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At least 55 records · Page 3

Analysis and prediction of intersection traffic violations using automated enforcement system data

We report that the automated enforcement system (AES) is an effective way of supplementing traditional traffic enforcement, and the traffic violation data from AES can also be effectively used for safety research. In this study, traffic violation data were used to analyze the influencing factors associated with traffic violations and to predict the probability of violations at intersections. The potential factors influencing violations include 24 independent factors related to time, space, traffic and weather. Results from a logistic model showed that the midday period, weekends, residential districts, collector roads, congested traffic conditions, high traffic flow, lower wind speed and low temperature would increase the probability of traffic violations. The probability of violations was predicted by the random forest algorithm, which was proven to be the best traffic violation prediction model among logistic regression, Gaussian naive Bayes, and support vector machine. Moreover, the proximity weighted synthetic oversampling technique (ProWSyn) method was applied to reduce the impact of the imbalance ratio (IR) and improve the model’s prediction performance. The receiver operating characteristics (ROC) curves and Precision-Recall (PR) curves illustrated that the random forest algorithm using oversampling data had the best classifier prediction performance than undersampling data. The area under curve (AUC) and out-of-bag (OOB) error with IR = 1 reached 0.914 and 0.0787, which showed the better performance of the random forest algorithm using ProWSyn in dealing with imbalanced traffic violation data.

42 ENGINEERING↗

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

Orbital Debris Quarterly News, Volume 13, No. 3

Inside - Congressional Hearing Held on Orbital Debris and Space Traffic - United Nations' COPUOS Receives Update on Iridium-Cosmos Collision - MMOD Inspection of the HST WFPC2 Radiator - Reentry Survivability Analysis of GPM Spacecraft - Update on Recent Major Breakup Fragments - Upcoming Meetings - Space Missions and Orbital Box Score

J.-C. Liou↗

Probabilistic Data Association for Orbital-Element Estimation Using Multistage Expectation–Maximization

Tracking space objects is important for managing space traffic and predicting collisions, but is difficult in part due to data association and orbit model uncertainty. Expectation–maximization (EM) is a commonly used tracking method that has not been widely considered for tracking space objects. The technique consists of iteratively computing data association probabilities with a set of current element estimates, and updating estimates of the elements by solving a nonlinear weighted least-squares regression problem where the weights are the data association probabilities. In this paper, we demonstrate the use of EM for probabilistic data association and orbital-element estimation by applying the technique to simulated data from two angles-only tracking scenarios. In both scenarios, EM provides correct data associations and accurate maximum likelihood estimates of orbital elements. One scenario considers tracking a single object in clutter and quantifies the improvement of the orbital-element estimates and data associations as the detection probability increases. However, standard application of EM requires knowing the number of objects or may fail when a large number of objects are present. To address these issues, this paper employs a multistage version of EM that is applicable when there are a large and possibly unknown number of objects.

97 MATHEMATICS AND COMPUTING↗

Enhanced/Synthetic Vision and Head-Worn Display Technologies for Terminal Maneuvering Area NextGen Operations

NASA is researching innovative technologies for the Next Generation Air Transportation System (NextGen) to provide a "Better-Than-Visual" (BTV) capability as adjunct to "Equivalent Visual Operations" (EVO); that is, airport throughputs equivalent to that normally achieved during Visual Flight Rules (VFR) operations rates with equivalent and better safety in all weather and visibility conditions including Instrument Meteorological Conditions (IMC). These new technologies build on proven flight deck systems and leverage synthetic and enhanced vision systems. Two piloted simulation studies were conducted to access the use of a Head-Worn Display (HWD) with head tracking for synthetic and enhanced vision systems concepts. The first experiment evaluated the use a HWD for equivalent visual operations to San Francisco International Airport (airport identifier: KSFO) compared to a visual concept and a head-down display concept. A second experiment evaluated symbology variations under different visibility conditions using a HWD during taxi operations at Chicago O'Hare airport (airport identifier: KORD). Two experiments were conducted, one in a simulated San Francisco airport (KSFO) approach operation and the other, in simulated Chicago O'Hare surface operations, evaluating enhanced/synthetic vision and head-worn display technologies for NextGen operations. While flying a closely-spaced parallel approach to KSFO, pilots rated the HWD, under low-visibility conditions, equivalent to the out-the-window condition, under unlimited visibility, in terms of situational awareness (SA) and mental workload compared to a head-down enhanced vision system. There were no differences between the 3 display concepts in terms of traffic spacing and distance and the pilot decision-making to land or go-around. For the KORD experiment, the visibility condition was not a factor in pilot's rating of clutter effects from symbology. Several concepts for enhanced implementations of an unlimited field-of-regard BTV concept for low-visibility surface operations were determined to be equivalent in pilot ratings of efficacy and usability.

