Results for “connected automated vehicles” — Page 8

DOE OSTI2021

Human-automated vehicle interactions

This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.

Guo, Longxiang↗

DOE OSTI2021

HUMAN-AUTOMATED VEHICLE INTERACTIONS

This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.

Guo, Longxiang↗

DOE OSTI2023

Deliver Signal Phase and Timing (SPAT) for Energy Optimization of Vehicle Cohort Via Cloud-Computing and LTE Communications

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques. An emulation-based algorithm is applied to predict the traffic signal state changes to provide adequate prediction horizon (e.g., at minimum 2 minutes) for the cohort energy optimization. In fact, the same connectivity and SPAT delivery methodology has been applied to traffic signalized intersections nationwide in the United States upon public agency approvals for access to their firewalled traffic control network and signal control systems or directly to individual controllers. This methodology proves its effectiveness and potential for rapid growth of such SPAT deliveries at mass production scale without needing infrastructure hardware retrofit or excessive communication means. To support the energy optimization of light and heavy-duty vehicle cohorts of mixed automation and propulsion systems (EV, ICE and hybrid), the connection and SPAT deliveries at two sites were completed, including public roads in Washtenaw County, Michigan and closed track test sites at American Center for Mobility (ACM) in Ypsilanti, Michigan. However, only closed test track results at ACM will be presented in this paper. A neuroevolution based optimizer is developed and implemented to control the speed of a vehicle cohort with different propulsion systems and automation levels. Closed track tests showed significant energy savings of the cohort operation.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2020

New Flight Rules to Enable the Era of Aerial Mobility in the National Airspace System

In the 21st Century, new aviation markets, vehicle types, and technologies are fast emerging, inspiring new operational concepts for the National Airspace System such as Unmanned Aircraft Systems Traffic Management and Urban Air Mobility. These novel operations envision a dramatic increase in aerial mobility, or the ability to navigate freely through the airspace with unprecedented access and operational flexibility. Implementing these concepts presents a major challenge to the existing operational modes of Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), developed under the limitations of early 20th Century technology and procedures to ensure safe navigation and separation from traffic. To meet this challenge and to support the needs of operators in the 21st Century and beyond, this paper proposes that VFR and IFR be augmented by new flight rules – Digital Flight Rules (DFR) – that leverage modern and emerging technologies and are not bound by restrictions borne of the state of technology 75-100 years ago. The objective of DFR is to provide safe and unfettered access to the airspace to all participating vehicle operators under all visibility conditions without incurring the limitations in operational flexibility inherent to IFR and even VFR. Advancements in communications, navigation, surveillance, aircraft connectivity, information access, automation technology, and supporting ground infrastructure provide the opportunity for the vehicle operator to engage at an unprecedented level in managing their flights regardless of flight visibility. Under DFR, these advancements enable the vehicle operator to assume full responsibility for traffic separation and therefore full trajectory management authority in all visibility conditions and airspace regions. The changes in roles and responsibilities are expected to enable greater airspace access and operational flexibility than afforded by IFR and VFR, thus enabling the emergence of new operations and a new era of advanced aerial mobility.

Mobility↗

NASA NTRSDate not supplied

Digital Flight: Enabling the Era of Scalable Mobility in the National Airspace System

In the 21st Century, new aviation markets, vehicle types, and technologies are fast emerging, inspiring new operational concepts for the National Airspace System such as Unmanned Aircraft Systems Traffic Management and Urban Air Mobility. These novel operations envision a dramatic increase in aerial mobility, or the ability to navigate freely through the airspace with unprecedented access and operational flexibility. Implementing these concepts presents a major challenge to the existing operational modes of Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), developed under the limitations of early 20th Century technology and procedures to ensure safe navigation and separation from traffic. To meet this challenge and to support the needs of operators in the 21st Century and beyond, this paper proposes that VFR and IFR be augmented by new flight rules – Digital Flight Rules (DFR) – that leverage modern and emerging technologies and are not bound by restrictions borne of the state of technology 75-100 years ago. The objective of DFR is to provide safe and unfettered access to the airspace to all participating vehicle operators under all visibility conditions without incurring the limitations in operational flexibility inherent to IFR and even VFR. Advancements in communications, navigation, surveillance, aircraft connectivity, information access, automation technology, and supporting ground infrastructure provide the opportunity for the vehicle operator to engage at an unprecedented level in managing their flights regardless of flight visibility. Under DFR, these advancements enable the vehicle operator to assume full responsibility for traffic separation and therefore full trajectory management authority in all visibility conditions and airspace regions. The changes in roles and responsibilities are expected to enable greater airspace access and operational flexibility than afforded by IFR and VFR, thus enabling the emergence of new operations and a new era of advanced aerial mobility.

