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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing traffic safety analysis with digital twin technology: integrating vehicle dynamics and environmental factors into microscopic traffic simulation

Traffic safety is a critical concern in transportation engineering and urban planning. Traditional traffic safety analysis requires trained observers to collect data in the field, which is time-consuming, labor-intensive, and sometimes inaccurate. In recent years, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, have been utilized to study traffic safety. However, microscopic traffic simulation only focuses on traffic-related factors, such as traffic volume, traffic signals, and lane configurations, neglecting vehicle dynamics and environment-related factors like weather and lighting conditions, which can significantly impact traffic safety. In light of this, this paper explores the application of digital twin technology in traffic safety analysis, integrating vehicle simulators, which consider vehicle dynamics and environmental factors, and microscopic traffic simulators, which simulate the operations of traffic flow, for enhanced safety evaluations. Various scenarios, including different weather conditions and visibility levels, are simulated using a digital twin of a road segment in Tuscaloosa, Alabama. The simulations employ Surrogate Safety Measures (SSMs) like Time to Collision (TTC) and Deceleration Rate to Avoid a Crash (DRAC) to assess safety under varying conditions. The results demonstrate that traffic digital twin can identify potential safety issues that traditional microscopic simulation cannot, providing insights for improving traffic control strategies and transportation infrastructure to enhance traffic safety.

Civil engineering↗
DOE OSTI2025

Traffic Shaping to Traffic Engineering in Time-Sensitive OT Network

Modern industrial automation systems increasingly depend on network infrastructures for time-critical communication, driving the need for solutions that guarantee timely and reliable data delivery. IEEE 802.1 Time-Sensitive Networking (TSN) holds significant promise for converging Information Technology (IT) and Operational Technology (OT) networks, enabling interoperability and supporting the coexistence of mixed-critical traffic crucial for Industry 4.0 and IIoT. To achieve deterministic communication, TSN employs various traffic shapers such as the Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), and Credit-Based Shaper (CBS). However, the effective deployment of TSN in industrial automation faces several challenges. These include the non-trivial mapping of diverse industrial traffic types to specific shapers, the complexity of optimizing shaper configurations. We present a model for effective traffic engineering within TSN enabled OT Network. Our experiments also demonstrate how shaping of certain traffic types get affected in absence of precise time synchronization and propose possible solutions based on experiment results. Based on our experimental results we provide recommendations on how traffic type assignments should be done and which traffic shaping mechanisms should be used for a particular traffic type.

Sarker, Taposh Kumer [University of Texas at El Pa↗
NASA NTRS2023

Search for UnderUtilized Airspace for Extensible Traffic Management Operations Based on Air Traffic Patterns

This paper presents a new method to facilitate integrating new vehicle traffic operations, operating with existing air traffic operations. The extensible traffic management (xTM) concept assumes that the new vehicles can operate in a dedicated Cooperative Area (CA) with minimal interaction with conventional air traffic and requiring minimal air traffic supervision. Our method assumes that a new xTM CA can be created when an underutilized airspace with little or no traffic can be identified. Our approach involves modeling airspace as a tree data structure and iteratively subdividing it into smaller cells, with underutilized airspace defined as any cells without flight tracks. The benefits of our approach include its applicability to all xTM scenarios, the ability to handle both 2D and 3D space using a unique tree data structure, and computational efficiency for key functions such as space decomposition, labeling of connected cells, and searching of cells containing a given point. By automatically searching for underutilized airspace based on operating air traffic patterns, we can optimize airspace utilization and improve air traffic management. Our proposed approach can quantitatively determine when and where to allow xTM operations in the National Airspace System.

extensible traffic management↗
NASA NTRS1973

Geosynchronous platform definition study. Volume 4, Part 1: Traffic analysis and system requirements for the baseline traffic model

The traffic analyses and system requirements data generated in the study resulted in the development of two traffic models; the baseline traffic model and the new traffic model. The baseline traffic model provides traceability between the numbers and types of geosynchronous missions considered in the study and the entire spectrum of missions foreseen in the total national space program. The information presented pertaining to the baseline traffic model includes: (1) definition of the baseline traffic model, including identification of specific geosynchronous missions and their payload delivery schedules through 1990; (2) Satellite location criteria, including the resulting distribution of the satellite population; (3) Geosynchronous orbit saturation analyses, including the effects of satellite physical proximity and potential electromagnetic interference; and (4) Platform system requirements analyses, including satellite and mission equipment descriptions, the options and limitations in grouping satellites, and on-orbit servicing criteria (both remotely controlled and man-attended).

