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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Dual Heat Pulse, Dual Layer Thermal Protection System Sizing Analysis and Trade Studies for Human Mars Entry Descent and Landing

NASA has been recently updating design reference missions for the human exploration of Mars and evaluating the technology investments required to do so. The first of these started in January 2007 and developed the Mars Design Reference Architecture 5.0 (DRA5). As part of DRA5, Thermal Protection System (TPS) sizing analysis was performed on a mid L/D rigid aeroshell undergoing a dual heat pulse (aerocapture and atmospheric entry) trajectory. The DRA5 TPS subteam determined that using traditional monolithic ablator systems would be mass expensive. They proposed a new dual-layer TPS concept utilizing an ablator atop a low thermal conductivity insulative substrate to address the issue. Using existing thermal response models for an ablator and insulative tile, preliminary hand analysis of the dual layer concept at a few key heating points indicated that the concept showed potential to reduce TPS masses and warranted further study. In FY09, the followon Entry, Descent and Landing Systems Analysis (EDL-SA) project continued by focusing on Exploration-class cargo or crewed missions requiring 10 to 50 metric tons of landed payload. The TPS subteam advanced the preliminary dual-layer TPS analysis by developing a new process and updated TPS sizing code to rapidly evaluate mass-optimized, full body sizing for a dual layer TPS that is capable of dual heat pulse performance. This paper describes the process and presents the results of the EDL-SA FY09 dual-layer TPS analyses on the rigid mid L/D aeroshell. Additionally, several trade studies were conducted with the sizing code to evaluate the impact of various design factors, assumptions and margins.

McGuire, Mary Kathleen↗
NASA NTRS2014

Exploration Technologies for Operations

Although the International Space Station (ISS) assembly has been completed, the Operations support teams continue to seek more efficient and effective ways to prepare for and conduct the ISS operations and future exploration missions beyond low earth orbit. This search for improvement has led to a significant collaboration between the NASA research and advanced software development community at NASA Ames Research Center and the Mission Operations community at NASA Johnson Space Center. Since 2001, NASA Ames Research Center has been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for several of the unmanned Mars missions operations. Since 2006, NASA Ames Research Center has also been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for manned operations support with the Mission Operations Directorate at NASA Johnson Space Center. This paper discusses the completion of the development and deployment of a variety of intelligent and human systems technologies adopted for manned mission operations. The technologies associated with the projects include advanced software systems for operations and human-centered computing. Human-centered computing looks to the processes and procedures that people do to perform any given job, then attempts to identify opportunities to improve these processes and procedures. In particular, for mission operations, improvements are quantified by specifically identifying how a tool can increase a persons efficiency, enhance a persons functional capability, andor improve the assurance of a persons decisions. The Ames development team has collaborated with the Mission Operations team to identify areas of efficiencies through technology infusion applications in support of the Plan, Train, and Fly activities of human-spaceflight mission operations. The specific applications discussed in this paper are in the areas of mission planning systems, mission operations design modeling and workflow automation, advanced systems monitoring, mission control technologies, search tools, training management tools, spacecraft solar array management, spacecraft power management, and spacecraft attitude planning. We discuss these specific projects between the Ames Research Center and the Johnson Space Centers Mission Operations Directorate, and how these technologies and projects are enhancing the mission operations support for the International Space Station. We also discuss the challenges, problems, and successes associated with long-distance and multi-year development projects between the research team at Ames and the Mission Operations customers at Johnson Space center. Finally, we discuss how these technology infusion applications and underlying technologies might be used in the future to support on-board operations of the crew and spacecraft systems as human exploration expands beyond low earth orbit to destinations in the solar system where communications delays will require more on-board autonomy and planning by the crew. Longer communications delays will require that the ground mission operations support will be primarily strategic in nature, while the tactical level of planning, systems monitoring and control, and failure analysisisolationrecovery will be the responsibility of both the spacecraft autonomous systems and the crew. Our expectation is that the technologies

mission operations↗
NASA NTRSDate not supplied

Technology Assessment and Modelling of Three Terminal Tandem Solar Cells for In-Space Utilization

