Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Network traffic analysis”

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.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SMAC: A soft MAC to reduce control overhead and latency in CDMA-based AMI networks

The utilization of state-of-the-art 3G cellular CDMA technologies in a utility owned AMI network results in a large amount of control traffic relative to data traffic, increases the average packet delay and hence are not an appropriate choice for smart grid distribution applications. Like the CDG, we consider a utility owned cellular like CDMA network for smart grid distribution applications and classify the distribution smart grid data as scheduled data and random data. Also, we propose SMAC protocol, which changes its mode of operation based on the type of the data being collected to reduce the data collection latency and control overhead when compared to 3G cellular CDMA2000 MAC. The reduction in the data collection latency and control overhead aids in increasing the number of smart meters served by a base station within the periodic data collection interval, which further reduces the number of base stations needed by a utility or reduces the bandwidth needed to collect data from all the smart meters. The reduction in the number of base stations and/or the reduction in the data transmission bandwidth reduces the CAPital EXpenditure (CAPEX) and OPerational EXpenditure (OPEX) of the AMI network. Finally, the proposed SMAC protocol is analyzed using markov chain, analytical expressions for average throughput and average packet delay are derived, and simulation results are also provided to verify the analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Estimation of Arrivals on Green at Signalized Intersections Using Stop-Bar Video Detection

Across the world, traffic congestion is increasing with alarming rapidity. Traffic signal control effectiveness, in coordinated networks, is often investigated in relation to the type of vehicle arrivals at the signalized intersections. Recently, several transportation agencies have switched from traditional loop detectors to video detection. When video cameras are accompanied by computer vision, one can extract more information about traffic “dynamics” than by using traditional inductive loop detectors. Collecting arrival times of multiple vehicles after the first arrival at the stop-bar detector might be challenging when using inductive loop detectors (since after the first arrival, detector status is always occupied). However, emerging video detection systems allow tracking of each vehicle’s entrance time in the detection zone, departure time from the detection zone, and the type of vehicle. This information can be used to estimate vehicular arrival and departure times, which then can be fed into machine learning algorithms to estimate arrivals on green (AOG). However, such research ideas have not been documented so far. Thus, this paper presents an estimation model for AOG, which was developed using multigene genetic programming. A robust experimental dataset was collected from a highly calibrated and validated microsimulation model of an 11-intersection corridor in Chattanooga, TN. The results of the model’s performance analysis showed the high accuracy of the training-, testing-, and validation datasets. The practical benefit of this model is that it can be applied to estimate arrival types at intersections where only stop-bar video detection exists.

Engineering↗
NASA NTRS2012

Safety Risk Knowledge Elicitation in Support of Aeronautical R and D Portfolio Management: A Case Study

Aviation is a problem domain characterized by a high level of system complexity and uncertainty. Safety risk analysis in such a domain is especially challenging given the multitude of operations and diverse stakeholders. The Federal Aviation Administration (FAA) projects that by 2025 air traffic will increase by more than 50 percent with 1.1 billion passengers a year and more than 85,000 flights every 24 hours contributing to further delays and congestion in the sky (Circelli, 2011). This increased system complexity necessitates the application of structured safety risk analysis methods to understand and eliminate where possible, reduce, and/or mitigate risk factors. The use of expert judgments for probabilistic safety analysis in such a complex domain is necessary especially when evaluating the projected impact of future technologies, capabilities, and procedures for which current operational data may be scarce. Management of an R&D product portfolio in such a dynamic domain needs a systematic process to elicit these expert judgments, process modeling results, perform sensitivity analyses, and efficiently communicate the modeling results to decision makers. In this paper a case study focusing on the application of an R&D portfolio of aeronautical products intended to mitigate aircraft Loss of Control (LOC) accidents is presented. In particular, the knowledge elicitation process with three subject matter experts who contributed to the safety risk model is emphasized. The application and refinement of a verbal-numerical scale for conditional probability elicitation in a Bayesian Belief Network (BBN) is discussed. The preliminary findings from this initial step of a three-part elicitation are important to project management practitioners as they illustrate the vital contribution of systematic knowledge elicitation in complex domains.

