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DOE OSTI2020

SMART Mobility. Connected and Automated Vehicles Capstone Report

The U.S. Department of Energy’s Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium is a multiyear, multi-laboratory collaborative, managed by the Energy Efficient Mobility Systems Program of the Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, dedicated to further understanding the energy implications and opportunities of advanced mobility technologies and services. The first three-year research phase of SMART Mobility occurred from 2017 through 2019 and included five research pillars: Connected and Automated Vehicles, Mobility Decision Science, Multi-Modal Freight, Urban Science, and Advanced Fueling Infrastructure. A sixth research thrust integrated aspects of all five pillars to develop a SMART Mobility Modeling Workflow to evaluate new transportation technologies and services at scale. This report summarizes the work of the Connected and Automated Vehicles (CAVs) Pillar. This Pillar investigated the energy, technology, and usage implications of vehicle connectivity and automation and identified efficient CAV solutions. For information about the other Pillars and about the SMART Mobility Modeling Workflow, please refer to the relevant Pillar’s Capstone Report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

2020 Transportation Research Board Workshop: Infrastructure Spatial Sensing at Intersections: The Potential to Enhance Safety and Enable Automation

The sensing technology that is enabling vehicle automation also can revolutionize traffic intersection safety, control, and efficiency. Infrastructure spatial sensing technology refers to the deployment of sensors that can detect and track all objects in the field of view - for example, mounting lidar sensors, radar, and video imaging at an intersection and fusing the data to produce a three-dimensional dynamic operational awareness. Combining such sensing capability with fail-safe vehicle communications can facilitate applications such as eco-approach and departure, optimizing efficient vehicle-signal coordination, and reducing traffic accidents through increasing safety. Furthermore, evidence is mounting suggesting that infrastructure-based sensing is needed in order to safely deploy automated public mobility alongside the normal vehicle and pedestrian traffic in our cities. Six speakers were invited to present their work from various aspects (safety, efficiency, and automation) addressing infrastructure-based sensing at the workshop on Infrastructure Spatial Sensing hosted in Washington DC as part of the Transportation Research Board Annual Meeting in January 12, 2019. A summary of the presentation are included herein.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗

DOE OSTI2021

High Value Opportunities to Advance Automation in Electric Grid Control Rooms

Grid operators and electric utilities are increasingly driven to develop automated processes and introduce decision support tools to reduce cognitive demand on System Operations staff and aid in the operational decision-making process. However, System Operation staff are traditionally hesitant to implement and accept new solutions, automation processes, and tools within the control room. This paper explores high-value opportunities to advance automation in electric grid control rooms for the purpose of improving grid safety, reliability, and resiliency during normal and emergency operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Automation of Solid Oxyde Electrolyzer Cell (SOEC) & Stack Assembly

The work performed under this agreement before the No/Go decision amounted to the following: 1. Preliminary manufacturing requirements defined by business sensitivity, baseline processes & risk assessment; 2. Process & materials development, in-line gauge exploration, and preliminary automation work used to reduce risk & further refine equipment specifications; 3. “Request for Quote” issued to multiple suppliers for major equipment; 4. Application specific equipment, hardware, and fixturing will be more beneficial to fabricate inhouse; 5.Current proposals & estimates meet cycle time, capital spend, & direct labor; space is on target but requires awareness; 6. Team will continue to explore opportunities to reduce risk (dry time, traceability); 7. Go / No-Go, Purchase Orders, Equipment build & commissioning next All other future task were not completed because during the Go /No-Go decision it was confirmed this project was a "No-Go" and did not proceed past BP1; these included the following: 1. Preliminary manufacturing requirements defined by business sensitivity, baseline processes & risk assessment; 2. Process & materials development, in-line gauge exploration, and preliminary automation work used to reduce risk & further refine equipment specifications; 3. “Request for Quote” issued to multiple suppliers for major equipment; 4. Application specific equipment, hardware, and fixturing will be more beneficial to fabricate inhouse; 5. Current proposals & estimates meet cycle time, capital spend, & direct labor; space is on target but requires awareness; 6. Team will continue to explore opportunities to reduce risk (dry time, traceability) In final preparation of the termination of the Automation of Solid Oxyde Electrolyzer Cell (SOEC) & Stack Assembly, Cummins has purchased no equipment with government funds, and there is no government-owned property in Cummins possession related to this project. Minimal labor and travel were completed and paid. This acts as the Final technical report and concludes our business with DOE on this grant.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Computed Tomography Automation Architecture Developed from a Comprehensive Literature Review

