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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗

NASA NTRS1997

Alternative Perspectives on Risk

The goal of the commercial air transport system is to provide air transportation to the flying public at an acceptable cost with minimal risk. in an ideal situation these three goals would support each other. In fact, it is sometimes the case that the goals conflict: getting passengers to their destinations on time may conflict with fixing a minor mechanical malfunction that may or may not impact safety; flying a route that will avoid turbulence, thereby providing passengers with a more comfortable ride, may consume more fuel; managing traffic density may mean aircraft are delayed or must use an approach that will result in a long taxi to their gates, costing time and fuel. Various players in the system--pilots, dispatchers, controllers, as well as managers in the airline carriers and traffic management system--make decisions every day that involve trade-offs of benefits and costs. The prospect of revisions in the air traffic management system, with shifts in responsibilities from controllers to users, including airline operations center personnel and pilots, means that individuals may be performing either new jobs or old jobs under new guidance. It will be essential to know how the various players (a) perceive the risks and benefits associated with the decisions they will make under the old and new control structures, and (b) how much risk they are willing to accept in making decisions. Risk is here defined as the probability and magnitude of negative events (after Slovic, 1987). Of primary interest are risks associated with traffic, weather, and operational factors such as schedule, fuel consumption, and passenger service. Previous research has documented differences between groups in perceptions of risks associated with both everyday and aviation related situations. Risk perception varies as a function of familiarity with the situation, degree to which one is potentially affected by the risk, the level of control one has over the situation, and one's level of experience and responsibility in the situation. In our presentation we will consider several factors that may influence differences in risk perception, risk tolerance and risk management among the three major categories of participants in the aviation system (pilots, dispatchers, and controllers). Primary factors that may affect risk attitudes (the collective term we will use for the three components of risk) include: expertise or job-specific knowledge or training, personal involvement or vulnerability to consequences, goals, time horizon (imminence of consequences), span of control and type of control, and information or technology support. These will be considered in the context of five different types of risk (physical threat, economic, social, legal, and ethical). A study designed to study differences between pilots and controllers in their perceptions and responses to traffic risks under the present and a user-preferred control situation will be described. Future studies involving dispatchers' risk perceptions regarding various types of risk will be discussed.

Davison, Jeannie↗

DOE OSTI2021

Cyber Physical Grid-Interactive Distributed Energy Resources Control for VPP Dispatch and Regulation: Preprint

This paper presents a cyber-physical algorithm for grid interactive DER control to enable two features of Virtual Power Plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. We first formulate the DER dispatch problem as a real-time, iterative, and grid-interactive DER control problem. Thereafter, we consider a probabilistic traffic model to characterize packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control center that coordinately execute this dispatch algorithm. Finally, we propose a cyber-physical grid-interactive DER control algorithm using the previous message strategy. The tracking and regulation capabilities of this proposed algorithm can be made immune to the asynchrony resulting from the communications network traffic. We carry out simulations to show possible numerical instabilities and sensitivities of the tracking and regulation capabilities on the proposed strategy. Our results exhibit that the uncertainties of the underlying communications infrastructure must be considered in the control algorithm for the VPP tracking and regulation capabilities of any DER in a generic Cyber-Physical System (CPS).

co-simulation↗

DOE OSTI2021

Formation and reconfiguration of tight multi-lane platoons

Advances in vehicular communication technologies are expected to facilitate cooperative driving in the future. Connected and Automated Vehicles (CAVs) are able to collaboratively plan and execute driving maneuvers by sharing their perceptual knowledge and future plans. In this paper, an architecture for autonomous navigation of tight multi-lane platoons traveling on public roads is presented. Using the proposed approach, CAVs are able to form single or multi-lane platoons of various geometrical configurations. They are able to reshape and adjust their configurations according to changes in the environment. The proposed architecture consists of two main components: an offline motion planner system and an online hierarchical control system. The motion planner uses an optimization-based approach for cooperative formation and reconfiguration in tight spaces. A constrained optimization scheme is used to plan smooth, dynamically feasible and collision-free trajectories for all the vehicles within the platoon. The paper addresses online computation limitations by employing a family of maneuvers precomputed offline and stored on a look-up table on the vehicles. The online hierarchical control system is composed of three levels: a traffic operation system (TOS), a decision-maker, and a path-follower. The TOS determines the desired platoon reconfiguration. The decision-maker checks the feasibility of the reconfiguration plan based on real-time information about the surrounding traffic. The reconfiguration maneuver is executed by a low-level path-following feedback controller in real-time. The effectiveness of the approach is demonstrated through simulations of three case studies: (1) formation reconfiguration (2) obstacle avoidance, and (3) benchmarking against behavior-based planning in which the desired formation is achieved using a sequence of motion primitives.