Shih, Ann T.↗
DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2023

EmSense: A High-Resolution Emulated Sensor for Experiments with the Smart Grid and Distributed Ledger Technology

This work involves the development of a device - EmSense (“Emulated Sensor”) - that emulates a high-resolution sensor for a power grid. The device collects raw current and voltage sensor data which derive from ORNL's signature library. This library is a dataset that ORNL curates from many different sources that include power systems from various utilities. The EmSense packages the data from the library in the form of IEC 61850 Sampled Value (SV) packets and then broadcasts these SV packets on the network. In another mode, EmSense can generate artificial sinusoidal data that appears as waveforms for voltage and current signals. EmSense has an internal algorithm for determining the period of a signal based on the data so that the period can be specified as a variable in the IEC 61850 packets. The purpose of EmSense is to allow for experimentation with the Dark Net Infrastructure where a variety of power line sensors must be represented along with their typical communication traffic. The EmSense device was developed in coordination with the software for receiving and processing the packets in the Distributed Ledger Technology (DLT) framework of the DarkNet Project. This receiving software must have a methodology for dealing with information of high velocity, variety, and volume. Experimenting with EmSense facilitates the development of such software. The results showed that the DLT framework and the trust-anchoring approach managed to process a large flow of traffic even with up to six instances of EmSense device broadcasting data. This was achieved without overfilling packet queues in the memory of the actual hardware of the DLT devices or causing the Central Processing Unit (CPU) of the hardware to be overwhelmed. The DLTs were also able to store the data in a compact and useful form for later analysis and archival purposes.

Werth, Aaron↗
NASA NTRS2020

Integration Test and Evaluation (IT&E) Flight Test Series 6 Live Virtual Constructive - Distributed Environment (LVC-DE) Test Report

The goals of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) (also UAS-NAS) Project are to reduce the barriers for UAS access and its integration into the NAS. The UAS-NAS project and industry stakeholders conducted a series of flight tests integrating technologies from the Modeling & Simulation (M&S), Human Systems Integration (HSI), and Communication and Control (C2), and Integration, Test & Evaluation (IT&E) research areas. The last of the flight test series, Flight Test Series 6 (FT6) was conducted in late 2019 and focused on evaluating the interaction of the airborne non-cooperative surveillance system and the Detect and Avoid (DAA) technology. The DAA system generated conflict alert and guidance for pilots using a Research Ground Control System (RGCS) to avoid intruder aircraft. The conflict alerting and guidance information was presented on the RGCS’s display using symbology developed by the human factors team. The objective of FT6 was to investigate the interoperability of Low Size, Weight, and Power (Low SWaP) sensors with the DAA alerting, guidance, and display requirements. To support this goal, the distributed test environments (DTE) were developed at Ames Research Center (ARC) and Armstrong Flight Research Center (AFRC) and securely linked over a Virtual Private Network (VPN). These environments took advantage of existing Live Virtual Constructive (LVC) technologies to support research observation at both Centers with the insertion of live UAS and manned intruder aircraft into a simulated NAS environment with Air Traffic Control (ATC) and constructive manned aircraft. The experiment was distributed between AFRC flight operations and research facilities and the Distributed Simulation Research Laboratory (DSRL) and Software Development Laboratory (SDL) in building N243 at ARC. The Air Traffic Controller and pseudo pilots operated from the DSRL and SDL, respectively, using the Multi-Aircraft Control System (MACS). The test subject and researchers operated from the Research Ground Control Station (RGCS) at AFRC using the Vigilant Spirit Control Station (VSCS) and associated DAA software and displays. Flight Operation for the unmanned aircraft (UA) and manned intruder traffic was conducted at AFRC. Virtual traffic was managed by ARC. Voice distribution was accomplished using a combination of disparate communication systems at ARC and AFRC. The purpose of this document is to record the development, design, and execution of activities in support of the FT6 efforts from the perspective of the ARC IT&E team. Furthermore, the Armstrong IT&E team has published a thorough FT6 Test Report, with emphasis on flight test support, facilities and vehicle development; this report complements the Armstrong report. Analysis of collected FT6 data will be conducted and reported by the M&S and HSI teams and will be published in separate reports.

