Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “traffic impact 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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Analysis of the Capacity Potential of Current Day and Novel Configurations for New York's John F. Kennedy Airport

In 2015, a series of systems analysis studies were conducted on John F. Kennedy Airport in New York (NY) in a collaborative effort between NASA and the Port Authority of New York and New Jersey (PANYNJ). This work was performed to build a deeper understanding of NY airspace and operations to determine the improvements possible through operational changes with tools currently available, and where new technology is required for additional improvement. The analysis was conducted using tool-based mathematical analyses, video inspection and evaluation using recorded arrival/departure/surface traffic captured by the Aerobahn tool (used by Kennedy Airport for surface metering), and aural data archives available publically through the web to inform the video segments. A discussion of impacts of trajectory and operational choices on capacity is presented, including runway configuration and usage (parallel, converging, crossing, shared, independent, staggered), arrival and departure route characteristics (fix sharing, merges, splits), and how compression of traffic is staged. The authorization in March of 2015 for New York to use reduced spacing under the Federal Aviation Administration (FAA) Wake Turbulence Recategorization (RECAT) also offers significant capacity benefit for New York airports when fully transitioned to the new spacing requirements, and the impact of these changes for New York is discussed. Arrival and departure capacity results are presented for each of the current day Kennedy Airport configurations. While the tools allow many variations of user-selected conditions, the analysis for these studies used arrival-priority, no-winds, additional safety buffer of 5% to the required minimum spacing, and a mix of traffic typical for Kennedy. Two additional "novel" configurations were evaluated. These configurations are of interest to Port Authority and to their airline customers, and are believed to offer near-term capacity benefit with minimal operational and equipage changes. One of these is the addition of an Optimized Profile Descent (OPD) route to runways 22L and 22R, and the other is the simultaneous use of 4 runways, which is not currently done at Kennedy. The background and configuration for each of these is described, and the capacity results are presented along with a discussion of drawbacks and enablers for each.

Glaab, Patricia↗
DOE OSTI2025

Investigating the Impact of Temporal and Directional Traffic Distribution on Crash Frequencies

Safety Performance Functions (SPFs) are mathematical models that establish relationships between the frequency of various crash types and site-specific characteristics, serving as essential tools for traffic safety analysis and roadway design. Traditional SPFs, however, often overlook the temporal fluctuations in traffic flow (such as peak-hour surges) and directional imbalances between opposing traffic streams. These traffic patterns can exacerbate congestion, disrupt driver behavior, and create unexpected conflict points, potentially leading to increased crash frequencies and more severe accidents. In light of this gap, this study aims to explore the potential of incorporating K-factors (representing peak-hour traffic proportions) and D-factors (reflecting the imbalance of directional traffic) into the development of SPFs to assess whether these factors can effectively represent the impact of temporal and spatial traffic distribution on roadway safety. Using crash data from Pennsylvania urban-suburban collector roadways, it is found that the D-factor plays a significant role in predicting the frequency of total crashes, fatal + injury crashes, and angle crashes, with positive coefficient signs indicating that higher directional imbalances correspond to increased crash risks. Similarly, the K-factor emerges as a critical predictor for fatal + injury crashes and rear-end crashes, with negative coefficients suggesting that a more pronounced traffic peak is associated with a reduction in expected crash frequencies. These results highlight the importance of accounting for uneven traffic distribution in both time and direction when developing SPFs, offering deeper insights into crash patterns and supporting more effective safety interventions and roadway designs.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗
NASA NTRS2015

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

wavelet analysis↗
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗
DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗
NASA NTRS1986

Application of intersatellite links to domestic satellite systems

The results of a study on intersatellite link (ISL) applications for domestic satellite communications are presented. It was determined if any technical, economic, or performance benefits could be gained by introducing intersatellite links into a domestic satellite communication network. Several key systems issues of domestic ISL's are addressed. These include the effect of a skewed traffic distribution on the selection of ISL satellite orbit locations, tolerable satellite spacing, and crosslink traffic-handling requirements. An ISL technology assessment is made by performing a parametric link analysis for several microwave and optical implementations. The impact of the crosslink on the end-to-end link performance is investigated for both regenerative and nonregenerative ISL architectures. A comparison is made between single satellite systems operating at C-, and Ku-bands and the corresponding ISL systems in terms of ground segment cost, space segment cost, and net link performance. Results indicate that ISL's can effectively expand the CONUS orbital arc, with a 60 GHz ISL implementation being the most attractive.