NASA seeks a sustained human presence on the lunar surface. High-efficiency and resilient energy systems are critical to supporting habitats, scientific outposts, and lunar surface operations. Photovoltaics have long been the backbone of space power systems, transitioning from silicon solar cells to multi-junction III-V solar cells, which now dominate state-of-the-art (SOA) technology. Multi-junction cells achieve high efficiency by layering semiconductors, each absorbing a specific portion of the solar spectrum. However, efficiency gains are increasingly constrained by device physics and manufacturing complexity. Additionally, higher-order junctions pose challenges for accurate modelling and performance characterization due to difficulties in replicating the AM0 spectrum.

solar cells↗
NASA NTRS2002

Evaluation of High-Performance Space Nuclear Electric Generators for Electric Propulsion Application

Electric propulsion applications are enhanced by high power-to-mass ratios for their electric power sources. At multi-megawatt levels, we can expect thrust production systems to be less than 5 kg/kWe. Application of nuclear electric propulsion to human Mars missions becomes an attractive alternative to nuclear thermal propulsion if the propulsion system is less than about 10 kg/kWe. Recent references have projected megawatt-plus nuclear electric sources at specific mass values from less than 1 kg/kWe to about 5 kg/kWe. Various assumptions are made regarding power generation cycle (turbogenerator; MHD (magnetohydrodynamics)) and reactor heat source design. The present paper compares heat source and power generation options on the basis of a parametric model that emphasizes heat transfer design and realizable hardware concept. Pressure drop (important!) is included in the power cycle analysis, and MHD and turbogenerator cycles are compared. Results indicate that power source specific mass less than 5 kg/kWe is attainable, even if peak temperatures achievable are limited to 1500 K. Projections of specific mass less than 1 kg/kWe are unrealistic, even at the highest peak temperatures considered.

Woodcock, Gordon↗
DOE OSTI2023

Bucket Loading Trajectory Optimization for the Automated Wheel Loader

The bucket motion of a wheel loader during the loading process is investigated in this study. The optimal bucket loading trajectory can be obtained by solving an optimal control problem with the performance criteria of the fill factor , fuel efficiency and operation cycle time . A control-oriented model for the bucket loading operation is developed. Based on the control-oriented model, the bucket loading process is formulated as an optimal control problem with physical constraints. An open-source optimization solver, OpenOCL, is used to solve this problem. The simulation results show that the proposed method is effective in generating the optimal trajectory with significantly increased energy efficiency and productivity. Furthermore, this optimal trajectory can be employed as a reference for an automated wheel loader or as a driver advisory for a human operated wheel loader.

42 ENGINEERING↗
DOE OSTI2022

Continual Learning for Pattern Recognizers using Neurogenesis Deep Learning

Deep neural networks have emerged as a leading set of algorithms to infer information from a variety of data sources such as images and time series data. In their most basic form, neural networks lack the ability to adapt to new classes of information. Continual learning is a field of study attempting to give previously trained deep learning models the ability to adapt to a changing environment. Previous work developed a CL method called Neurogenesis for Deep Learning (NDL). Here, we combine NDL with a specific neural network architecture (the Ladder Network) to produce a system capable of automatically adapting a classification neural network to new classes of data. The NDL Ladder Network was evaluated against other leading CL methods. While the NDL and Ladder Network system did not match the cutting edge performance achieved by other CL methods, in most cases it performed comparably and is the only system evaluated that can learn new classes of information with no human intervention.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Integrated System Test Approaches for the NASA Ares I Crew Launch Vehicle

