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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
DOE OSTI2026

Cooperative Automated Cohort Driving on Connected Infrastructure, Arterial Roadways, and Highways: Final Project Demonstration and System-of-Systems Model Correlation

This project seeks to synergize vehicle automated driving and connectivity data to improve mobility and energy efficiency of groups of mixed vehicles operating in close proximity (vehicle cohort) on various infrastructure. A custom cellular communication network links vehicles operating as a cohort with infrastructure to a centralized system-of-systems digital twin with an AI-based optimal behavior planner. The data contained in this set are from final testing and technology demonstrations to U.S. Department of Energy staff at the American Center for Mobility. The data contain single-lane, single-light scenarios; multi-lane, multi-light arterial scenarios; and limited-access highway scenarios. All test cases were derived from simulations and replicated on the test track. The project employed two and four light-duty vehicles with connectivity and drive automation for the testing. The baseline scenario without connectivity was run under the control of the system-of-systems centralized planner but operating each vehicle with an intelligent driver model controlling the velocity, lane utilization, and vehicle gap. This was to ensure the highest compatibility with the simulation in terms of dynamic behavior. The connected cohort case utilized AI optimization to perform coordinated and cooperative control for energy, as well as safe, comfortable behavior for the cohort. The dataset is appropriately named with unconnected and connected designations, with comparisons sharing the same run index number. The included PowerPoint and PDF files describe the test setup and provide an overview of results from the project. ![image](de-EE0009209_March_2023_Data_Arterial_Scenario_Results.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Energy-Efficient Maneuvering of Connected and Automated Vehicles (CAVs) with Situational Awareness at Intersections (Final Progress Report)

The increased development of Connected and Automated Vehicle (CAV) systems, currently used for safety and driver convenience, presents new opportunities to improve the energy efficiency of vehicles. Southwest Research Institute (SwRI) achieved a 20% energy consumption reduction in a 2017 Toyota Prius Prime plug-in hybrid by using connectivity (V2V, V2I, V2X) as part of the Next Generation Energy Technologies for Connected and Automated on-Road Vehicles (NEXTCAR) program. The energy consumption gains were achieved by a combination of vehicle dynamics and powertrain control algorithms with a focus on SAE L1 and L2 automated vehicles where a human is still responsible for safe operation. SwRI is now involved in NEXTCAR-II, focusing on energy-efficient control tech for SAE Level 4/5 automated vehicles, aiming for a 30% energy reduction compared to stock hybrids. The rise of Mobility as a Service (MaaS) is driving investments in L4 and L5 automated vehicles. A study by the University of Michigan shows these vehicles might increase energy use and emissions by 3-20%. Technology similar to NEXTCAR can enhance energy efficiency in highly automated vehicles, leveraging improved sensing and actuation capabilities. While the NEXTCAR programs targeted energy efficiency improvements for a single vehicle, this program adopts a more expansive approach. It places its focus on understanding and testing the cumulative effects within a region or corridor, aiming to assess how a subset of vehicles equipped with NEXTCAR-style technologies influence the overall energy consumption of all vehicles traveling within that area. Additionally, the program explores infrastructure-based mobility solutions to optimize efficiency, and seeks to understand and quantify public perception and likelihood of technology adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1991

Automated site characterization for robotic sample acquisition systems

A mobile, semi-autonomous vehicle with multiple sensors and on-board intelligence is proposed for performing preliminary scientific investigations on extraterrestrial bodies prior to human exploration. Two technologies, a hybrid optical-digital computer system based on optical correlator technology and an image and instrument data analysis system, provide complementary capabilities which might be part of an instrument package for an intelligent robotic vehicle. The hybrid digital-optical vision system could perform real-time image classification tasks using an optical correlator with programmable matched filters under control of a digital microcomputer. The data analysis system would analyze visible and multiband imagery to extract mineral composition and textural information for geologic characterization. Together these technologies would support the site characterization needs of a robotic vehicle for both navigational and scientific purposes.