Ponchak, D. S.↗
NASA NTRS1986

Application of intersatellite links to domestic satellite systems

The results of a study on intersatellite link (ISL) applications for domestic satellite communications are presented. It was determined if any technical, economic, or performance benefits could be gained by introducing intersatellite links into a domestic satellite communication network. Several key systems issues of domestic ISL's are addressed. These include the effect of a skewed traffic distribution on the selection of ISL satellite orbit locations, tolerable satellite spacing, and crosslink traffic-handling requirements. An ISL technology assessment is made by performing a parametric link analysis for several microwave and optical implementations. The impact of the crosslink on the end-to-end link performance is investigated for both regenerative and nonregenerative ISL architectures. A comparison is made between single satellite systems operating at C-, and Ku-bands and the corresponding ISL systems in terms of ground segment cost, space segment cost, and net link performance. Results indicate that ISL's can effectively expand the CONUS orbital arc, with a 60 GHz ISL implementation being the most attractive.

Ponchak, D. S.↗
NASA NTRS2010

Cruise-Efficient Short Takeoff and Landing (CESTOL): Potential Impact on Air Traffic Operations

The National Aeronautics and Space Administration (NASA) is investigating technological and operational concepts for introducing Cruise-Efficient Short Takeoff and Landing (CESTOL) aircraft into a future US National Airspace System (NAS) civil aviation environment. CESTOL is an aircraft design concept for future use to increase capacity and reduce emissions. CESTOL provides very flexible takeoff, climb, descent and landing performance capabilities and a high-speed cruise capability. In support of NASA, this study is a preliminary examination of the potential operational impact of CESTOL on airport and airspace capacity and delay. The study examines operational impacts at a subject site, Newark Liberty Intemational Airport (KEWR), New Jersey. The study extends these KEWR results to estimate potential impacts on NAS-wide network traffic operations due to the introduction of CESTOL at selected major airports. These are the 34 domestic airports identified in the Federal Aviation Administration's Operational Evolution Plan (OEP). The analysis process uses two fast-time simulation tools to separately model local and NAS-wide air traffic operations using predicted flight schedules for a 24-hour study period in 2016. These tools are the Sen sis AvTerminal model and NASA's Airspace Concept Evaluation System (ACES). We use both to simulate conventional-aircraft-only and CESTOL-mixed-with-conventional-aircraft operations. Both tools apply 4-dimension trajectory modeling to simulate individual flight movement. The study applies AvTerminal to model traffic operations and procedures for en route and terminal arrival and departures to and from KEWR. These AvTerminal applications model existing arrival and departure routes and profiles and runway use configurations, with the assumption jet-powered, large-sized civil CESTOL aircraft use a short runway and standard turboprop arrival and departure procedures. With these rules, the conventional jet and CESTOL aircraft are procedurally separated from each other geographically and in altitude during tenninal airspace approach and departure operations, and each use a different arrival runway. AvTeminal implements its unique Focal-point Scheduling Process to sequence, space and delay aircraft to resolve spacing and overtake conflicts among flights in the airspace and airport system serving KEWR. This Process effectively models integrated arrival and departure operations. AvTerminal assesses acceptance rates and delay magnitude and causality at selected locations, including en route outer boundary fixes, tenninal airspace arrival and departure boundary fixes, terminal airspace arrival merge and departure diverge fixes, and runway landing and takeoff runways. The analysis compares the resulting capacity impacts, flight delays and delay sources between CESTOL and conventional KEWR operations. AvTerminal quantitative results showed that CESTOL has significant capability to increase airport arrival acceptance rates (35-40% at KEWR) by taking advantage of otherwise underused airspace and runways where available. The study extrapolates the AvTerminal-derived KEWR peak arrival and departure acceptance rates to estimate capacity parameter values for each of the OEP airports in the ACES modeling of traffic through the entire NAS network. The extrapolations of acceptance rates allow full, partial or no achievement of CESTOL capacity gains at an OEP airport as determined by assessments of the degree to which local procedures allow leveraging of CESTOL capabilities. These assessments consider each OEP airport's runway geometries, runway system configurations, airport and airspace operations, and potential CESTOL traffic loadings. The ACES modeling, simulates airport and airspace spacing constraints imposed by airport runway system, terminal and en route air traffic control and traffic flow management operations using airport acceptance rates representing conventional-aircraft-only and CESTOL-mixed operations. CEOL aircraft are assumed to have Mach 0.8, and alternatively Mach 0.7, cruise speeds to examine compatibility with conventional aircraft operations in common airspace. The ACES results provides estimates of CESTOL delay impact NAS-wide and at OEP airports due to changes in OEP airport acceptance rates and changes in en route airspace potential conflict rates. Preliminary results show meaningful nationwide delay reductions (20%) due to CESTOL operations at 34 major domestic airports.

