AV Technology Changes/Traps - Need for Standards presentation.
Abstract not provided.
Fischer, Robert A.↗
SEARCH · Search NASA
Results for “AV”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Energy and the New Mobility - How Disruptive (to Energy) will AVs be?
Explore the source record for details and available documents.
Atkinson, Chris↗
"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↗
Ecosystem Controls on Methylmercury Production by Periphyton Biofilms in a Contaminated Stream: Implications for Predictive Modeling
Periphyton biofilms produce a substantial fraction of the overall monomethylmercury (MMHg) flux in East Fork Poplar Creek, an industrially contaminated, freshwater creek in Oak Ridge, Tennessee. We examined periphyton MMHg production across seasons, locations, and light conditions using mercury stable isotopes. Methylation and demethylation rate potentials (km, trans av and kd, trans av, respectively) were calculated using a transient availability kinetic model. Light exposure and season were significant predictors of km, trans av, with greater values in full light exposure and in the summer. Season, light exposure, and location were significant predictors of kd, trans av, which was highest in dark conditions, in the spring, and at the upstream location. Light exposure was the controlling factor for net MMHg production, with positive production for periphyton grown under full light exposure and net demethylation for periphyton grown in the dark. Ambient MMHg and km, trans av were significantly correlated. Transient availability rate potentials were 15 times higher for km and 9 times higher for kd compared to full availability rate potentials (km, full av and kd, full av) calculated at 1 d. No significant model for the prediction of km, full av or kd, full av could be constructed using light, season, and location. In addition, there were no significant differences among treatments for the full availability km, full av, kd, full av, or net MMHg calculated using the full availability rate potentials. km, full av was not correlated with ambient MMHg concentrations. The present results underscore the importance of applying transient availability kinetics to MMHg production data when estimating MMHg production potential and flux.
Schwartz, Grace E.↗
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↗
SU-D-17A-04: The Impact of Audiovisual Biofeedback On Image Quality During 4D Functional and Anatomic Imaging: Results of a Prospective Clinical Trial
Purpose: The ability of audiovisual (AV) biofeedback to improve breathing regularity has not previously been investigated for functional imaging studies. The purpose of this study was to investigate the impact of AV biofeedback on 4D-PET and 4D-CT image quality in a prospective clinical trial. We hypothesized that motion blurring in 4D-PET images and the number of artifacts in 4D-CT images are reduced using AV biofeedback. Methods: AV biofeedback is a real-time, interactive and personalized system designed to help a patient self-regulate his/her breathing using a patient-specific representative waveform and musical guides. In an IRB-approved prospective clinical trial, 4D-PET and 4D-CT images of 10 lung cancer patients were acquired with AV biofeedback (AV) and free breathing (FB). The 4D-PET images in 6 respiratory bins were analyzed for motion blurring by: (1) decrease of GTVPET and (2) increase of SUVmax in 4-DPET compared to 3D-PET. The 4D-CT images were analyzed for artifacts by: (1) comparing normalized cross correlation-based scores (NCCS); and (2) quantifying a visual assessment score (VAS). A two-tailed paired t-test was used to test the hypotheses. Results: The impact of AV biofeedback on 4D-PET and 4D-CT images varied widely between patients, suggesting inconsistent patient comprehension and capability. Overall, the 4D-PET decrease of GTVPET was 2.0±3.0cm3 with AV and 2.3±3.9cm{sup 3} for FB (p=0.61). The 4D-PET increase of SUVmax was 1.6±1.0 with AV and 1.1±0.8 with FB (p=0.002). The 4D-CT NCCS were 0.65±0.27 with AV and 0.60±0.32 for FB (p=0.32). The 4D-CT VAS was 0.0±2.7 (p=ns). Conclusion: A 10-patient study demonstrated a statistically significant reduction of motion blurring of AV over FB for 1/2 functional 4D-PET imaging metrics. No difference between AV and FB was found for 2 anatomic 4D-CT imaging metrics. Future studies will focus on optimizing the human-computer interface and including patient training sessions for improved comprehension and capability. Supported by NIH/NCI R01 CA 093626, Stanford BioX Interdisciplinary Initiatives Program, NHMRC Australia Fellowship, and Kwanjeong Educational Foundation. GE Healthcare provided the Respiratory Gating Toolbox for 4D-PET image reconstruction. Stanford University owns US patent #E7955270 which is unlicensed to any commercial entity.