The Ares I Crew Launch Vehicle (CLV) is being developed by the U.S. National Aeronautics and Space Administration (NASA) to provide crew access to the International Space Station (ISS) and, together with the Ares V Cargo Launch Vehicle (CaLV), serves as one component of a future launch capability for human exploration of the Moon. During the system requirements definition process and early design cycles, NASA defined and began implementing plans for integrated ground and flight testing necessary to achieve the first human launch of Ares I. The individual Ares I flight hardware elements: the first stage five segment booster (FSB), upper stage, and J-2X upper stage engine, will undergo extensive development, qualification, and certification testing prior to flight. Key integrated system tests include the Main Propulsion Test Article (MPTA), acceptance tests of the integrated upper stage and upper stage engine assembly, a full-scale integrated vehicle dynamic test (IVDT), aerodynamic testing to characterize vehicle performance, and integrated testing of the avionics and software components. The Ares I-X development flight test will provide flight data to validate engineering models for aerodynamic performance, stage separation, structural dynamic performance, and control system functionality. The Ares I-Y flight test will validate ascent performance of the first stage, stage separation functionality, and a highaltitude actuation of the launch abort system (LAS) following separation. The Orion-1 flight test will be conducted as a full, un-crewed, operational flight test through the entire ascent flight profile prior to the first crewed launch.

Cockrell, Charles E., Jr.↗
NASA NTRSDate not supplied

Generation of Continental Scale Percent Tree Cover Product Using Deep-learning and Multi-scale Remote Sensing Data

Spatially explicit percent tree cover (TC) estimation is critical for mapping forest aboveground biomass and its dynamics. While various TC products have been developed, there has not been a generalized framework that can be applied to diverse terrestrial ecosystems due to underlain extreme complexities. Deep learning algorithms can learn a spatial pattern and radiometric characteristics of tree canopy as a robust approximation of physical or empirical models, and thus have emerged as promising and efficient tools for large-scale TC mapping. In this study, we synergistically use very high-resolution aerial imageries (National Agriculture Imagery Program, NAIP) and medium resolution Landsat data to map continental-scale TC (CONUS and Mexico) through a hierarchical deep learning approach (Convolutional Neural Network), i.e., NAIP TC generated from a NAIP model is utilized to train a Landsat model. The produced TC product (hereafter, NEX-TC) is able to capture the spatial pattern of TC distribution and its changes driven by natural disturbance and human land management. We further explore and analyze the reliability and potential uncertainty of the NEX-TC by comparing it to lidar- (lidar-TC), National Land Cover Database (NLCD-TC), and MODIS Vegetation Continuous Field (MODIS-TC). This evaluation practice reveals that TC products based on passive optical sensors tend to underestimate TC across all land cover types while Landsat-based TCs (i.e., NEX-TC & NLCD-TC) perform better than the coarser MODIS TC estimate. Our results show that the NEX-TC is generally comparable to NLCD-TC but it particularly outperforms NLCD-TC and MODIS-TC over the dense forests where lidar-TC indicates >80% TC. These results indicate that our hierarchical deep learning approach and TC product will be effective and useful for characterizing large-scale tree cover and possibly associated carbon dynamics.

Landsat↗
NASA NTRS2023

Fault Detection and Diagnosis in Spacecraft Electrical Power Systems

The ability to accurately identify and isolate failures in the electrical power system (EPS) is critical to ensure the reliability of spacecraft. This paper proposes a novel solution to the problem of fault detection and diagnosis in direct current (DC) electric power systems for spacecraft. Autonomous operation becomes essential during deep space missions that lack the ability to monitor and control the spacecraft from ground locations. The current state of EPS fault supervision is insufficient to guarantee highly reliable operation. To solve this issue, a combination of model-based and knowledge-based techniques are used in a hierarchical framework to improve the diagnostic performance of the system. Noise, disturbances, and modeling errors are considered in the design of the fault detection system. Practical considerations related to spacecraft flight hardware and software are accounted for in the system design for flight applications. To assess the functionality of the design, a wide array of failures are simulated in a series of experiments. The experiments showed that the technique improved the capability of the autonomous system by increasing the number of fault types diagnosed. The significance of this study is to provide a framework capable of advanced diagnostics of an EPS with little to no interaction from human operators.

