A safety-based decision making architecture for autonomous systems

  • 2.74 MB
  • English
National Aeronautics and Space Administration, National Technical Information Service, distributor , [Washington, DC, Springfield, Va
Computer architecture., Artificial intellig
Other titlesSafety based decision making architecture for autonomous systems.
Statementby Joseph C. Musto and L.K. Lauderbaugh.
SeriesCIRSSE report -- #98., [NASA contractor report] -- NASA CR-191864.
ContributionsLauderbaugh, L. K., United States. National Aeronautics and Space Administration.
The Physical Object
Pagination1 v.
ID Numbers
Open LibraryOL16384758M

Get this from a library. A safety-based decision making architecture for autonomous systems. [Joseph C Musto; L K Lauderbaugh; United States. National Aeronautics and Space Administration.]. A tactical-level lane-driving and decision-making model that considers multisource information in a complex and dynamic urban environment is critical for the development of autonomous vehicles.

The decision-making architecture of an autonomous s ystem consists of three levels with decreasing decisional a utonomy [6 ]: the h igher “s trategic” level manage s goals.

Description A safety-based decision making architecture for autonomous systems FB2

convey the message autonomous vehicles are not science fiction anymore and these systems can be implemented on normal cars. A good example to a project Logic Processing Unit Sensors Mechanical Control Systems -laser sensors -cameras -radars -ultrasonic sensors -GPS, etc.

-Software -Decision making -Checking functionality -User interfaceFile Size: 1MB. [] Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving. [] An Empirical Evaluation of Deep Learning on Highway Driving. [] Self-Driving Vehicles: The Challenges and Opportunities Ahead.

[] Making Bertha Drive - An Autonomous Journey on a Historic Route. safety-based control are combined to avoid collisions. It was found that combination of DRL and safety-based control performs well in most scenarios. In order to enable DRL to escape local optima, speed up the training process and avoid danger conditions or accidents, Survival-Oriented Reinforce-ment Learning (SORL) model is proposed in [ Multi-UAV Operations are an area of great interest in government, industry, and research community.

In multi-UAV operations, a group of unmanned aerial vehicles (UAVs) are deployed to carry out missions such as search and rescue or disaster relief.

Details A safety-based decision making architecture for autonomous systems PDF

As multi-UAV systems operate in an open operational environment, many disrupting events can occur. To this end, resilience of these systems is of Cited by: 1. John X. Wang is Senior Principal Functional Safety Engineer at Flex.

Wang has authored/coauthored numerous books and papers on reliability engineering, risk engineering, engineering decision making under uncertainty, robust design and Six Sigma, lean manufacturing, green electronics manufacturing, cellular manufacturing, and industrial design engineering - inventive problem solving.

In reinforcement learning (RL) [Sutton and Barto], an agent learns to behave in an unknown environment based on the rewards it single objective RL these rewards are scalar.

However, most real-life problems are more naturally expressed with multiple objectives. For example, autonomous drivers need to minimize travel time and fuel consumption, while maximizing safety [Xiong et al. 6 Sciences for Maneuver. The Panel A safety-based decision making architecture for autonomous systems book Mechanical Science and Engineering at the Army Research Laboratory (ARL) conducted its review of ARL’s vehicle intelligence (VI) programs—intelligence and control, machine-human interaction, and perception—at Aberdeen, Maryland, on July, and its review of ARL’s vehicle science and technology programs—platform mechanics, energy and.

Intelligent connected vehicles (ICVs) are believed to change people’s life in the near future by making the transportation safer, cleaner and more comfortable. Although many prototypes of ICVs have been developed to prove the concept of autonomous driving and the feasibility of improving traffic efficiency, there still exists a significant gap before achieving mass production of high-level ICVs.

Cathy F. Gautreaux Deputy Administrator Federal Motor Carrier Safety Administration Cathy F. Gautreaux is the Deputy Administrator of the Federal Motor Carrier Safety Administration. As the Agency’s second-ranking official, Cathy is principally responsible for overseeing FMCSA’s day-to-day operational programs and activities, which are performed by more than 1, employees located in its.

System Safety Engineer for self-driving cars at Uber Advanced Technology Group. Contribution areas included quantitative safety analysis framework, functional hazard assessment, fault tree.

Fig. Steps to Create a New Blockchain Transaction. Blockchain applications in smart Logistics Smart logistics is typically defined by the use of new technologies such as IoT, AI, and Cloud computing. More- over, it allows a transfer of autonomy, intelligence, and autonomous decision-making : Yassine Issaoui, Azeddine Khiat, Ayoub Bahnasse, Hassan Ouajji.

International Conference on Transportation Engineering Decision-Making Model for Multi-Ship Collision Avoidance Based on Adaptive Genetic Algorithm. Decision Support System Design for Urban Public Transit Safety Based on Geography Information System.