60 APPLIED LIFE SCIENCES↗
User Acceptance of Shared Autonomous Vehicles
A dissertation is proposed to explore user acceptance of shared autonomous vehicles (SAVs). SAVs are facing limited user acceptance. To systematically tackle the user acceptance barriers of SAVs, the main problem can be disintegrated into two sub-problems of user acceptance of autonomous vehicles (AVs) and ridesharing. The comfort of the ride experience in AVs is a determinant of user acceptance. Understanding the influential factors and developing methodologies to quantify human comfort in AVs are essential to facilitating future research to improve human comfort in AVs. The current pooled rideshare (PR) service closely resembles the anticipated future of SAVs. Understanding why users prefer or refuse to use PR at the current stage prepares SAVs for broader acceptance in the future. Until now, a series of peer-reviewed publications have been published to achieve the technical goals. Two simulator-based user studies were conducted to instrument the research on human comfort in AVs. Statistical analysis was performed to identify the crucial vehicular behavioral factors of human comfort in AVs. The influential factors of human comfort in AVs and methodologies to quantify and detect human comfort in AVs were investigated. Two survey-based studies were deployed to facilitate the investigation of user acceptance of rideshare services. The influential factors of users' willingness to consider PR were explored and identified, and the choice behaviors in ridesharing services were comprehensively modeled and analyzed. The proposed research answers a series of fundamental questions regarding the user acceptance of SAVs. For the branch of user acceptance of AVs, the research generated guidelines for improving passenger comfort in AVs by identifying a series of autonomous driving factors of passenger comfort. The research also provides fundamental tools to estimate human comfort levels for future research and in-AV applications. For the branch of user acceptance of PR, the research provided user acceptance-aware vehicle, service, and policy design insights that can promote the usage of PR.
Su, Haotian↗
Audiovisual Biofeedback Improves Cine–Magnetic Resonance Imaging Measured Lung Tumor Motion Consistency
Purpose: To assess the impact of an audiovisual (AV) biofeedback on intra- and interfraction tumor motion for lung cancer patients. Methods and Materials: Lung tumor motion was investigated in 9 lung cancer patients who underwent a breathing training session with AV biofeedback before 2 3T magnetic resonance imaging (MRI) sessions. The breathing training session was performed to allow patients to become familiar with AV biofeedback, which uses a guiding wave customized for each patient according to a reference breathing pattern. In the first MRI session (pretreatment), 2-dimensional cine-MR images with (1) free breathing (FB) and (2) AV biofeedback were obtained, and the second MRI session was repeated within 3-6 weeks (mid-treatment). Lung tumors were directly measured from cine-MR images using an auto-segmentation technique; the centroid and outlier motions of the lung tumors were measured from the segmented tumors. Free breathing and AV biofeedback were compared using several metrics: intra- and interfraction tumor motion consistency in displacement and period, and the outlier motion ratio. Results: Compared with FB, AV biofeedback improved intrafraction tumor motion consistency by 34% in displacement (P=.019) and by 73% in period (P<.001). Compared with FB, AV biofeedback improved interfraction tumor motion consistency by 42% in displacement (P<.046) and by 74% in period (P=.005). Compared with FB, AV biofeedback reduced the outlier motion ratio by 21% (P<.001). Conclusions: These results demonstrated that AV biofeedback significantly improved intra- and interfraction lung tumor motion consistency for lung cancer patients. These results demonstrate that AV biofeedback can facilitate consistent tumor motion, which is advantageous toward achieving more accurate medical imaging and radiation therapy procedures.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Advantages of Intraprocedural Unenhanced CT During Adrenal Venous Sampling to Confirm Accurate Catheterization of the Right Adrenal Vein
Purpose: To evaluate the advantages of intraprocedural CT during adrenal venous sampling (AVS) to confirm accurate catheterization of the right adrenal vein (RAV). Materials and Methods: This single-institution study included 106 patients (mean age 52.4 years; range 28–74 years) with primary aldosteronism who performed contrast-enhanced CT (CECT) before AVS following AVS between January 2011 and March 2018. After catheterization of the RAV under fluoroscopic guidance, unenhanced CT images were obtained to confirm catheter position on unified CT angiography system. Catheter repositioning was performed when the catheter was inaccurately positioned. Venography findings were classified into two groups: (1) presumably cannulated in the RAV (presumed RAV group) and (2) obscured visualization of the RAV because of collateral vessels (obscured RAV group). Success rates of AVS were compared using Fisher’s exact test. Results: The overall success of AVS was achieved in 104 patients (98.1%). Catheter was deviated into the IVC during intraprocedural CT in four patients. Fourteen patients (14.0%) required catheter repositioning by intraprocedural CT images, and accurate catheterization in the RAV was eventually accomplished. The success rate of AVS was significantly higher in the presumed RAV group (90.1% [73/81]) than that in the obscured RAV group (68.4% [13/19]) (p = 0.024). If intraprocedural CT was not acquired during AVS, the success rate of AVS would have been significantly lower (84.9% [90/106]) compared with that use of intraprocedural CT (98.1% [104/106]) (p < 0.001). Conclusions: Intraprocedural unenhanced CT by referring to the preprocedural CECT before AVS enables the confirmation of accurate catheterization of the RAV. Level of Evidence: Level 4, case series.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Automated Lane Centering: An Off-the-Shelf Computer Vision Product vs. Infrastructure-Based Chip-Enabled Raised Pavement Markers