Source record↗
NASA NTRS1997

Design and Operational Evaluation of the Traffic Management Advisor at the Ft. Worth Air Route Traffic Control Center

NASA and the FAA have designed and developed and an automation tool known as the Traffic Management Advisor (TMA). The system was operationally evaluated at the Ft. Worth Air Route Traffic Control Center (ARTCC). The TMA is a time-based strategic planning tool that provides Traffic Management Coordinators and En Route Air Traffic Controllers the ability to efficiently optimize the capacity of a demand impacted airport. The TMA consists of trajectory prediction, constraint-based runway scheduling, traffic flow visualization and controllers advisories. The TMA was used and operationally evaluated for forty-one rush traffic periods during a one month period in the Summer of 1996. The evaluations included all shifts of air traffic operations as well as periods of inclement weather. Performance data was collected for engineering and human factor analysis and compared with similar operations without the TMA. The engineering data indicates that the operations with the TMA show a one to two minute per aircraft delay reduction during rush periods. The human factor data indicate a perceived reduction in en route controller workload as well as an increase in job satisfaction. Upon completion of the evaluation, the TMA has become part of the normal operations at the Ft. Worth ARTCC.

Swenson, Harry N.↗
NASA NTRS2017

Ramp Traffic Console (RTC) Ramp Manager Traffic Console (RMTC) Observer Mode User Manual

This document serves as a user manual for the Observer Mode Ramp Traffic Console (RTC) in Charlotte Douglas International Airport Ramp Control Tower. It describes the elements of the full RTC interface and provides explanations for how to interact with the RTC while managing ramp traffic using one of the four RTC sector displays. The RTC provides digitally updated data for all flights including Earliest Off Block Times (EOBT) and Traffic Management Initiatives. Use of the RTC in observer mode allows only for observer and reading of data provided on RTC. In Observer Mode, the RTC may not be used to make data entries. This includes pushback, holds, and proceed inputs as well as updates to a flights data using the flight menu. However, using the RTC in Observer Mode allows for real time observation of ramp operations including pushback and hold entries made by the ramp sector controllers. The pushback advisories and Traffic Management Initiative information is also provided in Observer Mode. The RTC also provides notifications, runway departure counts and lists and near arrival flight lists as additional sources of information for management of ramp traffic. There are also detailed instructions for how to manage traffic with Surface Time Based Metering (STBM) advisories provided on RTC if in STBM mode. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) while performing ramp manager functions such as managing the priority flight list, setting ramp status, and setting the metering mode. The RTC and RMTC ramp tool are one component of a suite of ATD-2 Tools.

Stevens, Lindsay K.↗
DOE OSTI2026

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗
NASA NTRSDate not supplied

Identifying Information Needs and Tools to Support Interactions between Upper Class E Traffic Management (ETM) Operations and the Air Traffic System (ATS)

With the introduction of high-altitude long endurance (HALE) vehicles and balloons designed to operate above 60,000 feet, the frequency and duration of operations in Upper Class E airspace are expected to increase. In response to the need for scalable traffic management for these diverse operations at higher altitudes, the FAA introduced the Upper Class E Traffic Management (ETM) concept. Like the successful demonstration of Uncrewed Aircraft System (UAS) Traffic Management (UTM), the ETM concept is also designed as a community-based, industry-driven cooperative approach to traffic management. As these vehicles and balloons ascend to/descend from ETM Cooperative Areas in Upper Class E, they will transit through Class A controlled airspace where they will interact with various entities of the conventional Air Traffic System (ATS) (e.g., Air Traffic Control (ATC)). This work explores tools that will help support ETM-ATS interactions for users throughout the ATS, as well as ETM Operators. An information needs analysis using ETM-ATS interaction use cases, revealed that the needed functionalities generally grouped themselves into two main themes, the visualization of flights and airspace designations, and digital communication capabilities across various human users. In this paper, we describe two envisioned tools, 1) an Integrated Visualization Tool to display flight information and airspace designations, and 2) an Integrated Digital Communication Tool to facilitate two-way information exchange between users about vehicle position information, the coordination of airspace approvals, and notifications. The tools we describe create an integrated visual representation of vehicles and airspace designations with a set of communication capabilities to consolidate information into a single display interface. These tools may be used to guide the development of prototype tools for demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center to further explore ETM-ATS interactions within the ETM concept.