UAS-NAS↗
NASA NTRS1991

NSI directed to continue SPAN's functions

During a series of network management retreats in June and July 1990, representatives from NASA Headquarters Codes O and S agreed on networking roles and responsibilities for their respective organizations. The representatives decided that NASA Science Internet (NSI) will assume management of both the Space Physics Analysis Network (SPAN) and the NASA Science Network (NSN). SPAN is now known as the NSI/DECnet, and NSN is now known as the NSI/IP. Some management functions will be distributed between Ames Research Center (ARC) and Goddard Space Flight Center (GSFC). NSI at ARC has the lead role for requirements generation and networking engineering. Advanced Applications and the Network Information Center is being developed at GSFC. GSFC will lead the NSI User Services, but NSI at Ames will continue to provide the User Services during the transition. The transition will be made as transparent as possible for the users. DECnet service will continue, but is now directly managed by NSI at Ames. NSI will continue to work closely with routing center managers at other NASA centers, and has formed a transition team to address the change in management. An NSI/DECnet working group had also been formed as a separate engineering group within NSI to plan the transition to Phase 5, DECnet's approach to Open System Integration (OSI). Transition is not expected for a year or more due to delays in produce releases. Plans to upgrade speeds in tail circuits and the backbone are underway. The proposed baseline service for new connections is up to 56 Kbps; 9.6 Kbps lines will gradually be upgraded as requirements dictate. NSI is in the process of consolidating protocol traffic, tail circuits, and the backbone. Currently NSI's backbone is fractional T1; NSI will go to full T1 service as soon as it is feasible.

Rounds, Fred↗
DOE OSTI2019

Life cycle assessment and tempo-spatial optimization of deploying dynamic wireless charging technology for electric cars

Dynamic wireless power transfer (DWPT), or dynamic wireless charging technology, enables charging-while-driving and offers opportunities for eliminating range anxiety, stimulating market penetration of electric vehicles (EVs), and enhancing the sustainability performance of electrified transportation. However, the deployment of wireless charging lanes on highways and urban road networks can be costly and resource-intensive. A life cycle assessment (LCA) is conducted here to compare the sustainability performance of DWPT applied in a network of highways and urban roads for charging electric passenger cars. The assessment compares DWPT to stationary wireless charging and to conventional plug-in charging using a case study of Washtenaw County in Michigan, USA over 20 years. The LCA is based on three key sustainability metrics: costs, greenhouse gas (GHG) emissions, and energy burdens, encompassing not only the use-phase burdens from electricity and fuel, but also the upfront deployment burdens of DWPT infrastructure. A genetic algorithm is applied to optimize the rollout of DWPT infrastructure both spatially and temporally in order to minimize life cycle costs, GHG, and energy burdens: (1) spatial optimization selects road segments to deploy DWPT considering traffic volume, speed, and pavement remaining service life (RSL); (2) temporal optimization determines in which year to deploy DWPT on a particular road segment considering EV market share growth as a function of DWPT coverage rate, future DWPT cost reduction, and charging efficiency improvement. Results indicate that optimal deployment of DWPT electrifying up to about 3% of total roadway lane-miles reduces life cycle GHG emissions and energy by up to 9.0% and 6.8%, respectively, and enables downsizing of the EV battery capacity by up to 48%, compared to the non-DWPT scenarios. Roadside solar panels and storage batteries are essential to significantly reduce life cycle energy and GHG burdens but bring additional costs. Breakeven analysis indicates a breakeven year for solar charging benefits to pay back the DWPT infrastructure burdens can be less than 20 years for GHG and energy burdens but longer than 20 years for costs. A monetization of carbon emissions of at least $250 per metric tonne of CO 2 is required to shift the optimal “pro-cost” deployment to the optimal “pro-GHG” deployment. A roadway segment with volume greater than about 26,000 vehicle counts per day, speed slower than 55 miles per hour (1 mile ≈ 1.609 km), and pavement RSL shorter than 3 years should be given a high priority for early-stage DWPT deployment.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1992

Guaranteeing synchronous message deadlines with the timed token medium access control protocol

We study the problem of guaranteeing synchronous message deadlines in token ring networks where the timed token medium access control protocol is employed. Synchronous capacity, defined as the maximum time for which a node can transmit its synchronous messages every time it receives the token, is a key parameter in the control of synchronous message transmission. To ensure the transmission of synchronous messages before their deadlines, synchronous capacities must be properly allocated to individual nodes. We address the issue of appropriate allocation of the synchronous capacities. Several synchronous capacity allocation schemes are analyzed in terms of their ability to satisfy deadline constraints of synchronous messages. We show that an inappropriate allocation of the synchronous capacities could cause message deadlines to be missed even if the synchronous traffic is extremely low. We propose a scheme called the normalized proportional allocation scheme which can guarantee the synchronous message deadlines for synchronous traffic of up to 33 percent of available utilization. To date, no other synchronous capacity allocation scheme has been reported to achieve such substantial performance. Another major contribution of this paper is an extension to the previous work on the bounded token rotation time. We prove that the time elapsed between any consecutive visits to a particular node is bounded by upsilon TTRT, where TTRT is the target token rotation time set up at system initialization time. The previous result by Johnson and Sevcik is a special case where upsilon = 2. We use this result in the analysis of various synchronous allocation schemes. It can also be applied in other similar studies.