42 ENGINEERING↗

DOE OSTI2025

Descriptor: Infrastructure Perception and Control: Multi-Sensor Object Tracking Dataset (IPC-MSOT)

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. Traffic accidents often occur at traffic intersections, including a large proportion of traffic fatalities and about one-half of all traffic injuries in the United States. Object detection data were collected in 2024 across three intersections in Colorado Springs, CO, USA, over the course of multiple days and various times to induce a heterogeneous mix of traffic conditions and behaviors. The purpose of the data collection exercises was to learn various attributes about infrastructure sensors and to build a repository of high-resolution, object-level data that can be used for research and development (e.g., to develop multisensor data fusion algorithms). The Infrastructure Perception and Control:Multi-Sensor Object tracking (IPC-MSOT) dataset was collected as part of the U.S. Department of Transportation's Strengthening Mobility and Revolutionizing Transportation (SMART) project, where the city of Colorado Springs, Colorado, and the National Renewable Energy Laboratory collaborated to collect object-level trajectory data from road users using multiple types of infrastructure sensors deployed at different intersections. This dataset allows for testing of late-stage sensor fusion algorithms and their ability to ingest multimodal sensor data, and it can be utilized by traffic engineers to design and evaluate trajectory-based signal control strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

SDN Project

The SDN Project completed on time and on budget and successfully accomplished 100% of the scope of work outlined in the original Statement of Project Objective (SOPO). The SDN Project formed an alliance between Ameren Corporation, University of Illinois Urbana- Champaign (UIUC), Pacific Northwest National Laboratories (PNNL), and Schweitzer Engineering Laboratories, Inc. (SEL). The objective of the SDN Project is to address Topic Area of Interest 2: Sustain critical energy delivery functions while responding to a cyber-intrusion under Funding Opportunity Announcement DE-FOA-0000797. The goal of the project is to design and commercially release technology that provides a method to sustain critical energy delivery functions during a cyber intrusion and to do this control system operators need the ability to quickly identify and isolate the affected network areas, and re-route critical information and control flows around. The objective of the SDN Project is to develop a Flow Controller that monitors, configures, and maintains the safe, reliable network traffic flows of all the local area networks (LANs) on a control system in the Energy sector. The SDN team identified the core attributes of a control system and produced an SDN flow controller that has the same core attributes enabling networks to be designed, configured and deployed that maximize the whitelisted, deny-bydefault and purpose built networks. This project researched, developed and commercially released technology that: Enables all field networks be to configured and monitored as if they are a single asset to be protected; Enables greatly improved and even precalculated response actions to reliability and cyber events; Supports pre-configured localized response actions tailored to provide resilience against failures and centralized response to cyber-attacks that improve network reliability and availability; Architecturally enables the right subject matter experts, who are usually the information technology and operational technology engineers, to be the ones centrally administering the technology and responding to events; Simplifies network configuration, improving deterministic Ethernet transport times, and providing instant visualization on where the communication circuits are and how all circuits are impacted when changes (e.g., configuration changes, failures or intrusions) happen, allowing operators to minimize downtime; and Improves the ability to identify deviations in network behavior resulting in detection and analysis of potential cyber intrusions and faster response times Results: This project has forever changed the way critical infrastructure networks are designed, secured, deployed and maintained. The cybersecurity and performance advantages achieved are significant, simply put traditional networking has been obsoleted while the team maintained Ethernet interoperability avoiding any legacy concerns. The team commercially released technology that accomplished all the cybersecurity goals outlined in the SOPO and completed it by executing the project management plan approved in the initial contract. The resulting Energy sector SDN flow controller model number is SEL-5056 and can be freely downloaded from the www.SELinc.com website. This technology not only improves the cybersecurity of control systems but has measured results that it improves the performance and reliability of the control system as well. This means the system owners can confidently apply it to their systems knowing that it will, “first do no harm” but actually improve the system as well. Success of the project is best measured by the sales and deployment of the technology. System owners in industrial, electric, defense, and oil and gas only months after commercial release have approved plans for deployment.