Couluris, G. J.↗
NASA NTRS1974

Advanced subsonic long-haul transport terminal area compatibility study. Volume 1: Compatibility assessment

An analysis was made to identify airplane research and technology necessary to ensure advanced transport aircraft the capability of accommodating forecast traffic without adverse impact on airport communities. Projections were made of the delay, noise, and emissions impact of future aircraft fleets on typical large urban airport. Design requirements, based on these projections, were developed for an advanced technology, long-haul, subsonic transport. A baseline aircraft was modified to fulfill the design requirements for terminal area compatibility. Technical and economic comparisons were made between these and other aircraft configured to support the study.

Source record↗
NASA NTRSDate not supplied

Prediction-Based Approaches for Generation of Noise-Power-Distance Data with Application to Urban Air Mobility Vehicles

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise-power-distance (NPD) data for use within AEDT. One utilizes AEDT’s fixed-wing aircraft modeling approach and the other utilizes the rotary-wing aircraft modeling approach.

noise-power-distance↗
NASA NTRS2023

Prediction of Noise-Power-Distance Data for Urban Air Mobility Vehicles

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise-power-distance (NPD) data for use within AEDT. One utilizes the AEDT fixed-wing aircraft modeling approach and the other utilizes the AEDT rotary-wing aircraft modeling approach.

noise-power-distance↗
NASA NTRSDate not supplied

On the Modeling of UAM Aircraft Community Noise in AEDT Helicopter Mode

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations. Prior work focused on modeling UAM aircraft within AEDT under fixed-wing mode. This paper addresses the modeling of UAM aircraft under helicopter mode, using requisite noise-power-distance data generated through analysis. Results are compared with those from the fixed-wing approach and a hybrid approach. The latter models some flight segments in fixed-wing mode and others in helicopter mode.

aircraft community noise↗
NASA NTRS2012

Projected Demand and Potential Impacts to the National Airspace System of Autonomous, Electric, On-Demand Small Aircraft

Electric propulsion and autonomy are technology frontiers that offer tremendous potential to achieve low operating costs for small-aircraft. Such technologies enable simple and safe to operate vehicles that could dramatically improve regional transportation accessibility and speed through point-to-point operations. This analysis develops an understanding of the potential traffic volume and National Airspace System (NAS) capacity for small on-demand aircraft operations. Future demand projections use the Transportation Systems Analysis Model (TSAM), a tool suite developed by NASA and the Transportation Laboratory of Virginia Polytechnic Institute. Demand projections from TSAM contain the mode of travel, number of trips and geographic distribution of trips. For this study, the mode of travel can be commercial aircraft, automobile and on-demand aircraft. NASA's Airspace Concept Evaluation System (ACES) is used to assess NAS impact. This simulation takes a schedule that includes all flights: commercial passenger and cargo; conventional General Aviation and on-demand small aircraft, and operates them in the simulated NAS. The results of this analysis projects very large trip numbers for an on-demand air transportation system competitive with automobiles in cost per passenger mile. The significance is this type of air transportation can enhance mobility for communities that currently lack access to commercial air transportation. Another significant finding is that the large numbers of operations can have an impact on the current NAS infrastructure used by commercial airlines and cargo operators, even if on-demand traffic does not use the 28 airports in the Continental U.S. designated as large hubs by the FAA. Some smaller airports will experience greater demand than their current capacity allows and will require upgrading. In addition, in future years as demand grows and vehicle performance improves other non-conventional facilities such as short runways incorporated into shopping mall or transportation hub parking areas could provide additional capacity and convenience.

Smith, Jeremy C.↗
NASA NTRS2018

The Influence of Mental Workload in Causes of System Degradation in Air Traffic Control

System safety and resilience is a critical concern in the air traffic domain. An important element of maintaining system safety and resilience is the ability of systems to ‘degrade gracefully’. However, previous research on the causes of system degradation in the air traffic domain are sporadic, and the potential interaction between the causes of degradation, and the resulting possible compound effect on the entire system, has been under-researched. An interview study was conducted with 12 retired controllers as participants. The results of a thematic analysis revealed the key causes of system degradation, and the associated impact on the ability of the controllers to prevent system degradation or recover the system. Findings have direct implications for identifying and mitigating potential risks of increasingly automated air traffic control systems.

