Search NASA⌕ Search

SEARCH · Search NASA

Results for “Vehicle detection”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Predicting the Impacts of Intravehicular Displays on Driving Performance with Human Performance Modeling

A challenge facing the U.S. National Highway Traffic Safety Administration (NHTSA), as well as international safety experts, is the need to educate car drivers about the dangers associated with performing distraction tasks while driving. Researchers working for the U.S. Army Research Laboratory have developed a technique for predicting the increase in mental workload that results when distraction tasks are combined with driving. They implement this technique using human performance modeling. They have predicted workload associated with driving combined with cell phone use. In addition, they have predicted the workload associated with driving military vehicles combined with threat detection. Their technique can be used by safety personnel internationally to demonstrate the dangers of combining distracter tasks with driving and to mitigate the safety risks.

Mitchell, Diane Kuhl↗
NASA NTRSDate not supplied

Safety Demonstrator Series for an In-Time Aviation Safety Management System

NASA's Advanced Air Mobility Integration Office has coordinated a meeting with the National Research Council Canada (NRC) to have an interchange of technical area activities to evaluate merit for international partnership. Both NASA and NRC will provide a brief overview of their Advanced Air Mobility activities. Additional aeronautics projects will have an opportunity to present a few slides on current activities and plans. Topics include wildfire, vehicle automation technologies and detect and avoid, and national campaign flight initiatives. NASA's System-Wide Safety (SWS) Project will provide a high-level overview of the the safety demonstrator series. The project has scheduled operational demonstrations of an in-time aviation safety management system across a series of disaster-oriented operations. First up is a wildland fire demonstration scheduled for 2025. Opportunities for synergy will be discussed.

system-wide safety↗
NASA NTRS1991

INS integrated motion analysis for autonomous vehicle navigation

The use of inertial navigation system (INS) measurements to enhance the quality and robustness of motion analysis techniques used for obstacle detection is discussed with particular reference to autonomous vehicle navigation. The approach to obstacle detection used here employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to points within the field of view of the sensor, which can then be used to provide obstacle detection. Results obtained with an INS integrated motion analysis approach are reviewed.

Roberts, Barry↗
NASA NTRS1979

Guidance of an autonomous planetary rover based on a short-range hazard detection system

The guidance of an autonomous planetary roving vehicle using a scanning laser/multidetector terrain sensor for short-range hazard detection has been simulated. The sensor data are used to model the terrain, thereby providing the information required by a path selection algorithm to control the motion of the rover. These simulation studies are providing the basis for developing both the real-time computer control software and the hardware systems for laboratory and field testing of rover.

Yerazunis, S. W.↗
NASA NTRS2011

Wheel-Based Ice Sensors for Road Vehicles

Wheel-based sensors for detection of ice on roads and approximate measurement of the thickness of the ice are under development. These sensors could be used to alert drivers to hazardous local icing conditions in real time. In addition, local ice-thickness measurements by these sensors could serve as guidance for the minimum amount of sand and salt required to be dispensed locally onto road surfaces to ensure safety, thereby helping road crews to utilize their total supplies of sand and salt more efficiently. Like some aircraft wing-surface ice sensors described in a number of previous NASA Tech Briefs articles, the wheelbased ice sensors are based, variously, on measurements of changes in capacitance and/or in radio-frequency impedance as affected by ice on surfaces. In the case of ice on road surfaces, the measurable changes in capacitance and/or impedance are attributable to differences among the electric permittivities of air, ice, water, concrete, and soil. In addition, a related phenomenon that can be useful for distinguishing between ice and water is a specific transition in the permittivity of ice at a temperature- dependent frequency. This feature also provides a continuous calibration of the sensor to allow for changing road conditions. Several configurations of wheel-based ice sensors are under consideration. For example, in a simple two-electrode capacitor configuration, one of the electrodes would be a circumferential electrode within a tire, and the ground would be used as the second electrode. Optionally, the steel belts that are already standard parts of many tires could be used as the circumferential electrodes. In another example (see figure), multiple electrodes would be embedded in rubber between the steel belt and the outer tire surface. These electrodes would be excited in alternating polarities at one or more suitable audio or radio frequencies to provide nearly continuous monitoring of the road surface under the tire. In still another example, one or more microwave stripline(s) or coplanar waveguide(s) would be embedded in a tire near its outer surface; in comparison with lower-frequency capacitive devices, a device of this type could be more sensitive.

Arndt, G. Dickey↗
NASA NTRS1992

Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation

Recent work on INS integrated motion analysis is described. Results were obtained with a maximally passive system of obstacle detection (OD) for ground-based vehicles and rotorcraft. The OD approach involves motion analysis of imagery acquired by a passive sensor in the course of vehicle travel to generate range measurements to world points within the sensor FOV. INS data and scene analysis results are used to enhance interest point selection, the matching of the interest points, and the subsequent motion-based computations, tracking, and OD. The most important lesson learned from the research described here is that the incorporation of inertial data into the motion analysis program greatly improves the analysis and makes the process more robust.