42 ENGINEERING↗

DOE OSTI2020

Impact of Lateral Alignment on the Energy Savings of a Truck Platoon

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the sensitivity of intentional lateral offsets over a range of intervehicle spacings. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb. In addition, the SAE J1939 instantaneous fuel rate was calibrated against the gravimetric measurements and used as proxy for additional analyses. The testing campaign demonstrated the effects of intervehicle gaps, following-vehicle longitudinal control, and manual lateral control. The new results are compared to previous truck-platooning studies to reinforce the value of the new information and demonstrate similarity to past trends. Fuel savings for the following vehicle was observed to exceed 10% at closer following distances. The results showed that energy savings generally increased in a non-linear fashion as the gap was reduced. The impact of different following-truck lateral offsets had a measurable impact, with up to 4% reduction in total fuel-savings (relative to an isolated vehicle condition) observed for offsets up to 1.3 m. The fuel-consumption savings on the straight segments of the track exceeded those on the curved segments by upwards of 6% and highlight some potential differences expected between close-track testing and on-highway use.

adaptive cruise control↗

DOE OSTI2020

Impact of Lateral Alignment on the Energy Savings of a Truck Platoon: Preprint

adaptive cruise control↗

DOE OSTI2021

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular attention to accurate energy values for strongly unsteady driving profiles; and sparse Lagrangian controls via automated vehicles, with a focus on controls that can be executed via existing technology such as adaptive cruise control systems. This framework serves as a key building block in developing control strategies for human-in-the-loop traffic flow smoothing on real highways. In this contribution, we outline the fundamental merits of integrating vehicle dynamics and energy modeling into a single framework, and we demonstrate the energy impact of sparse flow smoothing controllers via simulation results.

Lee, Jonathan W.↗

NASA NTRS2019

Models of Terminal Arrival Efficiency Rate

Terminal Arrival Efficiency Rate (TAER) is a measure of TRACON performance and the impact of Traffic Management Initiatives (TMI) within 100 miles of the airport. This measures not just the approach control performance, but also ARTCC performance to deliver traffic evenly. Identifying conditions that lead to low TAER can allow development of method to improve it. In this study, we developed linear and decision tree models of TAER.

Air Traffic Management↗

DOE OSTI2021

CPS Testbed Architectures for WAMPAC using Industrial Substation and Control Center Platforms and Attack-Defense Evaluation

Advanced persistent threats and cyberattacks can impact wide-area monitoring, protection, and control (WAMPAC) system operation. Many cyber-physical system (CPS) testbeds have been developed for attack-defense experimentation and attack-resiliency tools evaluation for WAMPAC, but they are limited to a simulation-and-emulation based environment. This paper presents a quasi-realistic CPS attack-defense testbed-based framework for WAMPAC applications using the industrial substation and control center platforms such as eTerra integrated with the hardware-in-the-loop CPS smart grid testbed available at Iowa State University. The proposed framework includes various combinations of industry-grade substation and control center platforms, communication topologies, real-time digital simulators, and a novel cyber-physical distributed intrusion-and-anomaly detection system (D-IADS) for WAMPAC applications. The D-IADS includes a master at the control center and geographically distributed sensor devices at each substation. Each D-IADS sensor deployed at a substation or control center network monitors ingress and egress traffic, detect intrusions, and dispatch alerts to the D-IADS master. The D-IADS master centrally monitors and analyze the alerts and controls D-IADS sensors. We considered an EMP60 synthetic CPS grid as a case study to demonstrate the framework and proposed D-IADS for WAMPAC applications against cyberattack vectors such as Man-in-the-Middle DNP3 attack, denial-of-service, and data-integrity attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Reachability Analysis for FollowerStopper: Safety Analysis and Experimental Results