Arthur, Jarvis J., III↗

NASA Small Spacecraft and Distributed Systems Program - Recent and Upcoming Technology Demonstrations and Development Efforts

NASA’s Small Spacecraft & Distributed Systems (SSDS) program strengthens U.S. ability to conduct unique missions by rapidly developing and demonstrating capabilities for SmallSat exploration, science, and commercial space. In collaboration with NASA Centers, other government agencies, commercial industry, and academia, SSDS advances next generation SmallSat technologies like power, processing, propulsion, communications, autonomous navigation, architectures (swarms), and applications (AI/ML/Edge Computing)—to extend missions beyond LEO into cislunar and planetary space. Various investment mechanisms exist for SSDS to select and fund projects that will ultimately advance NASA’s Moon to Mars Architecture. Presented here are the latest achievements and findings from recently completed SSDS projects, along with updates from ongoing efforts and planned future work. Successful missions like Starling and CAPSTONE continue to demonstrate their capability after several years on-orbit. Advancements in next generation swarm configurations are being implemented by Starling for space traffic monitoring and management applications. Findings from recent SSDS flight projects are discussed: DiskSat, a unique SmallSat platform alternative to canisterized nanosatellites, launched December 2025 and is gathering data; the PTD series of missions concluded in December 2025. Current SSDS efforts are focused on addressing NASA Shortfalls relating to rendezvous and proximity operations, neuromorphic computing, and space situational awareness.

Roger C Hunter↗

NASA Small Spacecraft and Distributed Systems: Recent and Upcoming Technology Demonstrations and Development Efforts

NASA’s Small Spacecraft & Distributed Systems (SSDS) program strengthens U.S. ability to conduct unique missions by rapidly developing and demonstrating capabilities for SmallSat exploration, science, and commercial space. In collaboration with NASA Centers, other government agencies, commercial industry, and academia, SSDS advances next generation SmallSat technologies like power, processing, propulsion, communications, autonomous navigation, architectures (swarms), and applications (AI/ML/Edge Computing)—to extend missions beyond LEO into cislunar and planetary space. Various investment mechanisms exist for SSDS to select and fund projects that will ultimately advance NASA’s Moon to Mars Architecture. Presented here are the latest achievements and findings from recently completed SSDS projects, along with updates from ongoing efforts and planned future work. Successful missions like Starling and CAPSTONE continue to demonstrate their capability after several years on-orbit. Advancements in next generation swarm configurations are being implemented by Starling for space traffic monitoring and management applications. Findings from recent SSDS flight projects are discussed: DiskSat, a unique SmallSat platform alternative to canisterized nanosatellites, launched December 2025 and is gathering data; the PTD series of missions concluded in December 2025. Current SSDS efforts are focused on addressing NASA Shortfalls relating to rendezvous and proximity operations, neuromorphic computing, and space situational awareness.

Roger Hunter↗

Multi‐Sensor Trajectory Reconstruction of the 24 April 2025 Alaska Fireball and Implications for Planetary Defense

On 24 April 2025 at 18:30:57 UTC, a bright daytime fireball over Southcentral Alaska was detected by 37 seismic stations, 16 single infrasound sensors, and four infrasound arrays, yielding 30 ballistic and multiple fragmentation arrivals. Here, the unprecedented density of seismoacoustic coverage enabled detailed reconstruction of the event using acoustic signals, with fragmentation source locations further guiding the identification of Doppler weather radar signatures of a meteorite fall. Incorporation of a radar-derived terminal point yielded a final trajectory solution, which agreed closely with an independent optical trajectory solution from video analysis. The reconstructed entry parameters from seismoacoustic analysis indicate a velocity of 25.3 km/s, an entry angle of 19°, and an energy release of ∼38 t TNT equivalent. Assuming a chondritic composition, the pre-entry object diameter was ∼0.7 m. Using orbital parameters from the optical solution, we estimate meteoroid composition as most likely an L-type ordinary chondrite. The event occurred in the sub-Arctic, where space-based optical systems face challenges in detection, demonstrating the critical role of dense ground-based seismoacoustic networks in characterizing high-latitude atmospheric entries. This uniquely well-recorded event demonstrates the capability of dense seismoacoustic networks to constrain bolide trajectories, energetics, and fragmentation, with radar and optical data providing critical confirmation and complementary perspectives. These results bridge the methodological gap between planetary-defense monitoring of natural impactors and space-traffic analyses of artificial reentries, illustrating how multi-sensor integration can deliver calibration-grade trajectories even for unpredicted events.