Mobility↗

NASA NTRS2019

A New Market for Terrestrial Single-Event Effects: Autonomous Vehicles

ISO-26262, the road vehicle functional safety standard, underwent a major overhaul that was released in December 2018. Radiation effects, and single-event effect (SEE) hazards in particular, play an important role in autonomous vehicle safety. This connection will only increase as the level of driving automation goes from "hands off," to "eyes off," to "mind off." This translates to increased coupling with space climate and weather in addition to other traditional terrestrial radiation sources like thorium and uranium contamination in process and packaging materials. We will focus on autonomous vehicle radiation effects and present both benefits and challenges to the space weather and radiation engineering communities.

Autonomous Vehicles↗

DOE OSTI2026

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Real-Time Dynamic Brake Assessment for Heavy Commercial Vehicle Safety

This paper summarizes initial results and findings of a model developed to determine the braking performance of commercial motor vehicles in motion regardless of brake type or gross weight. Real-world data collected by Oak Ridge National Laboratory for a U.S. Department of Energy study was used to validate the model. Expanding on previous proof-of-concept research showing the linear relationship of brake application pressure and deceleration additional parameters such as elevation were added to the model. Outputs from the model consist of coefficients calculated for every constant pressure braking event from a vehicle that can be used to calculate a deceleration and thus compute a stopping distance for a given scenario. Using brake application pressure profiles derived from the dataset, stopping distances for light and heavy loads of the same vehicle were compared for various speed and road grades. For a constant brake application pressure profile (i.e. the pressure is relatively constant throughout the entire stop) it was shown that the lighter vehicle was able to stop in a shorter distance than the heavier vehicle in most scenarios other than large uphill grades. Significant changes in weight can be observed through the fuel efficiency of the vehicle to determine if the model needs to be calibrated with new or additional braking events. The model was initially developed for tracking brake performance to inform routine maintenance and the ordering of vehicles in a platoon but can be expanded to other connected and automated research areas.

Siekmann, Adam↗

DOE OSTI2021

Safe Operations at Roadway Junctions - Design Principles from Automated Guideway Transit

Herein this paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone "interlocking" at each junction location deconflicts railway traffic, affirming safe passage. The analogous AV protection safety subsystem is defined as fail-safe equipment that monitors roadway intersections and junctions, communicates traffic signal status, perceives and communicates alerts and signals to AV connected vehicles concerning potential unsafe conditions, and performs related primary safety functions. Conclusions are drawn that the AV protection roadway intersection functions must be performed by local roadside equipment dedicated to protecting each roadway intersection and junction. Further, it is concluded that the communications technology connecting the infrastructure with the vehicle to perform this vital, fail-safe protection should meet specific functional and performance criteria.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1992

Automated Power-Distribution System

Autonomous power-distribution system includes power-control equipment and automation equipment. System automatically schedules connection of power to loads and reconfigures itself when it detects fault. Potential terrestrial applications include optimization of consumption of power in homes, power supplies for autonomous land vehicles and vessels, and power supplies for automated industrial processes.

Ashworth, Barry↗

DOE OSTI2024

Analysis of Automated Transit Network Systems with Battery-Electric Vehicles in Automated Mobility Districts: Preprint

The paper provides an overview of the insights and findings of the National Renewable Energy Laboratory's (NREL) ongoing research on the implementation of automated mobility districts (AMDs). AMD is a term coined by NREL to describe a geographically defined district or major activity center located in a dense urban setting with mobility applications provided by automated/autonomous vehicle (AV) systems spanning internal circulation and first-mile/last-mile connections to regional transportation hubs. Research over the past five years has focused on understanding the evolution of AMDs, beginning with demonstrations of automated shuttles prior to the pandemic, to more integrated on-demand mobility systems currently in initial stages of deployment. Initial insights and findings from earlier studies include the need for designation of a "jurisdiction having authority," a clear vision of a complete system to provide end-to-end mobility services, and the requisite intelligent infrastructure to complement AV technology. NREL's most recent Phase III research investigates station boarding/alighting (curb) issues, the full electrification of fleets, and the need for a systems engineering methodology (SEM) to properly analyze the complexities resulting from the convergence of automation, on-demand mobility, and electrification of the transit systems within the AMD. The paper reviews the findings of AMD research conducted during Phase I, II, and III, with special emphasis on Phase III results with respect to a descriptive example of the proposed SEM when a "digital twin" analytical model is used to simulate the transport fleet's battery-electric vehicle miles of travel and associated duty cycles through a rigorous analytical assessment with a comprehensive modeling process.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Multihorizon Model Predictive Control: An Application to Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles

Not provided.