Scholl, Marija S.↗
DOE OSTI2024

Advance Local Mobility Through Energy Efficient Mobility Systems Technologies

Everyone deserves reliable, affordable, and safe transportation to connect people to jobs, healthcare, education, and recreation. Our transportation systems are interconnected, multimodal networks working together to move people and goods. These systems are dynamic and are being reshaped by factors such as population trends, new technologies, shifting labor models, economic forces, and changing climate. Energy efficient mobility systems (EEMS) technologies can help transportation planners ensure changes in our transportation systems are equitable and sustainable by improving energy efficiency, travel time, and affordability, as well as overall access to mobility. Transportation planners and decision makers can use the following EEMS tools and strategies to advance local mobility.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1988

A robotic system for automation of logistics functions on the Space Station

Spacecraft inventory management is currently performed by the crew and as systems become more complex, increased crew time will be required to perform routine logistics activities. If future spacecraft are to function effectively as research labs and production facilities, the efficient use of crew time as a limited resource for performing mission functions must be employed. The use of automation and robotics technology, such as automated warehouse and materials handling functions, can free the crew from many logistics tasks and provide more efficient use of crew time. Design criteria for a Space Station Automated Logistics Inventory Management System is focused on through the design and demonstration of a mobile two armed terrestrial robot. The system functionally represents a 0 gravity automated inventory management system and the problems associated with operating in such an environment. Features of the system include automated storage and retrieval, item recognition, two armed robotic manipulation, and software control of all inventory item transitions and queries.

Martin, J. C.↗
NASA NTRSDate not supplied

A Proposed Taxonomy for Advanced Air Mobility

There has been a large growth in interest of utilizing new technologies—most notably electrified propulsion and automation—as well as new business models to bring aviation services into the daily lives of a greater segment of society. Generally, these services are envisioned to augment existing ground modes of transportation or to enable new operating capabilities for shorter-range aviation missions. These services, which have become known as advanced air mobility (AAM), include passenger transportation, cargo transportation, and aerial work missions, such as aerial photography. In this paper we describe advanced air mobility and provide a framework based on demand and supply concepts that can be used for developing a taxonomy for AAM with a focus on passenger applications. This taxonomy is intended to facilitate the nascent AAM stakeholder community in adopting a common terminology and to enable better coordination among disparate AAM research and development activities.

advanced air mobility↗
DOE OSTI2020

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL’s Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗
NASA NTRS2005

Trusted Autonomy for Space Flight Systems

NASA has long supported research on intelligent control technologies that could allow space systems to operate autonomously or with reduced human supervision. Proposed uses range from automated control of entire space vehicles to mobile robots that assist or substitute for astronauts to vehicle systems such as life support that interact with other systems in complex ways and require constant vigilance. The potential for pervasive use of such technology to extend the kinds of missions that are possible in practice is well understood, as is its potential to radically improve the robustness, safety and productivity of diverse mission systems. Despite its acknowledged potential, intelligent control capabilities are rarely used in space flight systems. Perhaps the most famous example of intelligent control on a spacecraft is the Remote Agent system flown on the Deep Space One mission (1998 - 2001). However, even in this case, the role of the intelligent control element, originally intended to have full control of the spacecraft for the duration of the mission, was reduced to having partial control for a two-week non-critical period. Even this level of mission acceptance was exceptional. In most cases, mission managers consider intelligent control systems an unacceptable source of risk and elect not to fly them. Overall, the technology is not trusted. From the standpoint of those who need to decide whether to incorporate this technology, lack of trust is easy to understand. Intelligent high-level control means allowing software io make decisions that are too complex for conventional software. The decision-making behavior of these systems is often hard to understand and inspect, and thus hard to evaluate. Moreover, such software is typically designed and implemented either as a research product or custom-built for a particular mission. In the former case, software quality is unlikely to be adequate for flight qualification and the functionality provided by the system is likely driven largely by the need to publish innovative work. In the latter case, the mission represents the first use of the system, a risky proposition even for relatively simple software.