Autonomous Power Systems↗
NASA NTRSDate not supplied

Comparison of Physical Workload Across Eva-Simulation Analog Environments: Hybrid Space Suit Simulator and Pressurized Suit Testing

NASA conducts research, testing, and training across a variety of analog environments to support characterization of human performance during Extravehicular Activities (EVAs). Time utilizing pressurized suits in an offloaded environment is both limited and expensive, making it challenging to carry out extensive research with these suits. The Human Physiology, Performance, Protection, and Operations (H-3PO) Laboratory at NASA Johnson Space Center designed a Hybrid Space Suit Simulator (HS3) as a low-cost, workload approximator and easy access research tool to provide relevant physical and cognitive workloads during simulated EVAs. A pilot study was conducted in a 1g analog environment where six healthy subjects (3 male, 3 female) underwent simulated 5-hour EVAs in the HS3. This study used a COSMED K5 portable metabolic analyzer and a Polar H10 heart rate monitor to evaluate physical workload during the EVAs. For direct comparison, EVA tasks and timelines were modeled after a similar study conducted in pressurized suits (Mark-III spacesuit, n=3 male; small xPGS spacesuit, n=3 female) at NASA’s Active Response Gravity Offload System (ARGOS) offloaded to Lunar gravity (1/6 g). The 1g HS3 data demonstrated increased metabolic rate when compared to pressurized, Lunar-offloaded suited simulated EVAs for certain tasks including the kneeling scoop (HS3: 1194±199 BTU/hr, ARGOS: 860±170 BTU/hr, p < 0.05) and 20 lb object relocation (HS3: 1651±136 BTU/hr, ARGOS: 1048±252.8 BTU/hr, p < 0.05), but it did not demonstrate any significant differences in heart rate (p > 0.05). Other simulated EVA tasks, such as a 500 m traverse (HS3: 1431±177 BTU/hr, ARGOS: 1212±294 BTU/hr, p > 0.05), showed similar workload profiles with no significant workload differences between HS3 and ARGOS. The HS3 is a useful research tool for increasing workloads in EVA research without pressurized suits, though it may overestimate workload during certain EVA tasks when used in 1g environments.

Zachary Wusk↗
DOE OSTI2025

Data-driven modeling of dynamic occupant thermostat override behavior for demand response applications

Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.

Sharma, Kunind [Northeastern University] (ORCID:00↗
NASA NTRS2019

Gravity as a Continuum: Effects of Altered Gravity on Drosophila Melanogaster Immunity

The impact of spaceflight on immune function is undoubtedly a critical focus in the area of space biology and human health research. Heat shock proteins (Hsp) are an evolutionarily conserved family of proteins that are expressed in response to cellular and physiological stressors, experienced during radiation exposure, confinement, circadian rhythm disruption, and altered gravity (hypergravity experienced at launch/landing and microgravity experienced in-flight). In particular, Hsp70 aids in the folding of proteins, facilitates the movement of proteins across the membranes during signal transductions and can stimulate innate immunity. Since Hsp70 is induced during cellular stress, and can act as a stimulator for innate immunity, we sought to address how a loss of Hsp70 affects immunity, under the stress-inducing model of acute and chronic hypergravity. Moreover, the effects of gravity as a continuum on the induction of Hsps and key immune genes were also assessed to determine if increased cellular stress, via increased gravity (g)-force, contributes to immune dysfunctions. For this, wildtype (W1118) and Hsp70 deficient (Hsp70null) Drosophila melanogaster were subjected to simulated hypergravity at increasing levels of g-force (1.2g, 3g, and 5g) for acute (1hr) and chronic (7-day) timepoints and were compared to 0g 'non-hypergravity' controls. Following simulation, whole bodies were sex-segregated, RNA was isolated and quantitative (q)PCR was performed to determine differential immune gene expression profiles. Further, functional output of hemocytes were assessed by a phagocytosis assay. Collectively, these studies evaluated the effects of Hsp70 in the context of immunity during acute and chronic hypergravity. Indeed, relevance for this work can directly translate to acute effects of launch/landing gravitational forces upon liftoff (~1.7g) and entry (~3.4g) that astronauts experience. In addition, the effects of chronic cellular stress is directly relevant to the immune health of astronauts on long duration missions, as well. Thus, as we approach the goal of returning to the Moon and landing the first humans on Mars, an evaluation of gravity as a continuum and the stress-inducing effects of altered gravity experienced during spaceflight on astronaut immunity and health are necessary.