Automation & Control Systems↗

DOE OSTI2025

Vehicle Automation Benefits and Challenges for Passenger Transport System Beyond Automated Driving

The National Renewable Energy Laboratory has been researching the implementation of fully automated passenger transport systems to be operated within dense urban settings, referred to as Automated Mobility Districts, based on roadway vehicle automation as opposed to track or train-based automation. This research, now in its third phase, is presently addressing the full spectrum of benefits and challenges of full automation of passenger transport systems with respect to fleet electrification and the associated multimodal, large fleet operational management, benefits beyond simply automating the driving tasks. The focal points summarized in the paper and presentation address the benefit-analysis of fleet automation to address added complexities imposed on the multi-fleet operational management when there is a simultaneous implementation of an on-demand service mode that connects with and optimizes the effectiveness of legacy transit systems and new sub-regional autonomous vehicle fleets, with specific emphasis on enhanced ability to better meet peak ridership demand. The research also begins to address challenges in operations arising from lack of personnel present to handle unexpected customer and system needs. Combined, this research articulates vehicle automation benefits and challenges beyond simply automating the driving tasks, addressing additional operational benefits automation provides to address the added complexities imposed by electrification and on-demand modes of operation.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2013

A System for Fault Management for NASA's Deep Space Habitat

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy.

Fault management↗

NASA NTRS2013

A System for Fault Management and Fault Consequences Analysis for NASA's Deep Space Habitat

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy

System Effects Analysis↗

DOE OSTI2023

Heavy-Duty Vehicle Air Drag Coefficient Estimation: From an Algebraic Perspective

When a heavy-duty vehicle (HDV) operates at the nominal highway speed, over two-thirds of its total resistive force comes from the air drag, contributing to more than half of its fuel consumption. One effective countermeasure to reduce the fuel consumption of HDVs is platooning, which employs connectivity and automated driving technologies to link two or more HDVs in convoy. Platooning allows HDVs to drive closer together and yields improved fuel economy and less CO2 emission thanks to the reduced air drag. Maximizing the energy benefits of an HDV platoon requires quantifying the drag interaction between vehicles. In practice, modeling the drag reduction in a platoon boils down to identifying the relationship between the air drag coefficient C d and the inter-vehicle distance d. Existing approaches to identify C d (d) include vehicle field tests, wind tunnel experiments, and computational fluid dynamics simulation, which can howbeit be time-consuming and cost prohibitive. In contrast, this paper proposes an algebraic approach, which relies on onboard-measurable variables, to estimate the air drag coefficient of an HDV in a platoon. Its algebraic nature avoids the classical persistence of excitation condition for parameter identification and can yield the identified parameter almost instantaneously. Simulation results demonstrate its effectiveness and the improved estimation speed over a recursive least squares identifier.

Wang, Zejiang↗

NASA NTRS2020

Designing and Training for Appropriate Trust in Increasingly Autonomous Advanced Air Mobility Operations: A Mental Model Approach: Version 1

To enable effective human-autonomy teaming (HAT) in Advanced Air Mobility (AAM) operations, the current paper presents a theoretical framework to design and train for appropriate trust in automation. The novel contribution of this work resides in connecting the construct of trust to mental models and showing how this method could be used to enable emerging HAT concepts such as Adaptive Trust Calibration. To contextualize this framework, in section 2 we discuss simplified vehicle operations (SVO) and remote vehicle operations (RVO), which are leading operational concepts within AAM. In section 3 we describe our perspective on automation and increasingly autonomous systems and present a brief discussion on human-automation interaction and human-autonomy teaming. In section 4 we provide a detailed discussion on the construct of trust in automation. In section 5 we present a framework that associates mental models with trust through principles of transparent design. Finally, in section 6 we present three descriptive models for designing and training for appropriate trust in increasingly autonomous systems.

Human-Autonomy Teaming↗

NASA NTRS1993

Development and evaluation of a profile negotiation process for integrating aircraft and air traffic control automation

The development and evaluation of the profile negotiation process (PNP), an interactive process between an aircraft and air traffic control (ATC) that integrates airborne and ground-based automation capabilities to determine conflict-free trajectories that are as close to an aircraft's preference as possible, are described. The PNP was evaluated in a real-time simulation experiment conducted jointly by NASA's Ames and Langley Research Centers. The Ames Center/TRACON Automation System (CTAS) was used to support the ATC environment, and the Langley Transport Systems Research Vehicle (TSRV) piloted cab was used to simulate a 4D Flight Management System (FMS) capable aircraft. Both systems were connected in real time by way of voice and data lines; digital datalink communications capability was developed and evaluated as a means of supporting the air/ground exchange of trajectory data. The controllers were able to consistently and effectively negotiate nominally conflict-free vertical profiles with the 4D-equipped aircraft. The actual profiles flown were substantially closer to the aircraft's preference than would have been possible without the PNP. However, there was a strong consensus among the pilots and controllers that the level of automation of the PNP should be increased to make the process more transparent. The experiment demonstrated the importance of an aircraft's ability to accurately execute a negotiated profile as well as the need for digital datalink to support advanced air/ground data communications. The concept of trajectory space is proposed as a comprehensive approach for coupling the processes of trajectory planning and tracking to allow maximum pilot discretion in meeting ATC constraints.

Green, Steven M.↗