.3 Second layer: Criteria 52 4.3.1 Efficiency dimension data analysis 52 4.3.2 Cost dimension data analysis 53 4.3.3 Emission dimensions data analysis 53 4.4 Third layer: Alternatives 54 Chapter 5. Results 55 Chapter 6. Conclusions 58 Bibliography. 62 Appendix 71 Appendix 1: Spearman Coefficient Correlation GS– WoS 73 Appendix 2: Spearman Coefficient Correlation GS - Scopus 74 Appendix 3: PRISMA 2020 Checklist 75 Appendix 4: AHP Expert Questionary 78 Appendix 5: AHP Electronic Survey Form 85 Appendix 6: AHP Top-Down Hierarchy Model 86 Acknowledgments 88 Abstract (Korean) 88석

Aeronautics and space report of the President, 1982 activities

Achievements of the space program are summerized in the area of communication, Earth resources, environment, space sciences, transportation, aeronautics, and space energy. Space program activities of the various deprtments and agencies of the Federal Government are discussed in relation to the agencies' goals and policies. Records of U.S. and world spacecraft launchings, successful U.S. launches for 1982, U.S. launched applications and scientific satellites and space probes since 1975, U.S. and Soviet manned spaceflights since 1961, data on U.S. space launch vehicles, and budget summaries are provided. The national space policy and the aeronautical research and technology policy statements are included

Numerical Computation, Data Analysis and Software in Mathematics and Engineering

The present book contains 14 articles that were accepted for publication in the Special Issue “Numerical Computation, Data Analysis and Software in Mathematics and Engineering” of the MDPI journal Mathematics. The topics of these articles include the aspects of the meshless method, numerical simulation, mathematical models, deep learning and data analysis. Meshless methods, such as the improved element-free Galerkin method, the dimension-splitting, interpolating, moving, least-squares method, the dimension-splitting, generalized, interpolating, element-free Galerkin method and the improved interpolating, complex variable, element-free Galerkin method, are presented. Some complicated problems, such as tge cold roll-forming process, ceramsite compound insulation block, crack propagation and heavy-haul railway tunnel with defects, are numerically analyzed. Mathematical models, such as the lattice hydrodynamic model, extended car-following model and smart helmet-based PLS-BPNN error compensation model, are proposed. The use of the deep learning approach to predict the mechanical properties of single-network hydrogel is presented, and data analysis for land leasing is discussed. This book will be interesting and useful for those working in the meshless method, numerical simulation, mathematical model, deep learning and data analysis fields