This paper presents a literature review on techniques related to the computed tomography procedure that incorporate automation elements in their research investigations or industrial applications. Computed tomography (CT) is a non-destructive testing (NDT) technique in that the imaging and inspection are performed without damaging the sample, allowing for additional or repeated analysis if necessary. The reviewed literature is organized based on the steps associated with a general NDT task in order to define an end-to-end computed tomography automation architecture. The process steps include activities prior to image collection, during the scan, and after the data are collected. It further reviews efforts related to repeating this process based on a previous scan result. By analyzing the multiple existing but disparate efforts found in the literature, we present a framework for fully automating NDT procedures and discuss the remaining technical gaps in the developed framework.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1989

Advancing automation and robotics technology for the space station Freedom and for the US economy

In April 1985, as required by Public Law 98-371, the NASA Advanced Technology Advisory Committee (ATAC) reported to Congress the results of its studies on advanced automation and robotics technology for use on the Freedom space station. This material was documented in the initial report (NASA Technical Memorandum 87566). A further requirement of the law was that ATAC follow NASA's progress in this area and report to Congress semiannually. This report is the eighth in a series of progress updates and covers the period between October 1, 1988, and March 31, 1989. NASA has accepted the basic recommendations of ATAC for its Space Station Freedom efforts. ATAC and NASA agree that the thrust of Congress is to build an advanced automation and robotics technology base that will support an evolutionary Space Station Freedom program and serve as a highly visible stimulator, affecting the U.S. long-term economy. The progress report identifies the work of NASA and the Freedom study contractors. It also describes research in progress, and it makes assessments of the advancement of automation and robotics technology on the Freedom space station.

Robotics↗

NASA NTRS2005

On Automating Failure Mode Analysis and Enforcing its Integrity

This paper reports our experience on the development of a design-for-safety (DFS) workbench called Risk Assessment and Management Environment (RAME) for microelectronic avionics systems. Our objective is to transform DFS practice from an ad-hoc, inefficient, error-prone approach to a stringent engineering process such that DFS can keep up with the rapidly growing complexity of avionics systems. In particular, RAME is built upon an information infrastructure that comprises a fault model, a knowledge base, and a failure reporting/tracking system. This infrastructure permits systematic learning from prior projects and enables the automation of failure modes, effects and criticality analysis (FMECA). Among other unique features, the most important advantage of RAME is its capability of directly accepting design source code in hardware description languages (HDLs) for automated failure mode analysis, which enables RAME to be compatible and to evolve with most electronic-computer-aided-design systems. Through an initial experimental evaluation of the RAME prototype, we show that our approach to FMECA automation improves failure mode analysis turn-around-time, completeness, and accuracy.

design for safety↗

NASA NTRS2013

Automated Design of Propellant-Optimal, End-to-End, Low-Thrust Trajectories for Trojan Asteroid Tours

The Sun-Jupiter Trojan asteroids are celestial bodies of great scientific interest as well as potential resources offering water and other mineral resources for longterm human exploration of the solar system. Previous investigations under this project have addressed the automated design of tours within the asteroid swarm. This investigation expands the current automation scheme by incorporating options for a complete trajectory design approach to the Trojan asteroids. Computational aspects of the design procedure are automated such that end-to-end trajectories are generated with a minimum of human interaction after key elements and constraints associated with a proposed mission concept are specified.

Trojan asteroid↗

NASA NTRS2016

Becoming Earth Independent: Human-Automation-Robotics Integration Challenges for Future Space Exploration

Future exploration missions will require NASA to integrate more automation and robotics in order to accomplish mission objectives. This presentation will describe on the future challenges facing the human operator (astronaut, ground controllers) as we increase the amount of automation and robotics in spaceflight operations. It will describe how future exploration missions will have to adapt and evolve in order to deal with more complex missions and communication latencies. This presentation will outline future human-automation-robotic integration challenges.

human-robotic↗

NASA NTRS2017

Spaceport Command and Control System Automated Testing

The Spaceport Command and Control System (SCCS) is the National Aeronautics and Space Administrations (NASA) launch control system for the Orion capsule and Space Launch System, the next generation manned rocket currently in development. This large system requires high quality testing that will properly measure the capabilities of the system. Automating the test procedures would save the project time and money. Therefore, the Electrical Engineering Division at Kennedy Space Center (KSC) has recruited interns for the past two years to work alongside full-time engineers to develop these automated tests, as well as innovate upon the current automation process.