Upper Class E Traffic Management (ETM)↗
NASA NTRSDate not supplied

Identifying Information Needs and Tools to Support Interactions between Upper Class E Traffic Management (ETM) Operations and the Air Traffic System (ATS)

With the introduction of high-altitude long endurance (HALE) vehicles and balloons designed to operate above 60,000 feet, the frequency and duration of operations in Upper Class E airspace are expected to increase. In response to the need for scalable traffic management for these diverse operations at higher altitudes, the FAA introduced the Upper Class E Traffic Management (ETM) concept. Like the successful demonstration of Uncrewed Aircraft System (UAS) Traffic Management (UTM), the ETM concept is also designed as a community-based, industry-driven cooperative approach to traffic management. As these vehicles and balloons ascend to/descend from ETM Cooperative Areas in Upper Class E, they will transit through Class A controlled airspace where they will interact with various entities of the conventional Air Traffic System (ATS) (e.g., Air Traffic Control (ATC)). This work explores tools that will help support ETM-ATS interactions for users throughout the ATS, as well as ETM Operators. An information needs analysis using ETM-ATS interaction use cases, revealed that the needed functionalities generally grouped themselves into two main themes, the visualization of flights and airspace designations, and digital communication capabilities across various human users. In this paper, we describe two envisioned tools, 1) an Integrated Visualization Tool to display flight information and airspace designations, and 2) an Integrated Digital Communication Tool to facilitate two-way information exchange between users about vehicle position information, the coordination of airspace approvals, and notifications. The tools we describe create an integrated visual representation of vehicles and airspace designations with a set of communication capabilities to consolidate information into a single display interface. These tools may be used to guide the development of prototype tools for demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center to further explore ETM-ATS interactions within the ETM concept.

Upper Class E Traffic Management (ETM)↗
NASA NTRSDate not supplied

Identifying Common Use Cases across Extensible Traffic Management (xTM) for Interactions with Air Traffic Controllers

NASA’s Extensible Traffic Management (xTM) builds on the foundation and the architecture of Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concept and extends it broadly to other domains, such as Advanced / Urban Air Mobility (AAM/UAM) and Upper Class E Traffic Management (ETM). These xTM concepts assume the ability to fly in airspace that is authorized to operate solely under xTM services and mostly without any air traffic control (ATC) support. However, they also assume circumstances in which the xTM vehicles would need to operate in conventional ATC-managed airspace, both during nominal and off-nominal scenarios. Due to the vast differences in the xTM vehicle performances and missions, there is a concern that ATC may have difficulty in safely managing the xTM traffic and providing appropriate services to all vehicles, unless a consistent set of roles, procedures, and data exchange requirements are defined across the diverse set of xTM vehicle operations. In this paper, we describe a set of use cases that have been identified in UTM, AAM/UAM, and ETM operations that are related to ATC interactions, and we propose to categorize these use cases across xTM domains based on common trigger events. Organizing the use cases from the perspective of ATC roles per each trigger event is expected to provide the first step in discovering common procedures and data requirements across xTM domains that could help ease the controllers’ cognitive task load and allow them to manage these interactions more safely.

Extensible Traffic Management (xTM)↗
NASA NTRS2001

The Development of the Multi-Center Traffic Management Advisor (MCTMA): Traffic Flow Management Research in a Multi-Facility Environment

The Traffic Management Advisor (TMA) is a decision-support tool for traffic managers and air traffic controllers that provides traffic flow visualization and other flow management tools. TMA creates an efficiently sequenced and safely spaced schedule for arrival traffic that meets but does not exceed specified airspace system constraints. TMA is being deployed at selected facilities throughout the National Airspace System in the US as part of the FAA's Free Flight Phase 1 program. TMA development and testing, and its current deployment, focuses on managing the arrival capacity for single major airports within single terminal areas and single en route centers. The next phase of development for this technology is the expansion of the TMA capability to complex facilities in which a terminal area or airport is fed by multiple en route centers, thus creating a multicenter TMA functionality. The focus of the multi-center TMA (McTMA) development is on the busy facilities in the Northeast comdor of the US. This paper describes the planning and development of McTMA and the challenges associated with adapting a successful traffic flow management tool for a very complex airspace.

Lee, Katharine K.↗
NASA NTRSDate not supplied

Simple Pattern Traffic Generation for Automated Flight Research in Non-Towered Traffic Patterns

Research efforts into autonomous air traffic will necessitate tools for testing algorithm capabilities. Testing will require flexible methods for creating large quantities of artificial data to verify the safety of automated systems. The traffic generation method in this work was developed to test traffic prediction and replanning algorithms for an autonomous vehicle attempting to land at a non-towered airport. The traffic generation method produces airport approach trajectories supporting a wide range of pattern entry types and typical pattern modification maneuvers for multiple aircraft types with varying performance capabilities. For each aircraft there are options for choosing the approach type, modifying how the approach is flown, and imposing scenario-driven temporal constraints, such as spacing between pairs of aircraft. The tool uses simplified aircraft dynamics to produce position and velocity profiles for traffic vehicles. Additionally, the tool supports standalone simulation tests or batch/bulk testing efforts, multiple output data options, and facilitates post-processing analysis.