Fireball↗

System and technology considerations for space-based air traffic surveillance

This paper describes the system trade-offs examined in a recent study of space-based air traffic surveillance. Three system options, each satisfying a set of different constraints, were considered. The main difference in the technology needed to implement the three systems was determined to be the size of the spacecraft antenna aperture. It was found that essentially equivalent position location accuracy could be achieved with apertures from 50 meters down to less than a meter in diameter, depending on the choice of signal structure and on the desired user update rate.

Vaisnys, A.↗

Effect of the orbital debris environment on the high-energy Van Allen proton belt

The lifetimes of high-energy (greater than 55 MeV) protons in the Van Allen radiation belt are calculated, assuming that in time the protons will collide with and be absorbed by particulate orbiting material. The calculations are based on the NASA/DoD Civil Needs Database for orbital debris (Gaines, 1966) and moderate assumptions of future space traffic. It is found that the lifetimes of high-energy protons below 1500 km will decrease, leading to a noticeable redution in their fluxes.

Konradi, Andrei↗

Soil stabilization mat for lunar launch/landing site

Facilities which are capable of handling frequent arrivals and departures of spaceships between Earth and a lunar colony are necessary. The facility must be able to provide these services with minimal interruption of operational activity within the colony. The major concerns associated with the space traffic are the dust and rock particles that will be kicked up by the rocket exhaust. As a result of the reduced gravitation of the Moon, these particles scatter over large horizontal distances. This flying debris will not only seriously interrupt the routine operations of the colony, but could cause damage to the equipment and facilities surrounding the launch site. An approach to overcome this problem is presented. A proposed design for a lunar take-off/landing mat is presented. This proposal goes beyond dealing with the usual problems of heat and load resistances associated with take-off and landing, by solving the problem of soil stabilization at the site. Through adequate stabilization, the problem of flying debris is eliminated.

Acord, Amy L.↗

NASA/JSC orbital debris models

The orbital debris models developed within the framework of the NASA Johnson Space Center's (JSC's) orbital debris program, are categorized as environment definition and risk assessment models. The EVOLVE, CHAIN and the orbital debris engineering model 1996 (ORDEM96) computer programs determine the past, present and future orbital particulate environment, while the BUMPER and debris assessment software (DAS) computer programs provide a means for evaluating the risks of specific space missions. These models are presented. To support these models and to conduct specialized analyses, NASA/JSC employs a range of auxiliary models, including explosion and collision satellite breakup models, hypervelocity impact ballistic limit models, orbit propagation and decay models, space traffic models and solid rocket motor effluent models.

Johnson, Nicholas↗

Safe Space Conduct: NASA Best Practices Overview

While prevention of launch and on-orbit collisions has been an institutional concern of NASA for several decades (beginning with the Shuttle program), historically the paucity of spaceactors and deployed payloads made the conduct of such protection activities relatively straightforward. With the substantial increases in launched payloads over the last several years, collision avoidance operations have become substantially more complicated. At the same time, many operators are uncertain regarding what collision avoidance activities are appropriate to their missions. The lack of a space traffic management authority to articulate standards and guidelines for such conduct has only increased the confusion.In response to this situation, NASA has published a Spacecraft Conjunction Assessment and Collision Avoidance Handbook, which articulates and explains the launch and on-orbit collision avoidance best practices that the Agency has developed and is requiring of present and future NASA missions. Because the CA2 Handbook is a living document regularly updated to reflect best practices changes as the industry develops, feedback from both NASA missions and other users is continuously collected in order to issue CA2 Handbook updates.This talk will summarize and explain the collision avoidance best practices from the CA2Handbook, along with the key issues that drove the selection of those practices.

Conjunction Assessment↗

NASA Best Practices Overview

While prevention of launch and on-orbit collisions has been an institutional concern of NASA for several decades (beginning with the Shuttle program), historically the paucity of space actors and deployed payloads made the conduct of such protection activities relatively straightforward. With the substantial increases in launched payloads over the last several years, collision avoidance operations have become substantially more complicated. At the same time, many operators are uncertain regarding what collision avoidance activities are appropriate to their missions. The lack of a space traffic management authority to articulate standards and guidelines for such conduct has only increased the confusion. In response to this situation, NASA has published a Spacecraft Conjunction Assessment and Collision Avoidance Handbook, which articulates and explains the launch and on-orbit collision avoidance best practices that the Agency has developed and is requiring of present and future NASA missions. Because the CA2 Handbook is a living document regularly updated to reflect best practices changes as the industry develops, feedback from both NASA missions and other users is continuously collected in order to issue CA2 Handbook updates. This talk will summarize and explain the collision avoidance best practices from the CA2 Handbook, along with the key issues that drove the selection of those practices.