Safe autonomous vehicle (AV) operations depend on an accurate perception of the driving environment, which necessitates the use of a variety of sensors. Computational algorithms must then process all of this sensor data, which typically results in a high on-vehicle computational load. For example, existing lane markings are designed for human drivers, can fade over time, and can be contradictory in construction zones, which require specialized sensing and computational processing in an AV. But, this standard process can be avoided if the lane information is simply transmitted directly to the AV. High definition maps and road side units (RSUs) can be used for direct data transmission to the AV, but can be prohibitively expensive to establish and maintain. Additionally, to ensure robust and safe AV operations, more redundancy is beneficial. A cost-effective and passive solution is essential to address this need effectively. In this research, we propose a new infrastructure information source (IIS), chip-enabled raised pavement markers (CERPMs), which provide environmental data to the AV while also decreasing the AV compute load and the associated increase in vehicle energy use. CERPMs are installed in place of traditional ubiquitous raised pavement markers along road lane lines to transmit geospatial information along with the speed limit using long range wide area network (LoRaWAN) protocol directly to nearby vehicles. This information is then compared to the Mobileye commercial off-the-shelf traditional system that uses computer vision processing of lane markings. Our perception subsystem processes the raw data from both CEPRMs and Mobileye to generate a viable path required for a lane centering (LC) application. To evaluate the detection performance of both systems, we consider three test routes with varying conditions. Our results show that the Mobileye system failed to detect lane markings when the road curvature exceeded ±0.016 m -1 . For the steep curvature test scenario, it could only detect lane markings on both sides of the road for just 6.7% of the given test route. On the other hand, the CERPMs transmit the programmed geospatial information to the perception subsystem on the vehicle to generate a reference trajectory required for vehicle control. The CERPMs successfully generated the reference trajectory for vehicle control in all test scenarios. Moreover, the CERPMs can be detected up to 340 m from the vehicle’s position. Our overall conclusion is that CERPM technology is viable and that it has the potential to address the operational robustness and energy efficiency concerns plaguing the current generation of AVs.
33 ADVANCED PROPULSION SYSTEMS↗
Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamics scheme
Lagrangian methods to solve the inviscid Euler equations produce numerical oscillations near shock waves. A common approach to reducing these oscillations is to add artificial viscosity (AV) to the discrete equations. The AV term acts as a dissipative mechanism that attenuates oscillations by smearing the shock across a finite number of computational cells. However, AV introduces several control parameters that are not determined by the underlying physical model, and hence, in practice are tuned to the characteristics of a given problem. We seek to improve the standard quadratic-linear AV form by replacing it with a learned neural function that reduces oscillations relative to exact solutions of the Euler equations, resulting in a hybrid numerical-neural hydrodynamic solver. Because AV is an artificial construct that exists solely to improve the numerical properties of a hydrodynamic code, there is no offline ‘viscosity data’ against which a neural network can be trained before inserting into a numerical simulation, thus requiring online training. We achieve this via differentiable programming, i.e. end-to-end backpropagation or adjoint solution through both the neural and differential equation code, using automatic differentiation of the hybrid code in the Julia programming language to calculate the necessary loss function gradients. A novel offline pre-training step accelerates training by initializing the neural network to the default numerical AV scheme, which can be learned rapidly by space-filling sampling over the AV input space. We find that online training over early time steps of simulation is sufficient to learn a neural AV function that reduces numerical oscillations in long-term hydrodynamic shock simulations. These results offer an early proof-of-principle that online differentiable training of hybrid numerical schemes with novel neural network components can improve certain performance aspects existing in purely numerical schemes.