LCS↗

NASA NTRS2017

Spaceport Command and Control System Automation Testing

Testing↗

NASA NTRS2017

The Relationship Between Workload and Performance in Air Traffic Control: Exploring the Influence of Levels of Automation and Variation in Task Demand

In an air traffic environment, task demand is dynamic. However, previous research has largely considered the association of task demand and controller performance using conditions of stable task demand. Further, there is a comparatively restricted understanding of the influence of task demand transitions on workload and performance in association with different types and levels of automation that are available to controllers. This study used an air traffic control simulation to investigate the influence of task demand transitions, and two conditions of automation, on workload and efficiency-related performance. Findings showed that both the direction of the task demand variation and the amount of automation influenced the relationship between workload and performance. Findings are discussed in relation to capacity and arousal theories. Further research is needed to enhance understanding of demand transition and workload history effects on operator experience and performance, in both air traffic control and other safety-critical domains.

function allocation↗

NASA NTRS2018

Automated Scenario Generation for Human-in-the-Loop Simulations

Automated Multi-Aircraft Control System scenario generation for Human-in-the-Loop evaluations of air traffic management concepts is described. Methods for analyzing and comparing the seed-scenario generated using the automated process and the Human-in-the-Loop-scenario designed to meet the experiment objectives are discussed. The main findings are: (1) many of the characteristics of the seed-scenario used for constructing the Human-in-the-Loop-scenario are preserved in the Human-in-the-Loop Scenario, (2) landing characteristics of the traffic generated by the Multi-Aircraft Control System using the input scenario compare reasonably well with that intended in the input scenario, and (3) many of desired characteristics of the Human-in-the-Loop-scenario can be achieved by further automation.

SMART-NAS Testbed↗

NASA NTRS2016

Automating Microbial Directed Evolution For Bioengineering Applications

From a micro-biology perspective, directed evolution is a technique that uses controlled environmental pressures to select for a desired phenotype. Directed evolution has the distinct advantage over rational design of not needing extensive knowledge of the genome or pathways associated with a microorganism to induce phenotypes. However, there are currently limitations to the applicability of this technique including being time-consuming, error-prone, and dependent on existing assays that may lack selectivity for the given phenotype. The AADEC (Autonomous Adaptive Directed Evolution Chamber) system is a proof-of-concept instrument to automate and improve the technique such that directed evolution can be used more effectively as a general bioengineering tool. A series of tests using the automated system and comparable by-hand survival assay measurements have been carried out using UV-C radiation and Escherichia coli cultures in order to demonstrate the advantages of the AADEC versus traditional implementations of directed evolution such as random mutagenesis. AADEC uses UV-C exposure as both a source of environmental stress and mutagenesis, so in order to evaluate the UV-C tolerance obtained from the cultures, a manual UV-C exposure survival assay was developed alongside the device to compare the survival fractions at a fixed dosage. This survival assay involves exposing E. coli to UV-C radiation using a custom-designed exposure hood to control the flux and dose. Surviving cells are counted then transferred to the next iteration and so on for several iterations to calculate the survival fractions for each exposure iteration.This survival assay primarily serves as a baseline for the AADEC device, allowing quantification of the differences between the AADEC system over the manual approach. The primary data of comparison is survival fractions; this is obtained by optical density and plate counts in the manual assay and by optical density growth curve fits pre- and post-exposure in the automated case. This data can then be compiled to calculate trends over the iterations to characterize increasing UV-C resistance of the E.coli strains. The observed trends are statistically indistinguishable through several iterations from both sources.

Bioengineering↗

NASA NTRS2020

An Enhanced Autonomy Approach to Automated Trajectory Negotiation

Improved real-time decision-making capabilities in both civil transport avionics and airline dispatcher workstations are helping to improve commercial aviation operations in many ways. One emerging capability is the automated derivation of alternate flight plans that yield both flight cost savings and smoother workflow. This emerging capability may be complemented with automated trajectory negotiation capabilities. Here we explore such automated trajectory negotiation capabilities, potential benefit mechanisms, and the required tools, procedures, and architectures.

Trajectory↗

NASA NTRS1997

ARTSN: An Automated Real-Time Spacecraft Navigation System

ARTSN, the Automated Real-Time Spacecraft Navigation system is a real time system for the automated navigation of interplanetary spacecraft. The system processes the real time DSN radio metric data flow and generates updated spacecraft solutions and the associated covariance. ARTSN is designed modularly with the user interface input and output separated from the data analysis modules. Designed for distributed application, the system provided, for the first time, an automated method of processing radio metric navigation data for interplanetary spacecraft.

ARTSN↗

NASA NTRS2021

Vertiport Automation Software Architecture and Requirements

The purpose of Vertiport Automation Software Architecture and Requirements was developed to mature the Vertiport Automation System (VAS) described in the High-Density Automated Vertiport ConOps, into a set of artifacts that enable the development of a VAS prototype. The scope of document was to develop: (1) A VAS Software Architecture diagram that logically organizes VAS functionality into specific software components; (2) VAS Software Trade Study identifying existing commercial products and NASA research that can be used in part or with modifications to fulfill VAS functionality. (3) A set of VAS Functional Requirements which decompose the VAS concept into software functionality, including any interfaces and data flows needed; (4) A set of VAS Test Approaches describing a methodology for verification of the VAS Functional Requirements; and (5) An application user experience (UX) design study describing the general features needed in a VAS user interface.

Advanced Air Mobility↗