Freed, Michael↗
NASA NTRS2021

Resilience Engineering's Potential for Advanced Air Mobility (AAM)

The national airspace (NAS) will rapidly evolve in the next ten to twenty years. Plans for Advanced Air Mobility (AAM) during that period envision highly automated airspace management systems and electrically powered vehicles. AAM concepts also anticipate limited human roles. The goal of limiting the human role is to minimize the potential for misadventures, yet how the human role is limited needs to be carefully considered in order to also preserve the potential for human successes. The field of resilience engineering (RE) focuses on how systems can change in order to seize an opportunity or withstand an unforeseen challenge. RE methods rely on the use of empirical data to optimize the ability of any system to adapt. RE studies have shown how individual and team initiatives ensure resilient system performance by creating safety through flexibility. Benefits of the RE approach include improved awareness of operational circumstances and how system elements depend on each other, and the ability to allocate limited resources and prepare for surprise. RE offers the ability to account for and incorporate the human role as an essential element in order to ensure NAS systems’ resilient performance. Data on the human contribution to safe and resilient system performance, which is termed “work as done,” are available but are not being considered as the NAS evolves. We present an approach that describes how use of RE can enable the evolving NAS to adapt, and perform, in a resilient manner.

Aviation Safety↗
NASA NTRSDate not supplied

The ARADS Project as an Astrobiological Survey Mission Prototype

An astrobiological survey prior to human arrival will be important for preservation of signs of any existing or past evidence of Martian life, to reduce the risk of unintentional forward contamination of Martian environments in which terrestrial microbes might be able to gain a foothold (e.g., [1]), and to potentially protect the health of any human crews and enable their safe return to Earth. Evaluating for the presence of life and biosignatures may become a critical-path Mars exploration precursor in the not-so-far future, circa 2030-35. The near-subsurface, with its potential combination of volatiles, vapor exchange with the surface, and shelter from surface radiation, will be a primary initial target for in-situ astrobiological investigation. Sample acquisition, drilling and sample handling are key elements of robotic missions that target the subsurface [2], as well as near-surface ground ice deposits. In the mid 2000s, the Mars Astrobiology Field Laboratory (AFL) was proposed as a follow-on mission concept to the Mars Science Laboratory (MSL)/Curiosity rover mission [3]. The AFL would have included precision drilling to 2m, automated sample handling and remote processing of cores. However, the AFL concept needed further development and maturation. The Atacama Rover Astrobiology Drilling Studies (ARADS) project concept [4] was in part AFL-inspired. The 2014 ARADS concept included a medium sized rover, with habitability instruments, including the Phoenix Wet Chemistry Laboratory (WCL) [5], and an enhanced version of the ExoMars Mars Organic Molecule Analyzer (MOMA) Laser Desorption-Linear Ion Trap Mass Spectrometer (LITMS) [6]. ARADS likewise included two biosignature detection instruments -- the Signs of Life Detector (SOLID) immunoassay instrument [7,8] and the Chemical Laptop-derived [9] Planetary In-Situ Capillary Electrophoresis System (PISCES), while mitigating Planetary Protection-relevant contamination issues [10]. ARADS project objectives were to demonstrate the potential science return for such a mission in the context of the search for evidence of life, and technically to demonstrate the feasibility of roving with drilling missions to Mars. ARADS technology goals targeted analog-site demonstrations of automated drilling and sampling, integrated with its mobile habitability and biosignature detection instruments. And ARADS science operations goals developed remote science, contamination mitigation, and communications methods to enable simulating AFL-like science operations with time delays, directed by a remote science team[11]. Five subsequent Mars analog site field demonstrations (in Chile’s hyperarid Atacama Desert, 2016-19) provided a step-by-step development pathway for the ARADS platform’s science capabilities and systems integration, culminating in an integrated remote roving mission simulation in the final ARADS year (2019).