Agrawal, Gopal↗
NASA NTRS1983

Requirements for a mobile communications satellite system. Volume 1: Executive summary

Three types of satellite-aided mobile communications are considered for users in areas not served by (terrestrial) cellular radio systems. In System 1, mobile units are provided a direct satellite link to a gateway station, which serves as the interface to the terrestrial toll network. In System 2, a terrestrial radio link similar to those in cellular systems connects the mobile unit to a translator station; each translator relays the traffic from mobile units in its vicinity, via satellite, to the regional gateway. It is not feasible for System 2 to provide ubiquitous coverage. Therefore, System 3 is introduced, in which the small percentage of users not within range of a translator are provided a direct satellite link as in System 1. While System 2 can operate with leased satellite capacity, Systems 1 and 3 require a dedicated satellite. A major portion of this study is concerned with the design of a satellite for System 1. A weight limit of 10,000 lbs, corresponding to the projected 1990 STS capability, is imposed on the design. Frequency re-use of the allocated spectrum, through multiple satellite beams, is employed to generate the specified system capacity. Both offset-fed and center-fed reflectors are considered. For an assumed 10-MHz allocation and a population of 350,000 subscribers, a two-satellite system is required. The reflector diameters corresponding to offset-fed and center-fed geometries are 46 m and 62 m, respectively. Thus, large-space-structure technology is inherent to the implementation of System 1. In addition to establishing the technical requirements for the three types of satellite systems, the monthly service charge needed to provide a specified return on invested capital is computed. A net present value analysis is used for this purpose.

Source record↗
DOE OSTI2021

Using bursty announcements for detecting BGP routing anomalies

Despite the robust structure of the Internet, it is still susceptible to disruptive routing updates that prevent network traffic from reaching its destination. Our research shows that BGP announcements that are associated with disruptive updates tend to occur in groups of relatively high frequency, followed by periods of infrequent activity. We hypothesize that we may use these bursty characteristics to detect anomalous routing incidents. In this work, we use manually verified ground truth metadata and volume of announcements as a baseline measure, and propose a burstiness measure that detects prior anomalous incidents with high recall and better precision than the volume baseline. We quantify the burstiness of inter-arrival times around the date and times of four large-scale incidents: the Indosat hijacking event in April 2014, the Telecom Malaysia leak in June 2015, the Bharti Airtel Ltd. hijack in November 2015, and the MainOne leak in November 2018; and three smaller scale incidents that led to traffic interception: the Belarusian traffic direction in February 2013, the Icelandic traffic direction in July 2013, and the Russian telecom that hijacked financial services in April 2017. Our method leverages the burstiness of disruptive update messages to detect these incidents. We describe limitations, open challenges, and how this method can be used for routing anomaly detection.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Barriers and Benefits: Understanding Riders’ Views on Pooled Rideshare in the U.S.

This manuscript provides actionable recommendations to enhance user satisfaction and address existing barriers regarding pooled rideshare (PR) in the United States. Despite PR’s intended benefits, such as reduced traffic congestion and cost savings, its adoption remains limited. To identify these actionable items, a U.S. nationwide survey with 5385 participants explored transportation preferences, barriers, and motivators for PR use in the summer of 2021. First, two factor analyses were conducted. The first factor analysis identified the five factors associated with one’s willingness to consider PR (time/cost, traffic/environment, safety, privacy, and service experience). The second factor analysis revealed the four factors related to ways to optimize one’s PR experience (comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety). Privacy concerns, for instance, were found to reduce the likelihood of PR adoption by 77%, and convenience had the potential to increase it by 156%. A structural equation model evaluated the relationships among these nine key factors influencing PR usage to develop the Pooled Rideshare Acceptance Model (PRAM). The privacy, safety, trust service, and convenience factors each had a significant large effect (Cohen’s f 2 > 0.35) on the model. PRAM was extended using multigroup analyses to reveal the nuanced impact of 16 demographics, including gender, generation, rideshare experience, etc., highlighting the need for tailored strategies to improve PR acceptance through the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs). Multiple workshops were held with diverse audiences to translate the team’s findings to date into 84 actionable recommendations, categorized across topical areas like safety, routing, driver and passenger selection, user education, etc. These findings are a foundation for a future study to determine which items resonate with different user groups. In the meantime, the actional items serve as a user-driven resource for policymakers, transportation network companies, and researchers, offering a roadmap to potential improvements to PR services to address existing concerns with the goal of increasing the usage of PR.