Olivieri, Joe↗
DOE OSTI2023

Evaluation of Copper Chelation Therapy in a Transgenic Rat Model of Cerebral Amyloid Angiopathy

Cerebral amyloid angiopathy (CAA) is characterized by the accumulation of the amyloid β (Aβ) protein in blood vessels and leads to hemorrhages, strokes, and dementia in elderly individuals. Recent reports have shown elevated copper levels colocalized with vascular amyloid in human CAA and Alzheimer’s disease patients, which have been suggested to contribute to cytotoxicity through the formation of reactive oxygen species. Here, we treated a transgenic rat model of CAA (rTg-DI) with the copper-specific chelator, tetrathiomolybdate (TTM), via intraperitoneal (IP) administration for 6 months to determine if it could lower copper content in vascular amyloid deposits and modify CAA pathology. In this work, results showed that TTM treatment led to elevated Aβ load in the hippocampus of the rTg-DI rats and increased microbleeds in the wild type (WT) animals. X-ray fluorescence microscopy was performed to image the distribution of copper and revealed a surprising increase in copper colocalized with Aβ aggregates in TTM-treated rTg-DI rats. Unexpectedly, we also found an increase in the copper content in unaffected vessels of both rTg-DI and WT animals. These results show that IP administration of TTM was ineffective in removing copper from vascular Aβ aggregates in vivo and increased the development of disease pathology in CAA.

36 MATERIALS SCIENCE↗
DOE OSTI2025

One‐at‐a‐Time Parameter Perturbation Ensemble of the Community Land Model, Version 5.1

Comprehensive land models are subject to significant parametric uncertainty, which can be hard to quantify due to the large number of parameters and high model computational costs. We constructed a large parameter perturbation ensemble (PPE) for the Community Land Model version 5.1 with biogeochemistry configuration (CLM5.1-BGC). We performed more than 2,000 simulations perturbing 211 parameters across six forcing scenarios. This provides an expansive data set, which can be used to identify the most influential parameters on a wide range of output variables globally, by biome, or by plant functional type. We found that parameter effects can exceed scenario effects and that a small number of parameters explains a large fraction of variance across our ensemble. The most important parameters can differ regionally and also based on the forcing scenario. The software infrastructure developed for this experiment has greatly reduced the human and computer time needed for CLM PPEs, which can facilitate routine investigation of parameter sensitivity and uncertainty, as well as automated calibration.

Kennedy, Daniel [NSF National Center for Atmospher↗
NASA NTRS1985

Image gathering and processing - Information and fidelity

In this paper we formulate and use information and fidelity criteria to assess image gathering and processing, combining optical design with image-forming and edge-detection algorithms. The optical design of the image-gathering system revolves around the relationship among sampling passband, spatial response, and signal-to-noise ratio (SNR). Our formulations of information, fidelity, and optimal (Wiener) restoration account for the insufficient sampling (i.e., aliasing) common in image gathering as well as for the blurring and noise that conventional formulations account for. Performance analyses and simulations for ordinary optical-design constraints and random scences indicate that (1) different image-forming algorithms prefer different optical designs; (2) informationally optimized designs maximize the robustness of optimal image restorations and lead to the highest-spatial-frequency channel (relative to the sampling passband) for which edge detection is reliable (if the SNR is sufficiently high); and (3) combining the informationally optimized design with a 3 by 3 lateral-inhibitory image-plane-processing algorithm leads to a spatial-response shape that approximates the optimal edge-detection response of (Marr's model of) human vision and thus reduces the data preprocessing and transmission required for machine vision.