biosignatures↗
NASA NTRS2020

UAM Vision Concept of Operations (ConOps) UAM Maturity Level (UML) 4

This Vision ConOps is intended as a foundation to engage members of the UAM community and provide a consensus on the future vision of UAM operations. It provides a concept for more detailed discussion and a basis for the exploration of ideas using a common framework to inform the continued development and integration of UAM as part of the broader transportation system. Advanced Air Mobility (AAM) encompasses a range of innovative aviation technologies (small drones, electric aircraft, automated air traffic management, etc.) that are transforming aviation’s role in everyday life, including the movement of goods and people. Urban Air Mobility (UAM) represents one of the most exciting and complex AAM concepts with highly automated aircraft, providing commercial services to the public over densely populated cities. This concept has generated tremendous interest and industry investment. UAM envisages a future in which advanced technologies and new operational procedures enable practical, cost-effective air travel as an integral mode of transportation in metropolitan areas. It represents one of the most exciting and complex AAM concepts with highly automated aircraft providing commercial services to the public over densely populated cities. For this reason, the National Aeronautics and Space Administration (NASA) selected UAM as the initial goal of its AAM efforts and the focus of this Vision Concept of Operations (ConOps) document. UAM Community Vision ConOps: This Vision ConOps effort was led by experts from NASA’s Aeronautics Research Mission Directorate (ARMD) in collaboration with the Federal Aviation Administration (FAA) and Deloitte’s Ecosystem Advisory Group (a cohort of advisers with aviation, aerospace, and regulatory expertise). To develop this Vision ConOps, NASA, FAA, and Deloitte built upon the current body of aeronautical research and consulted with more than 100 stakeholder organizations. This UAM community includes entities ranging from legacy aviation leaders to innovators and new market entrants. Stakeholders consulted included the federal government, state and local government, aerospace original equipment manufacturers (OEMs), local transportation organizations, prospective UAM operators, academia, industry standards-setting bodies, airports, service suppliers, and others (as described in Appendix G). This input was captured through the following methods: • A series of more than two dozen interviews with industry experts, federal regulators, state and local governments, and industry trade groups provided insight into the challenges of UAM integration into the National Airspace System (NAS), as well as technology developments and a variety of perspectives as to how UAM systems will integrate. • A series of two-day community workshops enabling active, detailed engagement of nearly 100 industry, academic, federal, and state stakeholder individuals. These workshops, hosted by NASA and Deloitte, explored UAM concepts in detail, and stakeholders were invited to collaboratively analyze and propose solutions to some of the greatest conceptual challenges behind UAM at an intermediate state. • A review of more than 160 sources of UAM literature from across government, industry, and academia, which are listed in Appendix H. • The public sharing of workshop input and document drafts for review and input across the UAM community. Feedback in the form of more than 1,000 comments and inputs on the document was received from industry groups, individual companies, academia, and government (federal, state, and local), among others. Although effort was made to incorporate inputs from across the UAM stakeholder group, not all comments could ultimately be incorporated in this version. The team resolved conflicting comments or ideas while maintaining consistency with the known direction of regulators and ensuring the document was coherent and consistent. It is recognized that this is a rapidly evolving area and that concepts will likely change over time; as such, this Vision ConOps is a living document and is expected to evolve as concepts mature. The ConOps does, however, provide a vision of UAM concepts and solutions based on the broad insights from across the UAM stakeholder community at the time of its publication and is intended to serve as a UAM North Star for continued research and development of UAM. As a broad Vision ConOps, is not a detailed engineering document; rather, it focuses primarily on outlining a broad, high-level vision across all aspects of a UAM transportation system.

Urban Air Mobility↗
NASA NTRS1988

Mars Rover Sample Return - Rover challenges

Mission requirements, design considerations, and scenarios are presented for the Mars Rover Sample Return mission to send rovers to Mars to collect samples for return to earth. Rover automation is examined in detail. Issues of rover design related to mobility, local navigation, and sample acquisition are discussed. Scenarios for rover operation are given, including a comparison between the level of automation of the computer-aided remote driving system and the level of the semiautonomous navigation system. It is suggested that the rover must be more automated than previous aircraft.

Allen, Lew↗
NASA NTRSDate not supplied

Urban Air Mobility (UAM) Vision Concept of Operations (ConOps) UAM Maturity Level (UML)-4 Overview

The Vision ConOps is intended as a foundation to engage members of the UAM community and provide a consensus on the future vision of UAM operations. It provides a concept for more detailed discussion and a basis for the exploration of ideas using a common framework to inform the continued development and integration of UAM as part of the broader transportation system. Advanced Air Mobility (AAM) encompasses a range of innovative aviation technologies (small drones, electric aircraft, automated air traffic management, etc.) that are transforming aviation’s role in everyday life, including the movement of goods and people. Urban Air Mobility (UAM) represents one of the most exciting and complex AAM concepts with highly automated aircraft, providing commercial services to the public over densely populated cities.