actionable recommendations↗
DOE OSTI2019

CONSTRUCTING A NETWORK FUNDAMENTAL DIAGRAM: A SYNTHETIC ORIGIN-DESTINATION APPROACH

The Network Fundamental Diagram (NFD) is increasingly used in traffic monitoring and control. One obstacle to a wider application of NFDs in network control is the difficulty of obtaining data from all vehicles traveling in the network to construct an accurate NFD. One solution is to estimate the NFD using data from only a fraction of vehicles (i.e., probe vehicles), where the probe vehicle market penetration rate (MPR) needs to be estimated. A previous study conducted by the authors demonstrated that a distance or time weighted harmonic mean was needed to estimate the flow- and density-based MPRs, respectively using a pairing k-mean clustering approach. This paper proposes another approach that utilizes probe vehicle and observed link volume data to estimate the MPR. A heuristic model is proposed to identify the optimum locations from which to collect link traffic volume data for use in the MPR estimation. The estimated MPR can then be used to construct the NFD. Results show that these models can accurately estimate the NFD with limited probe vehicle and link traffic volume data. Accordingly, the models can be used in the field to estimate the NFD using readily available loop detector and probe vehicle data. The ideal locations for traffic volume data collection can also be proactively chosen to generate optimum estimation results. Since the models proposed here show no significant gains with an increased magnitude of collected data after a certain threshold, they will be helpful, particularly when large-scale data collection is not affordable or realistic.

Spatial Analysis, Market Penetration Rate, NFD, Sy↗
DOE OSTI2017

Impact of Trucking Network Flow on Preferred Biorefinery Locations in the Southern United States

The impact of the trucking transportation network flow was modeled for the southern United States. The study addresses a gap in existing research by applying a Bayesian logistic regression and Geographic Information System (GIS) geospatial analysis to predict biorefinery site locations. A one-way trucking cost assuming a 128.8 km (80-mile) haul distance was estimated by the Biomass Site Assessment model. The “median family income,” “timberland annual growth-to-removal ratio,” and “transportation delays” were significant in determining mill location. Transportation delays that directly impacted the costs of trucking are presented. Here, a logistic model with Bayesian inference was used to identify preferred site locations, and locations not preferential for a mill location. The model predicted that higher probability locations for smaller biomass mills (feedstock capacity, the size of sawmills) were in southern Alabama, southern Georgia, southeast Mississippi, southern Virginia, western Louisiana, western Arkansas, and eastern Texas. The higher probability locations for large capacity mills (feedstock capacity, the size for pulp and paper mills) were in southeastern Alabama, southern Georgia, central North Carolina, and the Mississippi Delta regions.

09 BIOMASS FUELS↗
DOE OSTI2019

Constructing a Network Fundamental Diagram: Synthetic Origin–Destination Approach

The Network Fundamental Diagram (NFD) is significantly used in traffic monitoring and control. One obstacle to a wider application of NFDs in network control is the difficulty of obtaining data from all vehicles traveling in the network to construct an accurate NFD. One solution is to estimate the NFD using data from only a fraction of vehicles (i.e., probe vehicles), where the probe vehicle market penetration rate (MPR) needs to be estimated. A previous study conducted by the authors demonstrated that a distance or time weighted harmonic mean was needed to estimate the flow- and density-based MPRs, respectively using a pairing k-mean clustering approach. This paper introduces another approach that utilizes probe vehicle and observed link volume data to estimate the MPR. A heuristic model is proposed to identify the optimum locations from which to collect link traffic volume data for use in the MPR estimation. The estimated MPR can then be used to construct the NFD. Results show that these models can accurately estimate the NFD with limited probe vehicle and link traffic volume data. Accordingly, the models can be used in the field to estimate the NFD using readily available loop detector and probe vehicle data. The ideal locations for traffic volume data collection can also be proactively chosen to generate optimum estimation results. Since the models proposed here show no significant gains with an increased magnitude of collected data after a certain threshold, they will be helpful, particularly when large-scale data collection is not affordable or realistic.