Peng Hu and Huapu Lu. - the right information to make safety-based decisions moving forward. The stakeholder’s interests and backgrounds were different, and each needed information on the IRT model and its results (e.g., the crash rates of the prioritized carrier population compared with carriers prioritized by SMS) to inform their decision making.

QSMM, a recursive acronym for "QSMM State Machine Model", is a framework for learning finite automatons that perform goal-directed interaction with entities which exhibit deterministic or stochastic behavior.

The learning process can be carried out in real time together with the interaction process. A basic building block for supporting state models of finite automatons is adaptive. The steady-state flow is examined for a car-following model in which the acceleration at time t of a car attempting to follow a lead car is proportional to the relative velocity at a time t − Δ and in which the sensitivity λ is no longer taken constant as in previous work but is inversely proportional to the car spacing.

The characteristics of the steady-state flow for this model are Cited by: The specific topics discussed include requirements engineering for embedded software systems, tools and methods used in the automotive industry, software product lines, architectural frameworks, various related ISO standards, functional safety and safety cases, cooperative intelligent transportation systems, autonomous vehicles, and security.

The research on “AI”-based self-adaptation decision making is far from mature, an enormous technical challenges still have to be overcome [19,], especially the safety and correctness verification problem. As SCPS is safety-critical, it is important to guarantee the C&D of self-adaptation : Peng Zhou, Decheng Zuo, Kun Mean Hou, Zhan Zhang, Jian Dong, Jian-Jin Li, Haiying Zhou.

Introduction. In the global context, the European electronic industry faces stiff competition. Electronic systems are becoming more and more complex and software intensive, which calls for novel engineering practices to tackle advances in productivity and quality of these, now, cyber-physical systems.

Model-Driven Engineering (MDE) refers to a system development methodology where Cited by: Abstract. Proceedings of the Fourth International Conference on Transportation Engineering, held in Chengdu, China, OctoberSponsored by Southwest Jiaotong University; China Communications and Transportation Association; the Transportation & Development Institute of ASCE; Mao Yisheng Science and Technology Education Foundation; and Zhan Tianyou Development.

CH Purpose. The Defense Acquisition Guidebook (DAG), Chapter 8, provides guidance on the process and procedures for managing risks through planning and executing an effective and affordable test and evaluation (T&E) program that enables the Department of Defense (DoD) to.

In general terms, four sub-systems describe an RFID system’s architecture (): (1) a transponder or tag, which contains the identification data, (2) a reader to interact directly with the tag exchanging information with it, (3) a RFID middleware and (4) a business and/or information management middleware supports RFID tag data management by handling devices, filtering, collecting Cited by: 2.

Selecting the Best By Comparing Simulated Systems In a Group of Three When Variances are Known and Unequal. Dieker and Seong-Hee Kim (Georgia Institute of Technology) Calibration of a decision making process in a simulation model by a bicriteria optimization problem.

Fermin Mallor and Cristina Azcarate (Public University of Navarre. Scientific Research Publishing is an academic publisher with more than open access journal in the areas of science, technology and medicine. It also publishes. The book caters to a diverse audience; anyone who uses analytical techniques in decision making will need this book.

Of the many books available on this subject, most are not broad enough, not. Smart City Implementation Models Based on IoT Technology free download Abstract. IoT (Internet of Things) is the network of physical objects-devices, vehicles, buildings and other items embedded with electronics, software, sensors, and network connectivity-that.

Miguel Teixeira, Pedro M. d'Orey and Zafeiris Kokkinogenis, "Simulating Collective Decision-Making for Autonomous Vehicles Coordination Enabled by Vehicular Networks: A Computational Social Choice Perspective," Simulation Modelling Practice and Theory, vol.

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98, pp.January Utility Cybersecurity System Integration Considerations with Respect to Reliability and Safety Based on Current Standards Changes.

Room: AB; Session Number:Cybersecurity and Incidence Response 2B; Wednesday, Janu PM - PM. decision-making systems to enable humans and machines to work together and to agree on common decisions, as well as how to deal with the lack of agreement in some situations.

Also, there is another important discussion arising in the context of human-machine collaboration that must be investigated.IEEE membership offers access to technical innovation, cutting-edge information, networking opportunities, and exclusive member benefits.

Members support IEEE's mission to advance technology for humanity and the profession, while memberships build a platform to introduce careers in technology to students around the world.Amy C. Edmondson is the Novartis Professor of Leadership and Management at the Harvard Business School, a chair established to support the study of human interactions that lead to the creation of successful enterprises that contribute to the betterment of son has been recognized by the biannual Thinkers50 global ranking of management thinkers sinceand most recently was.