Edwards, Tamsyn E.↗
NASA NTRS2018

The Influence of Mental Workload in Causes of System Degradation in Air Traffic Control

System safety and resilience is a critical concern in the air traffic domain. An important element of maintaining system safety and resilience is the ability of systems to ‘degrade gracefully'. However, previous research on the causes of system degradation in the air traffic domain are sporadic, and the potential interaction between the causes of degradation, and the resulting possible compound effect on the entire system, has been under-researched. An interview study was conducted with 12 retired controllers as participants. The results of a thematic analysis revealed the key causes of system degradation, and the associated impact on the ability of the controllers to prevent system degradation or recover the system. Findings have direct implications for identifying and mitigating potential risks of increasingly automated air traffic control systems.

Edwards, Tamsyn↗
NASA NTRS2016

Benefit Opportunities for Integrated Surface and Airspace Departure Scheduling: A Study of Operations at Charlotte-Douglas International Airport

NASA is collaborating with the FAA and aviation industry to develop and demonstrate new capabilities that integrate arrival, departure, and surface air-traffic operations. The concept relies on trajectory-based departure scheduling and collaborative decision making to reduce delays and uncertainties in taxi and climb operations. The paper describes the concept and benefit mechanisms aimed at improving flight efficiency and predictability while maintaining or improving operational throughput. The potential impact of the technology is studied and discussed through a quantitative analysis of relevant shortfalls at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport. Results from trajectory analysis indicate substantial opportunity to reduce taxi delays for both departures and arrivals by metering departures at the gate in a manner that maximizes throughput while adhering to takeoff restrictions due mostly to airspace constraints. Substantial taxi-out delay reduction is shown for flights subject to departure restrictions stemming from traffic flow management initiatives. Opportunities to improve the predictability of taxi, takeoff, and climb operations are examined and their potential impact on airline scheduling decisions and air-traffic forecasting is discussed. In addition, the potential to improve throughput with departure scheduling that maximizes use of available runway and airspace capacity is analyzed.

air traffic management↗
DOE OSTI2025

Energy-efficient multimodal mobility networks in transportation digital twins: Strategies and optimization

The study proposes a comprehensive Transportation Mobility (TransitMo) framework covering conceptual design, model formulation, optimization, simulation, and impact analysis of the transportation mobility system. TransitMo is composed of a transportation digital twin developed in Simulation of Urban MObility (SUMO) and an Intelligent Traffic Management and Control Center (ITMCC) that identifies the best ways to improve the movement of people within urban areas using various modes of transportation. This study encompasses advanced modeling techniques, algorithms, and strategic testing to optimize energy efficiency and mobility in a multimodal shared mobility network. TransitMo’s practical applications are exemplified through a city-scaled simulation network in Chattanooga, TN, employing demographic data to analyze historical traffic patterns and forecast future demands. Central to this methodology are three models: the User Preference Model (UP), the Energy Consumption Model (EC), and the System Optimization Model (SO). These models work in concert to iteratively devise the optimal travel incentives and minimize the total system cost in a real-time manner. In conclusion, test results verified that the proposed adaptive incentive program and optimized bus scheduling can improve network performance by increasing public transit ridership.

42 ENGINEERING↗
NASA NTRS2015

Conflict Detection Performance Analysis for Function Allocation Using Time-Shifted Recorded Traffic Data

The performance of the conflict detection function in a separation assurance system is dependent on the content and quality of the data available to perform that function. Specifically, data quality and data content available to the conflict detection function have a direct impact on the accuracy of the prediction of an aircraft's future state or trajectory, which, in turn, impacts the ability to successfully anticipate potential losses of separation (detect future conflicts). Consequently, other separation assurance functions that rely on the conflict detection function - namely, conflict resolution - are prone to negative performance impacts. The many possible allocations and implementations of the conflict detection function between centralized and distributed systems drive the need to understand the key relationships that impact conflict detection performance, with respect to differences in data available. This paper presents the preliminary results of an analysis technique developed to investigate the impacts of data quality and data content on conflict detection performance. Flight track data recorded from a day of the National Airspace System is time-shifted to create conflicts not present in the un-shifted data. A methodology is used to smooth and filter the recorded data to eliminate sensor fusion noise, data drop-outs and other anomalies in the data. The metrics used to characterize conflict detection performance are presented and a set of preliminary results is discussed.

Guerreiro, Nelson M.↗