97 MATHEMATICS AND COMPUTING↗
Automated Vehicle Feasibility Study
This study collected automated vehicle (AV) performance data on public roadways in Athens, Ohio. The route for the study contained a combination of roads with different functional classifications, conditions, annual average daily traffic, and ownership responsibilities for maintenance and repair. Preparation for the public road deployment was done in a controlled environment at Transportation Research Center’s SMARTCenter, a dedicated AV test facility in East Liberty, Ohio. Researchers analyzed data and extracted insights relevant for both AV developers and infrastructure owners and operators. The study found that rural environments offer a unique set of roadway features such as hills and curves, which can challenge the driving behavior of an AV. Rural regions can also contain a large number of low-traffic gravel roads that lack pavement markings, which appear to be a crucial infrastructure element for operation of current generation AVs. Similarly, the presence of well-maintained lane lines along curves can influence the AV’s roadway departure tendencies. The study found that curvature-related behavior of an AV is also influenced by driving speed on the roadway segment. Such findings were consistent regardless of the time of day along the route or season of data collection. However, commentary about AV performance in active adverse weather cannot be made, as this is still an area of active research.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Energy Implications of Current Travel and the Adoption of Automated Vehicles
Current travel patterns and energy usage could be dramatically disrupted by new vehicle technologies, specifically in the case of automated vehicle (AV) technology. AV development is rapidly progressing and some experts anticipate it will be widely available to the public within 10 to 30 years (Litman and Litman 2018; Bansal and Kockelman 2017). This transformation in transportation could have a significant impact on the way people travel and potentially on overall energy consumption. AV adoption could have a wide range of potential energy implications, depending on their usage and the efficiency of the AVs. To better understand these implications, a random survey of more than 1,000 adults living in the continental United States was conducted for the National Renewable Energy Laboratory (NREL) using the Opinion Research Corporation (ORC) survey methodology (See A.1). While other survey efforts at the time of the study broadly investigated the barriers to acceptance of AVs, this study uniquely investigated how the technology will affect driving and commuting habits. The results were analyzed to better understand which groups of people will likely adopt AV technology first, how respondents currently travel, and how respondents may change their travel patterns if AVs are widely adopted.
33 ADVANCED PROPULSION SYSTEMS↗
How do perceptions of safety and car ownership importance affect autonomous vehicle adoption?
In this study, we explicitly modeled how individuals' perceptions of automated vehicle (AV) safety and the importance they place on car ownership affect mode choices involving conventional and automated vehicles in the context of privately owned cars and ridehailing services. We adopted psychometric questions to capture these two latent variables and designed a stated preference survey based on the participants' actual travel patterns. Then, we quantified the impact of these latent variables on mode choices using an integrated choice and latent variable (ICLV) model. We found that both latent variables have a statistically significant effect on mode choices. The results show that car ownership importance has the most potent effect on privately owned cars (conventional car and self-driving car), followed by driverless ridehailing and conventional ridehailing. We also found that changes in safety perception are equivalent to sizable changes in price. In addition, we further investigated the impact of improvements in safety perception through four scenarios. The scenario testing results show that as the distribution of perceived safety is compressed toward positive safety perception, the market share of AVs spikes and dominates regular cars. Our results demonstrate that based on our respondents' current understanding of AVs, even if AV prices were comparable to regular cars, we cannot expect widespread use of AVs. However, improvements in AVs' safety and, consequently, consumer safety perception can considerably expand AVs' market share, and may offset the high cost of using the technology.