Roberts, Barry↗
NASA NTRS2003

Obstacle detection in foliage with ladar and radar

Autonomous off-road navigation is central to several important applications of unmanned ground vehicles. This requires the ability to detect obstacles in vegetation. We examine the prospects for doing so with scanning ladar and with a linear array of 2.2 GHz micro-impulse radar transceivers. For ladar, we summarize our work to date on algorithms for detecting obstacles in tall grass with single-axis ladar, then present a simple probabilistic model of the distance into tall grass that ladar-based obstacle detection is possible.

ladar↗
NASA NTRS1973

Gradient estimates from stereo measurements for a Martian vehicle

The Martian roving vehicle requires an autonomous obstacle detection and path selection system. A laser range finder will be used to determine the locations of a number of discrete points at distances of 3 to 30 meters from the vehicle. The system might measure angles, ranges or a combination of both types of measurements.

Pfeifer, W. J.↗
NASA NTRS2013

Orion MPCV Touchdown Detection Threshold Development and Testing

A robust method of detecting Orion Multi-Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post-landing segment of the Flight Software (FSW). An in-depth trade study was completed to determine optimal characteristics of the touchdown detection method resulting in an algorithm monitoring filtered, lever-arm corrected, 200 Hz Inertial Measurement Unit (IMU) vehicle acceleration magnitude data against a tunable threshold using persistence counter logic. Following the design of the algorithm, high fidelity environment and vehicle simulations, coupled with the actual vehicle FSW, were used to tune the acceleration threshold and persistence counter value to result in adequate performance in detecting touchdown and sufficient safety margin against early detection while descending under parachutes. An analytical approach including Kriging and adaptive sampling allowed for a sufficient number of finite element analysis (FEA) impact simulations to be completed using minimal computation time. The combination of a persistence counter of 10 and an acceleration threshold of approximately 57.3 ft/s2 resulted in an impact performance factor of safety (FOS) of 1.0 and a safety FOS of approximately 2.6 for touchdown declaration. An RCS termination acceleration threshold of approximately 53.1 ft/s(exp)2 with a persistence counter of 10 resulted in an increased impact performance FOS of 1.2 at the expense of a lowered under-parachutes safety factor of 2.2. The resulting tuned algorithm was then tested on data from eight Capsule Parachute Assembly System (CPAS) flight tests, showing an experimental minimum safety FOS of 6.1. The formulated touchdown detection algorithm will be flown on the Orion MPCV FSW during the Exploration Flight Test 1 (EFT-1) mission in the second half of 2014.

Daum, Jared↗
NASA NTRS1976

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Longendorfer, B. A.↗
NASA NTRS1993

Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

Matthies, Larry↗
NASA NTRS2020

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

… or, “It’s in the details, how to make complicated software perform like complicated hardware.” In attempts to minimize development time and quickly build an operational vehicle, NASA’s Space Launch System (SLS) has had to be intentional about integrated testing. Constraints on budget and schedule have required balance between testing needs and the desire for an integrated flight vehicle as soon as possible. To provide key insights early in design and analysis cycles, a large amount of effort has shifted into maturing and validating models at the component level with integrated testing as a means to validate their integration. In terms of SLS Navigation, this, and the model-based design approach have pushed explicit requirements for sensor models to be validated against flight hardware to high precision. This paper covers the approach taken to verify and validate the models for the two key navigation sensors on the SLS vehicle, the Redundant Inertial Navigation Sensor and the Rate Gyro Assembly. These models are used in performance evaluation, fault detection, and operations development extensively. Using a mix of data from hardware vendor documentation and testing reports, limited in-house testing, and integration activities, these models were able to be validated against flight hardware at multiple levels, from the internal software design to statistical behavior at the raw sensor and integrated box levels. The high level of insight into the hardware elements is instrumental to support flight certification activities and building confidence in SLS Navigation capability. Focused testing enabled additional insight and validation that proved invaluable and the resulting insights were used to focus and mature models. Additionally, of having validated performance-based hardware models enables a wide breadth of activities including detailed fault detection studies and integration into future vehicle frameworks, such as an upper stage and provide a valuable asset to continued SLS analysis and design.