Huck, F. O.↗
NASA NTRS2000

Separation of Carbon Monoxide and Carbon Dioxide for Mars ISRU-Concepts

Solid oxide electrolyzers, such as electrolysis cells utilizing yttria-stabilized zirconia, can produce oxygen from Mars atmospheric carbon dioxide and reject carbon monoxide and unreacted carbon dioxide in a separate stream. The oxygen-production process has been shown to be far more efficient if the high-pressure, unreacted carbon dioxide can be separated and recycled back into the feed stream. Additionally, the mass of the adsorption compressor can be reduced. Also, the carbon monoxide by-product is a valuable fuel for space exploration and habitation, with applications from fuel cells to production of hydrocarbons and plastics. In our research, we will design, construct, and test an innovative, robust, low mass, low power separation device that can recover carbon dioxide and carbon monoxide for Mars ISRU. Such fundamental process technology, involving gas-solid phase separation in a reduced gravitational environment, will help to enable Human Exploration and Development of Space. The separation device will be scaled to operate with a CO2 sorption compressor and a zirconia electrolysis device built at the NASA Ames Research Center and the University of Arizona, respectively. In our research, we will design, construct, and test an innovative, robust, low mass, low power separation device that can recover carbon dioxide and carbon monoxide for Mars ISRU, Such fundamental process technology, involving gas-solid phase separation in a reduced gravitational environment, will help to enable Human Exploration and Development of Space. The separation device will be scaled to operate with a CO2 sorption compressor and a zirconia electrolysis device built at the NASA Ames Research Center and the University of Arizona, The separation device will be scaled to operate with a CO2 sorption compressor and a zirconia electrolysis device built at the NASA Ames Research Center and the University of Arizona, Research needs for the design shown are as follows: (1) The best adsorbent for the process must be determined. (2) Adsorption isotherms must be measured, both for pure components and mixtures. (3) Mathematical modeling must be performed to provide a solid framework for design. (4) The separation system must be constructed and tested. (5) System integration must be studied.

LeVan, M. Douglas↗
NASA NTRS2002

A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation

Near-infrared spectroscopy (NIRS) has been used to noninvasively monitor adult human brain function in a wide variety of tasks. While rough spatial correspondences with maps generated from functional magnetic resonance imaging (fMRI) have been found in such experiments, the amplitude correspondences between the two recording modalities have not been fully characterized. To do so, we simultaneously acquired NIRS and blood-oxygenation level-dependent (BOLD) fMRI data and compared Delta(1/BOLD) (approximately R(2)(*)) to changes in oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations derived from the NIRS data from subjects performing a simple motor task. We expected the correlation with deoxyhemoglobin to be strongest, due to the causal relation between changes in deoxyhemoglobin concentrations and BOLD signal. Instead we found highly variable correlations, suggesting the need to account for individual subject differences in our NIRS calculations. We argue that the variability resulted from systematic errors associated with each of the signals, including: (1) partial volume errors due to focal concentration changes, (2) wavelength dependence of this partial volume effect, (3) tissue model errors, and (4) possible spatial incongruence between oxy- and deoxyhemoglobin concentration changes. After such effects were accounted for, strong correlations were found between fMRI changes and all optical measures, with oxyhemoglobin providing the strongest correlation. Importantly, this finding held even when including scalp, skull, and inactive brain tissue in the average BOLD signal. This may reflect, at least in part, the superior contrast-to-noise ratio for oxyhemoglobin relative to deoxyhemoglobin (from optical measurements), rather than physiology related to BOLD signal interpretation.

Non-NASA Center↗
DOE OSTI2019

Automated Vehicles in Hazardous Merging Traffic: A Chance-Constrained Approach

To realize the energy efficiency and productivity benefits of automated driving, control algorithms must function safely among conventional vehicles. Prototype tests on public roads have revealed a trend of human-driven vehicles rear-ending automated ones. A popular belief holds that unusually conservative control algorithms play a role in such collisions. In August 2018, an automated vehicle was rear-ended while waiting to merge. Inspired by that incident, this paper examines a resemblant scenario in simulation using model predictive control for the automated vehicle. Constraint setup alternatives to avoid collisions with inattentive following vehicles are proposed and assessed in this simulation environment. In one variant, imminent rear-end collisions are detected and constraints are modified to promote more aggressive merging during such an event. Results show that higher-performing chance constraint designs can reduce collision probability, but may have other adverse effects depending on the particular algorithm.

Dollar, R. Austin↗