Autonomous Vehicle↗
NASA NTRS1983

Simulation study of traffic-sensor noise effects on utilization of traffic situation display for self-spacing task

The effect of traffic sensor noise on the ability of a pilot to perform an intrail spacing task was determined. The tests were conducted in a fixed base cockpit simulator configured as a current generation transport aircraft, with an electronic traffic display provided in the weather radarscope location. The true positions of the traffic were perturbed in both relative range and azimuth by random errors to simulate traffic sensor noise associated with an onboard sensor. The evaluation task involved simulated instrument approaches into a terminal area while maintaining self separation on a lead aircraft. Separation performance data and pilot subjective ratings and comments were obtained. The results of the separation data indicate that displayed traffic position errors, having standard deviation values up to 0.3-n.mi. range and 8 deg azimuth, had negligible effect on the spacing performance achieved by the pilots. Speed profiles of the lead aircraft, display of the lead aircraft groundspeed, and individual pilot techniques were found to significantly affect the mean spacing performance.

Williams, D. H.↗
NASA NTRS2018

Ramp Traffic Console (RTC) Ramp Manager Traffic Console (RMTC) User Manual

This document serves as a user manual for the Ramp Traffic Console (RTC) in the Ramp Control Tower. It describes the elements of the RTC interface and provides explanations for how to utilize the RTC to manage ramp traffic. The RTC provides live data for all flights including Earliest Off-Block Times (EOBT) and Traffic Management Initiatives (TMI). The RTC augments management of ramp traffic by providing notifications of runway configurations, and lists flight arrivals, near arrivals and departures as additional sources of information. If applicable, this document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) for ramp manager functions of adjusting the priority flight list, and setting ramp status. The RTC/RMTC ramp tool are components of Airspace Technology Demonstration-2.

ATD-2 RMTC↗
NASA NTRS2019

Ramp Traffic Console (RTC) Ramp Manager Traffic Console (RMTC) User Manual

This document serves as a user manual for the Ramp Traffic Console (RTC) Version 4.6.0 in the Ramp Control Tower. It describes the elements of the RTC interface and provides explanations for how to utilize RTC to manage ramp traffic. RTC provides live data for all flights including Earliest Off-Block Times (EOBTs) and Traffic Management Initiatives (TMIs). RTC augments management of ramp traffic by providing notifications of runway configurations, and lists flight arrivals, near arrivals, and departures as additional sources of information. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) for Ramp Manager functions, such as adjusting the priority flight list and setting the ramp status. The RTC/RMTC ramp tools are components of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Airport surface decision support tool↗
NASA NTRS2020

Air Traffic Management TestBed Traffic Viewer: Developer's Guide

The Air Traffic Management (ATM) TestBed is a Platform as a Service that is being developed by the National Aeronautics and Space Administration (NASA) to help design, configure, integrate, run, and monitor air traffic simulations. The platform is designed to provide cloud services including back-end, big-data analytics tools, on-demand computing resource management, data storage, and communication middleware. The ATM TestBed reduces the time to test concepts and technologies, supports interactions among various methods such as human-in-the-loop and automation-in-the-loop simulations, and enables collaborative simulations by sharing technologies and tools in the ATM community. The Traffic Viewer application provides a graphical user interface tool for visualizing real and simulated air traffic as well as airspace definition in two-dimensional space. This guide describes a high-level design and implementation of Traffic Viewer and provides information for a new developer or a user to add new capabilities by following the software design and leveraging existing capabilities.

Lai, Chok Fung↗
NASA NTRS1977

A computerized traffic control algorithm to determine optimal traffic signal settings

An algorithm was developed to optimally control the traffic signals at each intersection using a discrete time traffic model applicable to heavy or peak traffic. Off line optimization procedures were applied to compute the cycle splits required to minimize the lengths of the vehicle queues and delay at each intersection. The method was applied to an extensive traffic network in Toledo, Ohio. Results obtained with the derived optimal settings are compared with the control settings presently in use.

Seldner, K.↗
NASA NTRS2020

Ramp Traffic Console (RTC) and Ramp Manager Traffic Console (RMTC) User Manual

This document serves as a user manual for the ATD-2 Ramp Traffic Console (RTC) (version 5.11) utilized by the Ramp Control Tower. It describes the elements of the RTC interface and provides step-by-step instructions for using the tool. RTC provides live flight information, including, flight state and location, departure/arrival schedules, gate conflicts, Traffic Management Initiative (TMI) restrictions, and gate advisories to support Surface Time-Based Metering (STBM). RTC facilitates information sharing with the Air Traffic Control (ATC) Tower. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) for Ramp Manager functions, such as managing the priority flight list and setting the ramp status. The RTC/RMTC ramp tools are components of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Deborah Lee Bakowski↗