33 ADVANCED PROPULSION SYSTEMS↗
Economic Incentives for Agrivoltaics Systems with Commodity Crops in the Midwestern United States
Declining costs of photovoltaic (PV) technology and rising market and policy incentives are leading to the growing deployment of PV on cropland in the US Midwest, leading to concerns about the displacement of food and feed crop production. Agrivoltaic (AV) technology enables the dual use of land by co-locating PV energy and crop production, potentially reducing land-use competition with crop production. We develop a benefit-cost analysis framework to compare the net economic returns from AV to those with stand-alone PV and crop production on a representative field and show conditions under which AV can be more profitable for both a solar developer and a farmer. We integrate it with a crop and solar energy model to simulate the performance of various field designs and space and height configurations in AV systems to accommodate soybean production with conventional farm equipment under representative conditions in the US Midwest. We find that an AV system with soybean production is less profitable than PV alone for a solar developer due to the high capital costs of raising panel height, and less profitable for a farmer than leasing land for PV due to its adverse effects of shading on crop yield. We discuss the changes in technology and market prices of solar energy and soybeans that are necessary to make the AV system profitable for solar developers and farmers. We show that AV can worsen rather than mitigate the conflict between food crops and solar energy production in the Midwest.
14 SOLAR ENERGY↗
Exploratory Investigation of Disengagements and Crashes in Autonomous Vehicles Under Mixed Traffic: An Endogenous Switching Regime Framework
Autonomous Vehicles (AVs) have a large potential to improve traffic safety but also pose some critical challenges. While AVs may help reduce crashes caused by human error, they still may experience failures of technologies and sensing, as well as decision-making errors in a mixed traffic environment. A disengagement refers to an AV transitioning control from autonomous systems to the trained test driver. The safety critical nature of disengagements makes it imperative to analyze disengagements and crashes together. In this study, we analyze both crashes and disengagements from real-world AV driving in California to fill the knowledge gap regarding the relationship between disengagements and crashes in a mixed traffic environment. A nested logit model was calibrated using three different outcomes: (1) disengagement with a crash, (2) disengagement with no crash, and (3) no disengagement with a crash. Furthermore, endogenous switching regime models were also calibrated to draw distinctions between the relation of disengagements and crashes while accounting for endogeneity effects. The results show that factors related to AV systems (such as software failures) and other roadway participants increase the propensity of a disengagement without a crash. Furthermore, AVs were observed to disengage less often as the technology matured over time. Marginal effects revealed an 8% decrease. The results thus suggest that disengagements are a part of AVs' safe performance and disengagement alerts may need to be triggered in order to avoid certain failures with current technology.
42 ENGINEERING↗
SU-E-J-29: Audiovisual Biofeedback Improves Tumor Motion Consistency for Lung Cancer Patients
Purpose: To investigate whether the breathing-guidance system: audiovisual (AV) biofeedback improves tumor motion consistency for lung cancer patients. This will minimize respiratory-induced tumor motion variations across cancer imaging and radiotherapy procedues. This is the first study to investigate the impact of respiratory guidance on tumor motion. Methods: Tumor motion consistency was investigated with five lung cancer patients (age: 55 to 64), who underwent a training session to get familiarized with AV biofeedback, followed by two MRI sessions across different dates (pre and mid treatment). During the training session in a CT room, two patient specific breathing patterns were obtained before (Breathing-Pattern-1) and after (Breathing-Pattern-2) training with AV biofeedback. In each MRI session, four MRI scans were performed to obtain 2D coronal and sagittal image datasets in free breathing (FB), and with AV biofeedback utilizing Breathing-Pattern-2. Image pixel values of 2D images after the normalization of 2D images per dataset and Gaussian filter per image were used to extract tumor motion using image pixel values. The tumor motion consistency of the superior-inferior (SI) direction was evaluated in terms of an average tumor motion range and period. Results: Audiovisual biofeedback improved tumor motion consistency by 60% (p value = 0.019) from 1.0±0.6 mm (FB) to 0.4±0.4 mm (AV) in SI motion range, and by 86% (p value < 0.001) from 0.7±0.6 s (FB) to 0.1±0.2 s (AV) in period. Conclusion: This study demonstrated that audiovisual biofeedback improves both breathing pattern and tumor motion consistency for lung cancer patients. These results suggest that AV biofeedback has the potential for facilitating reproducible tumor motion towards achieving more accurate medical imaging and radiation therapy procedures.
60 APPLIED LIFE SCIENCES↗