42 ENGINEERING↗
DOE OSTI2025

Understanding and Modeling Pooled Rideshare Acceptance: Influential Factors, Preferred User Experiences, and Implications

Ridesharing allows people to share a vehicle with others traveling in the same direction, which can reduce costs and traffic congestion. Pooled rideshare (PR) services, such as UberX Share and Lyft Shared, offer an economical and environmentally friendly alternative by matching passengers traveling similar routes. However, despite these benefits, PR adoption remains low due to concerns about safety, privacy, and convenience. This research explores the factors influencing PR adoption and provides recommendations to improve user acceptance. A nationwide survey of 5,385 participants across the U.S. was conducted to understand why people choose or avoid PR. The study identified five key factors influencing PR consideration: safety, service experience, privacy, traffic/environment, and time/cost. Additional research examined ways to optimize PR experiences by identifying four critical factors: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. To measure the impact of these factors, a statistical model called the Pooled Rideshare Acceptance Model (PRAM) was developed, providing insights into how each element influences PR adoption. Further analysis using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) revealed how demographic characteristics such as age, gender, income, and past rideshare experience shape PR perceptions. Some key findings from the multigroup analyses showed that younger users valued technological features and environmental benefits, while older users prioritized reliability and service transparency. Additionally, privacy concerns were more significant for female users, while convenience was critical for higher-income groups. These results emphasize that a 'onesize-fits-all' approach to PR service design is not effective, highlighting the need for tailored strategies to address different user segments. Further, workshops were conducted with researchers and students to translate the findings into real-world solutions. These workshops and 3 all the statistical analyses led to the development of 95 actionable recommendations. The recommendations focus on key areas such as safety, service reliability, user education, and accessibility, offering tangible improvements to PR services. The insights from this study provide valuable guidance for policymakers, transportation network companies (TNCs), and researchers aiming to make PR services safer, more accessible, and widely accepted. By addressing user concerns, PR can become a more viable transportation option, supporting sustainable urban mobility and reducing reliance on private vehicles. Additionally, these findings emphasize the importance of user-centric service design in encouraging broader PR adoption. Future research should explore evolving trends in PR preferences, technological advancements, and policy changes to ensure continued improvements. By implementing these recommendations, PR services can better align with user expectations, enhance trust in shared mobility, and contribute to a more efficient transportation ecosystem.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Unlocking the Mysteries of the Moon’s Shadowed Regions

The Moon poles host large quantities of water-ice deposits in the permanently shadowed regions (PSRs), which are vital for enabling sustainable human space exploration, making these regions high-priority targets for upcoming Artemis missions [1]. Unfortunately, today, the best available orbital lunar imagery [2, 3] lacks the meter-scale resolution and signal needed to understand the geomorphology and trafficability of PSRs, complicating the planning and execution of future missions seeking to explore PSRs. We have developed an image enhancement tool called HORUS (Hyper-effective nOise Removal Unet Software) [4, 5], designed to enhance LRO Narrow-Angle Camera (NAC) optical low-light imagery of permanently shadowed regions by effectively removing the CCD-related, photon, and other residual noises that corrupt the images. The tool is composed of two deep learning neural networks trained on environmental metadata and real and synthetic imagery, the latter generated by a physical noise model (LROC). We demonstrated that HORUS effectively produces low-noise, high-resolution images (~1.5m/px), achieving a 5 to 10x improvement over existing long-exposure images of PSRs. HORUS allows scientists and engineers to identify geomorphic features (e.g., craters and boulders) in shadowed regions as small as 3 meters across as well as to peek inside of small shadowed regions, for the first time. The tool was deployed and thoroughly validated for NASA's VIPER mission [6], where it was applied to 20 candidate target regions across the lunar South Pole. Additionally, we conducted different approaches to validate the resulting HORUS-processed images. With HORUS denoised images, VIPER scientists can increase their confidence on what surface features (previously unseen) exist in the shadowed regions, helping them plan rover traverses more safely and efficiently (e.g., Fig. 1) In this manuscript, we will describe how VIPER scientists are utilizing HORUS denoised images to extract new information from the terrain and increase their confidence in what surface features exist in the shadowed regions. In combination with other high-resolution images and digital elevation maps, HORUS images are helping the team analyze potential lading and science sites, as well as planning traverses more safely and efficiently (e.g., Fig. 1). Additionally, we will describe how HORUS tool unlocks a broad range of scientific and exploration applications to other Artemis and CPLS missions to the lunar poles, including (but not limited to) geomorphic analysis, change detection, surface hazard detection, and terrain relative navigation.

artificial intelligence↗