Evan J Anzalone↗
NASA NTRS2020

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

… or, “It’s in the details, how to make complicated software perform like complicated hardware.” In attempts to minimize development time and quickly build an operational vehicle, NASA’s Space Launch System (SLS) has had to be intentional about integrated testing. Constraints on budget and schedule have required balance between testing needs and the desire for an integrated flight vehicle as soon as possible. To provide key insights early in design and analysis cycles, a large amount of effort has shifted into maturing and validating models at the component level with integrated testing as a means to validate their integration. In terms of SLS Navigation, this, and the model-based design approach have pushed explicit requirements for sensor models to be validated against flight hardware to high precision. This paper covers the approach taken to verify and validate the models for the two key navigation sensors on the SLS vehicle, the Redundant Inertial Navigation Sensor and the Rate Gyro Assembly. These models are used in performance evaluation, fault detection, and operations development extensively. Using a mix of data from hardware vendor documentation and testing reports, limited in-house testing, and integration activities, these models were able to be validated against flight hardware at multiple levels, from the internal software design to statistical behavior at the raw sensor and integrated box levels. The high level of insight into the hardware elements is instrumental to support flight certification activities and building confidence in SLS Navigation capability. Focused testing enabled additional insight and validation that proved invaluable and the resulting insights were used to focus and mature models. Additionally, of having validated performance-based hardware models enables a wide breadth of activities including detailed fault detection studies and integration into future vehicle frameworks, such as an upper stage and provide a valuable asset to continued SLS analysis and design.

Thomas Park↗
NASA NTRS1990

Knowledge/geometry-based Mobile Autonomous Robot Simulator (KMARS)

Ongoing applied research is focused on developing guidance system for robot vehicles. Problems facing the basic research needed to support this development (e.g., scene understanding, real-time vision processing, etc.) are major impediments to progress. Due to the complexity and the unpredictable nature of a vehicle's area of operation, more advanced vehicle control systems must be able to learn about obstacles within the range of its sensor(s). A better understanding of the basic exploration process is needed to provide critical support to developers of both sensor systems and intelligent control systems which can be used in a wide spectrum of autonomous vehicles. Elcee Computek, Inc. has been working under contract to the Flight Dynamics Laboratory, Wright Research and Development Center, Wright-Patterson AFB, Ohio to develop a Knowledge/Geometry-based Mobile Autonomous Robot Simulator (KMARS). KMARS has two parts: a geometry base and a knowledge base. The knowledge base part of the system employs the expert-system shell CLIPS ('C' Language Integrated Production System) and necessary rules that control both the vehicle's use of an obstacle detecting sensor and the overall exploration process. The initial phase project has focused on the simulation of a point robot vehicle operating in a 2D environment.

Cheng, Linfu↗
NASA NTRS2016

Towards an Aero-Propulso-Servo-Elasticity Analysis of a Commercial Supersonic Transport

This paper covers the development of an aero-propulso-servo-elastic (APSE) model using computational fluid dynamics (CFD) and linear structural deformations. The APSE model provides the integration of the following two previously developed nonlinear dynamic simulations: a variable cycle turbofan engine and an elastic supersonic commercial transport vehicle. The primary focus of this study is to provide a means to include relevant dynamics of a turbomachinery propulsion system into the aeroelastic studies conducted during a vehicle design, which have historically neglected propulsion effects. A high fidelity CFD tool is used here for the integration platform. The elastic vehicle neglecting the propulsion system serves as a comparison of traditional approaches to the APSE results. An overview of the methodology is presented for integrating the propulsion system and elastic vehicle. Static aeroelastic analysis comparisons between the traditional and developed APSE models for a wing tip detection indicate that the propulsion system impact on the vehicle elastic response could increase the detection by approximately ten percent.

aeroservoelasticity↗
NASA NTRS1996

A Leak Monitor for Industry

GenCorp Aerojet Industrial Products, Lewis Research Center, Marshall Space Flight Center, and Case Western Reserve University developed a gas leak detection system, originally for use with the Space Shuttle propulsion system and reusable launch vehicles. The Model HG200 Automated Gas Leak Detection System has miniaturized sensors that can identify extremely low concentrations of hydrogen without requiring oxygen. A microprocessor-based hardware/software system monitors the sensors and displays the source and magnitude of hydrogen leaks in real time. The system detects trace hydrogen around pipes, connectors, flanges and pressure tanks, and has been used by Ford Motor Company in the production of a natural gas-powered car.

Source record↗
NASA NTRS1975

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

Problems related to an unmanned exploration of the planet Mars by means of an autonomous roving planetary vehicle are investigated. These problems include: design, construction and evaluation of the vehicle itself and its control and operating systems. More specifically, vehicle configuration, dynamics, control, propulsion, hazard detection systems, terrain sensing and modelling, obstacle detection concepts, path selection, decision-making systems, and chemical analyses of samples are studied. Emphasis is placed on development of a vehicle capable of gathering specimens and data for an Augmented Viking Mission or to provide the basis for a Sample Return Mission.

Gisser, D. G.↗
NASA NTRS2003

Parameter Transient Behavior Analysis on Fault Tolerant Control System

In a fault tolerant control (FTC) system, a parameter varying FTC law is reconfigured based on fault parameters estimated by fault detection and isolation (FDI) modules. FDI modules require some time to detect fault occurrences in aero-vehicle dynamics. This paper illustrates analysis of a FTC system based on estimated fault parameter transient behavior which may include false fault detections during a short time interval. Using Lyapunov function analysis, the upper bound of an induced-L2 norm of the FTC system performance is calculated as a function of a fault detection time and the exponential decay rate of the Lyapunov function.

Belcastro, Christine↗