Brian Hill↗
NASA NTRSDate not supplied

Initial Performance Evaluation of Flight Path Management Onboard Automation

Significant developments in automation are necessary to achieve safe and efficient operations in advanced aerial mobility related concepts. Urban Air Mobility (UAM) is rapidly growing, emerging field that poses a challenging use case with a tighter scale of operations compared to the traditional commercial transport paradigm. A large part of the challenge is the uncharted territory; as of this paper, no set of operational standards or guidelines for UAM operations have been established and automated en route operations for UAM level 4 (UML-4) have not been studied. Flight Path Management (FPM) automation provides a set of capabilities that are critical toward enabling airborne vehicles to achieve mission success while maintaining operational safety. An initial performance evaluation of FPM automation was conducted using a UAM-adapted version of the Autonomous Operations Planner (AOP), an onboard trajectory management capability developed over years of research targeting commercial transport operations, as its reference implementation. This paper describes the evaluation, including the approach and methodology for simulating FPM automation in UML-4, key results, future work, and conclusions.

flight path management↗
NASA NTRS2000

Internet Access to Spacecraft

The Operating Missions as Nodes on the Internet (OMNI) project at NASA's Goddard Space flight Center (GSFC), is demonstrating the use of standard Internet protocols for spacecraft communication systems. This year, demonstrations of Internet access to a flying spacecraft have been performed with the UoSAT-12 spacecraft owned and operated by Surrey Satellite Technology Ltd. (SSTL). Previously, demonstrations were performed using a ground satellite simulator and NASA's Tracking and Data Relay Satellite System (TDRSS). These activities are part of NASA's Space Operations Management Office (SOMO) Technology Program, The work is focused on defining the communication architecture for future NASA missions to support both NASA's "faster, better, cheaper" concept and to enable new types of collaborative science. The use of standard Internet communication technology for spacecraft simplifies design, supports initial integration and test across an IP based network, and enables direct communication between scientists and instruments as well as between different spacecraft, The most recent demonstrations consisted of uploading an Internet Protocol (IP) software stack to the UoSAT- 12 spacecraft, simple modifications to the SSTL ground station, and a series of tests to measure performance of various Internet applications. The spacecraft was reconfigured on orbit at very low cost. The total period between concept and the first tests was only 3 months. The tests included basic network connectivity (PING), automated clock synchronization (NTP), and reliable file transfers (FTP). Future tests are planned to include additional protocols such as Mobile IP, e-mail, and virtual private networks (VPN) to enable automated, operational spacecraft communication networks. The work performed and results of the initial phase of tests are summarized in this paper. This work is funded and directed by NASA/GSFC with technical leadership by CSC in arrangement with SSTL, and Vytek Wireless.

Rash, James↗
NASA NTRSDate not supplied

Training the Powered-Lift Evaluation Pilot

This paper focuses on the preparation and training of evaluation pilots during the second of two research studies: Automation Enabled Pilot studies 1 and 2 (AEP-1 and AEP-2). These studies are intended to assess novel aircraft automation concepts for electric powered aircraft equipped with Indirect Flight Control Systems (IFCS) capable of Vertical Takeoff and Landing (eVTOL). The AEP-1 study importantly introduced the concept of future evaluation methods used in the AEP-1 study for eVTOL equipped with IFCS that are agnostic and cut cross both airworthiness and operational requirements. The AEP-2 study utilized an updated Lift Plus Cruise aircraft model and examined pilot interaction with novel procedures and interfaces. Specifically, it explored challenges related to transitioning from forward flight to landing with an industry representative Urban Air Mobility (UAM) approach procedure, establishing baselines for future automation studies.

AAM↗
NASA NTRSDate not supplied

Training the Powered-Lift Evaluation Pilot

This presentation focuses on the preparation and training of evaluation pilots during the second of two research studies: Automation Enabled Pilot studies 1 and 2 (AEP-1 and AEP-2). These studies are intended to assess novel aircraft automation concepts for electric powered aircraft equipped with Indirect Flight Control Systems (IFCS) capable of Vertical Takeoff and Landing (eVTOL). The AEP-1 study importantly introduced the concept of future evaluation methods used in the AEP-1 study for eVTOL equipped with IFCS that are agnostic and cut cross both airworthiness and operational requirements. The AEP-2 study utilized an updated Lift Plus Cruise aircraft model and examined pilot interaction with novel procedures and interfaces. Specifically, it explored challenges related to transitioning from forward flight to landing with an industry representative Urban Air Mobility (UAM) approach procedure, establishing baselines for future automation studies.

AAM↗