Conjunction Assessment↗

Conjunction Assessment and Deconfliction Paradigm for Co-Located Satellite Constellations With on-Spacecraft “Autonomous” Flight Dynamics Control

Satellite constellations that employ on-spacecraft flight dynamics and conjunction assessment (CA) approaches face particular challenges. First, they must arrange to obtain and upload to the constellation satellite close approach information, such as Conjunction Data Messages, so that their on-board systems will have the data they need to make informed CA decisions. Second, given current latencies in obtaining CA screening information, such systems often cannot obtain dedicated screenings of their proposed maneuvers before they are executed. Third, they usually cannot engage in real time with owner/operators (O/Os) with whom they may come into conjunction, relying instead on pre-arranged courses of action that may or may not fit a given situation well. Despite these difficulties, it is nonetheless possible, as operators such as SpaceX have demonstrated, to operate safely using on-board CA calculations, in the presence of a largely collaborative operating environment. The situation breaks down, however, when two constellations that operate with such a paradigm are placed in the same orbital region and will experience conjunctions with each other. Each may have a vague idea of where the other’s satellites are, or perhaps even a somewhat precise idea if they exchange O/O ephemerides, but neither will know the other’s more immediate maneuver intentions, especially for situations in which they are in a high-risk conjunction with each other and a mitigation maneuver is required. As there is no formalized way for these automated systems to ascertain each other’s intentions for this type of conjunction, it is quite possible that each spacecraft may choose a maneuver that results in the two objects’ colliding. An opportunity to develop a solution to this problem was presented by the NASA “Starling” project, a small experimental constellation developed to demonstrate autonomous satellite control and constellation reconfiguration and for which a launch was obtained that, serendipitously, will place this constellation close to the SpaceX Starlink constellation. Because the NASA constellation is experimental, an extended mission part of the mission has been negotiated to implement and test mechanisms for resolving the problem of co-located constellations with on-board flight dynamics control. For the last eighteen months, a consortium among NASA Ames (the Starling satellite providers), NASA CARA (the Agency organization responsible for conjunction assessment), Space X, and the Department of Commerce (in observer status) has met regularly to assemble a concept of operations for a robust solution to this problem and has developed a prototype ground node that will serve as a needed CA screening and information dispensary. The approach and methods, as well as the active employment of the developed ground node, will be tested both in simulation before actual use and then in actual spacecraft operations, which are anticipated to begin in January 2024. This paper will describe the co-located autonomously-controlled constellation problem and the developed solution in detail, outlining what ground node (i.e., government) infrastructure and features are required, what particular capabilities are needed by the constellations themselves in order to make use of this deconfliction paradigm, and the migration path forward to allow such a capability set to be incorporated by the Department of Commerce’s space traffic coordination system.

Conjunction Assessment↗

Conjunction Assessment and Deconfliction Paradigm for Co-located Satellite Constellations with On-Spacecraft “Autonomous” Flight Dynamics Control

Constellations that employ highly-automated satellite flight dynamics can operate safely from a collision avoidance (CA) perspective using current CA screening technology and communication paradigms—except when in proximity to other highly-automated constellations: there is no existing arrangement and concept of operations to allow the low-latency CA screenings, exchange of information, and assignment/acceptance of mitigation responsibility that co-location of highly-automated constellations requires. However, the serendipitous co-location of the NASA Starling mission—an autonomously-controlled technology demonstration constellation—and the SpaceX Starlink constellation has presented an opportunity (indeed, a requirement) to develop and build out a solution for safe operations of two (or more) co-located, highly-automated satellite constellations. Such a solution has been designed and constructed, including the required ground node; and it will be exercised as a dedicated, in-flight safety experiment between the two constellations from January to September 2024. Lessons learned from this experiment are expected to feed the design of the US Department of Commerce’s Tracking Control System for Space (TraCSS) space traffic coordination solution.

conjunction assessment↗

Space Station user traffic model analysis for mission payload servicing into the twenty-first century

The Space Station-based Customer Servicing Facility service bay requirements for service accommodation to the Initial Orbit Capability (IOC) and far-term Station Accommodation Test Sets (SETS) missions are analyzed using the developed mission traffic model. Analysis results are presented which indicate that one servicing bay will be sufficient to accommodate IOC customer servicing requirements. Growth servicing requirements indicate that an additional servicing bay will be needed for accommodation of the far-term SATS mission payloads. Even though the level of total mission accommodation is below 100 percent for one bay at IOC and two bays during growth operations, the levels are such that operational work-around exists so that additional servicing bays will not be required.

Gould, G. J.↗