Motivated by earlier work and the developer of a new algorithm, the FollowerStopper, this article uses reachability analysis to verify the safety of the FollowerStopper algorithm, which is a controller designed for dampening stop-and-go traffic waves. With more than 1100 miles of driving data collected by our physical platform, we validate our analysis results by comparing it to human driving behaviors. The FollowerStopper controller has been demonstrated to dampen stop-and-go traffic waves at low speed, but previous analysis on its relative safety has been limited to upper and lower bounds of acceleration. To expand upon previous analysis, reachability analysis is used to investigate the safety at the speeds it was originally tested and also at higher speeds. Two formulations of safety analysis with different criteria are shown: distance-based and time headway-based. The FollowerStopper is considered safe with distance-based criterion. However, simulation results demonstrate that the FollowerStopper is not representative of human drivers - it follows too closely behind vehicles, specifically at a distance human would deem as unsafe. On the other hand, under the time headway-based safety analysis, the FollowerStopper is not considered safe anymore. A modified FollowerStopper is proposed to satisfy time-based safety criterion. Simulation results of the proposed FollowerStopper shows that its response represents human driver behavior better.

Chou, Fang-Chieh↗

NASA NTRS2012

Flying Schedule-Matching Descents to Explore Flight Crews' Perceptions of Their Load and Task Feasibility

Multiple studies have investigated the development and use of ground-based (controller) tools to manage and schedule traffic in future terminal airspace. No studies have investigated the impacts that such tools (and concepts) could have on the flight-deck. To begin to redress the balance, an exploratory study investigated the procedures and actions of ten Boeing-747-400 crews as they flew eight continuous descent approaches in the Los Angeles terminal airspace, with the descents being controlled using speed alone. Although the study was exploratory in nature, four variables were manipulated: speed changes, route constraints, clearance phraseology, and winds. Despite flying the same scenarios with the same events and timing, there was at least a 50 second difference in the time it took crews to fly the approaches. This variation is the product of a number of factors but highlights potential difficulties for scheduling tools that would have to accommodate this amount of natural variation in descent times. The primary focus of this paper is the potential impact of ground scheduling tools on the flight crews performance and procedures. Crews reported "moderate to low" workload, on average; however, short periods of intense and high workload were observed. The non-flying pilot often reported a higher level of workload than the flying-pilot, which may be due to their increased interaction with the Flight Management Computer, when using the aircraft automation to assist with managing the descent clearances. It is concluded that ground-side tools and automation may have a larger impact on the current-day flight-deck than was assumed and that studies investigating this impact should continue in parallel with controller support tool development.

Martin, Lynne Hazel↗

NASA NTRS1999

Voice loops as coordination aids in space shuttle mission control

Voice loops, an auditory groupware technology, are essential coordination support tools for experienced practitioners in domains such as air traffic management, aircraft carrier operations and space shuttle mission control. They support synchronous communication on multiple channels among groups of people who are spatially distributed. In this paper, we suggest reasons for why the voice loop system is a successful medium for supporting coordination in space shuttle mission control based on over 130 hours of direct observation. Voice loops allow practitioners to listen in on relevant communications without disrupting their own activities or the activities of others. In addition, the voice loop system is structured around the mission control organization, and therefore directly supports the demands of the domain. By understanding how voice loops meet the particular demands of the mission control environment, insight can be gained for the design of groupware tools to support cooperative activity in other event-driven domains.

STS Shuttle Project↗

NASA NTRSDate not supplied

Developing a Cybersecurity Architecture for Extensible Traffic Management (xTM)

This paper explores the development of a cybersecurity architecture tailored for Extensible Traffic Management (xTM) to address emerging challenges in managing diverse aerial vehicles within the National Airspace System (NAS). Driven by technological advances and the rise of uncrewed aerial systems (UAS), urban air mobility (UAM), and high-altitude traffic (ETM), the NAS is undergoing a paradigm shift. Traditional air traffic management, reliant on traditional Federal Aviation Administration (FAA) control, will give way to decentralized coordination among autonomous and semi-autonomous systems. The proposed xTM Security Architecture, designed as a high-level framework, focuses on ensuring the confidentiality, integrity, and availability of data and operations in this evolving ecosystem. Utilizing threat modeling, the research identifies potential risks across key flight phases, operations and use cases to offer security control recommendations. Key objectives include analyzing interactions between novel airspace entrants and existing NAS traffic, cataloging vulnerabilities, and developing mitigative strategies to ensure safety, operational stability, and secure data exchanges. This research lays the groundwork for regulatory and industry adaptation, providing critical insights into managing cybersecurity risks in this complex, multi-domain environment.

UAM↗

DOE OSTI2022

Medium-scale to large-scale implementation of cyber-physical human experiments in live traffic

Autonomous Vehicles (AVs) such as cars and trucks are being developed and tested as Cyber-Physical Human systems while the technology improves. Before these systems can achieve full autonomy, some serve as tools in the form of adaptive cruise control. The CIRCLES Consortium investigates the potential for AVs to increase fuel efficiency of highway traffic by smoothing “stop-and-go” traffic waves that result from normal human driving behavior in congestion. We have performed an experiment to evaluate the real world effects of implementing this strategy. A medium-scale experiment was performed on I-24 near Nashville, TN in August 2021. This was a precursor to a larger experiment that will take place November 2022. We examine how the human part of the experiment will change as we scale up from an 11 vehicle test (four AVs) to 100 AVs. There are many solutions to problems of the medium-scale experiment that would be inconvenient, complicate the experience, or not be practicable. The medium-scale experiment involved 11 cars of which four had a custom control algorithm installed to be engaged by the driver. The large-scale experiment will have 100 cars, all with custom control algorithm installed to act on traffic when the controller is engaged. We examine key choices made for the medium experiment, and how some will be different for the large experiment. Our experience performing the medium-scale experiment has made it clear that repeating our methods from this smaller one are inefficient or impossible if used for the large-scale experiment and will be improved.

McQuade, Sean T.↗

NASA NTRS2017

Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

Traffic flow management seeks to balance the demand for National Airspace System (NAS) flight resources, such as airspace and airports, with the available supply. When forecasted weather blocks nominal air traffic routes, traffic managers must re-route affected flights for weather avoidance. Depending on the nature and scope of the weather, traffic managers may use pre-coordinated re-routes such as Playbook Routes or Coded Departure Routes, or may design ad hoc local re-routes. The routes of affected flights are modified accordingly. These weather avoidance routes will, of course, be less efficient than the nominal routes due to increased flight time and fuel burn. In current traffic management operations, the transition into a weather avoidance re-routing initiative is typically implemented more aggressively than the transition out of that initiative after the weather has dissipated or moved away. For example, strategic large-scale Playbook re-routes are sometimes left in place (as initially implemented) for many hours before being lifted entirely when the weather dissipates. There is an opportunity to periodically modify the re-routing plan as weather evolves, thereby attenuating its adverse impact on flight time and fuel consumption; this is called delay recovery. Multi-Flight Common Routes (MFCR) is a NASA-developed operational concept and associated decision support tool for delay recovery, designed to assist traffic managers to efficiently update weather avoidance traffic routes after the original re-routes have become stale due to subsequent evolution of the convective weather system. MFCR groups multiple flights to reduce the number of advisories that the traffic manager needs to evaluate, and also merges these flights on a common route segment to provide an orderly flow of re-routed traffic. The advisory is presented to the appropriate traffic manager who evaluates it and has the option to modify it using MFCRs graphical user interface. If the traffic manager finds the advisory to be operationally appropriate, he or she would coordinate with the Area Supervisor(s) of the sectors that currently control the flights in the advisory. When the traffic manager accepts the MFCR advisory via the user interface, the corresponding flight plan amendments would be sent to the displays of the appropriate sector controllers, using the Airborne Re-Routing (ABRR) capability which is scheduled for nationwide operation in 2017. The sector controllers would then offer this time-saving route modification to the pilots of the affected flights via datalink (or voice), and implement the corresponding flight plan amendment if the pilots accept it. MFCR is implemented as an application in the software environment of the Future Air traffic management Concepts Evaluation Tool (FACET). This paper focuses on an initial subject matter expert (SME) evaluation of MFCR. The evaluation covers MFCRs operational concept, algorithm, and user interface.

Human-in-the-loop Evaluation↗