33 CFR 105.260 - Security measures for restricted areas.

Code of Federal Regulations, 2010 CFR

2010-07-01

...; (7) Control the entry, parking, loading and unloading of vehicles; (8) Control the movement and...) Using security personnel, automatic intrusion detection devices, surveillance equipment, or surveillance systems to detect unauthorized entry or movement within restricted areas; (7) Directing the parking...

33 CFR 105.260 - Security measures for restricted areas.

Code of Federal Regulations, 2011 CFR

2011-07-01

...; (7) Control the entry, parking, loading and unloading of vehicles; (8) Control the movement and...) Using security personnel, automatic intrusion detection devices, surveillance equipment, or surveillance systems to detect unauthorized entry or movement within restricted areas; (7) Directing the parking...

Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

NASA Astrophysics Data System (ADS)

Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar

2018-03-01

Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.

Toward detection of marine vehicles on horizon from buoy camera

NASA Astrophysics Data System (ADS)

Fefilatyev, Sergiy; Goldgof, Dmitry B.; Langebrake, Lawrence

2007-10-01

This paper presents a new technique for automatic detection of marine vehicles in open sea from a buoy camera system using computer vision approach. Users of such system include border guards, military, port safety and flow management, sanctuary protection personnel. The system is intended to work autonomously, taking images of the surrounding ocean surface and analyzing them on the subject of presence of marine vehicles. The goal of the system is to detect an approximate window around the ship and prepare the small image for transmission and human evaluation. The proposed computer vision-based algorithm combines horizon detection method with edge detection and post-processing. The dataset of 100 images is used to evaluate the performance of proposed technique. We discuss promising results of ship detection and suggest necessary improvements for achieving better performance.

A video-based real-time adaptive vehicle-counting system for urban roads.

PubMed

Liu, Fei; Zeng, Zhiyuan; Jiang, Rong

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.

A video-based real-time adaptive vehicle-counting system for urban roads

PubMed Central

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios. PMID:29135984

Combating Terrorism Technology Support Office 2006 Review

DTIC Science & Technology

2006-01-01

emplaced beyond the control point, activated manually or automatically , with warning lights and an audible alarm to alert innocent pedestrians. The...throughout a vehicle. When a tamper event is detected, SERVANT automatically records sensor data and surveillance video and sends an alert to the security...exposure to organophosphate nerve agents, botulinum toxin, cyanide, and carbon monoxide and will be packaged into a portable , lightweight, mobile hand

Detection and Classification of Motor Vehicle Noise in a Forested Landscape

NASA Astrophysics Data System (ADS)

Brown, Casey L.; Reed, Sarah E.; Dietz, Matthew S.; Fristrup, Kurt M.

2013-11-01

Noise emanating from human activity has become a common addition to natural soundscapes and has the potential to harm wildlife and erode human enjoyment of nature. In particular, motor vehicles traveling along roads and trails produce high levels of both chronic and intermittent noise, eliciting varied responses from a wide range of animal species. Anthropogenic noise is especially conspicuous in natural areas where ambient background sound levels are low. In this article, we present an acoustic method to detect and analyze motor vehicle noise. Our approach uses inexpensive consumer products to record sound, sound analysis software to automatically detect sound events within continuous recordings and measure their acoustic properties, and statistical classification methods to categorize sound events. We describe an application of this approach to detect motor vehicle noise on paved, gravel, and natural-surface roads, and off-road vehicle trails in 36 sites distributed throughout a national forest in the Sierra Nevada, CA, USA. These low-cost, unobtrusive methods can be used by scientists and managers to detect anthropogenic noise events for many potential applications, including ecological research, transportation and recreation planning, and natural resource management.

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

PubMed

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-02-19

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

PubMed Central

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-01-01

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver’s vigilance level . Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model. PMID:26907278

Detection and enforcement of failure-to-yield in an emergency vehicle preemption system

NASA Technical Reports Server (NTRS)

Bachelder, Aaron (Inventor); Wickline, Richard (Inventor)

2007-01-01

An intersection controlled by an intersection controller receives trigger signals from on-coming emergency vehicles responding to an emergency call. The intersection controller initiates surveillance of the intersection via cameras installed at the intersection in response to a received trigger signal. The surveillance may begin immediately upon receipt of the trigger signal from an emergency vehicle, or may wait until the intersection controller determines that the signaling emergency vehicle is in the field of view of the cameras at the intersection. Portions of the captured images are tagged by the intersection controller based on tag signals transmitted by the vehicle or based on detected traffic patterns that indicate a potential traffic violation. The captured images are downloaded to a processing facility that analyzes the images and automatically issues citations for captured traffic violations.

Automatic detection and counting of cattle in UAV imagery based on machine vision technology (Conference Presentation)

NASA Astrophysics Data System (ADS)

Rahnemoonfar, Maryam; Foster, Jamie; Starek, Michael J.

2017-05-01

Beef production is the main agricultural industry in Texas, and livestock are managed in pasture and rangeland which are usually huge in size, and are not easily accessible by vehicles. The current research method for livestock location identification and counting is visual observation which is very time consuming and costly. For animals on large tracts of land, manned aircraft may be necessary to count animals which is noisy and disturbs the animals, and may introduce a source of error in counts. Such manual approaches are expensive, slow and labor intensive. In this paper we study the combination of small unmanned aerial vehicle (sUAV) and machine vision technology as a valuable solution to manual animal surveying. A fixed-wing UAV fitted with GPS and digital RGB camera for photogrammetry was flown at the Welder Wildlife Foundation in Sinton, TX. Over 600 acres were flown with four UAS flights and individual photographs used to develop orthomosaic imagery. To detect animals in UAV imagery, a fully automatic technique was developed based on spatial and spectral characteristics of objects. This automatic technique can even detect small animals that are partially occluded by bushes. Experimental results in comparison to ground-truth show the effectiveness of our algorithm.

Investigation of Matlab® as platform in navigation and control of an Automatic Guided Vehicle utilising an omnivision sensor.

PubMed

Kotze, Ben; Jordaan, Gerrit

2014-08-25

Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed.

Investigation of Matlab® as Platform in Navigation and Control of an Automatic Guided Vehicle Utilising an Omnivision Sensor

PubMed Central

Kotze, Ben; Jordaan, Gerrit

2014-01-01

Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed. PMID:25157548

Localized contourlet features in vehicle make and model recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, B. S.

2009-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic Number Plate Recognition (ANPR) systems. Several vehicle MMR systems have been proposed in literature. In parallel to this, the usefulness of multi-resolution based feature analysis techniques leading to efficient object classification algorithms have received close attention from the research community. To this effect, Contourlet transforms that can provide an efficient directional multi-resolution image representation has recently been introduced. Already an attempt has been made in literature to use Curvelet/Contourlet transforms in vehicle MMR. In this paper we propose a novel localized feature detection method in Contourlet transform domain that is capable of increasing the classification rates up to 4%, as compared to the previously proposed Contourlet based vehicle MMR approach in which the features are non-localized and thus results in sub-optimal classification. Further we show that the proposed algorithm can achieve the increased classification accuracy of 96% at significantly lower computational complexity due to the use of Two Dimensional Linear Discriminant Analysis (2DLDA) for dimensionality reduction by preserving the features with high between-class variance and low inter-class variance.

Irregular and adaptive sampling for automatic geophysic measure systems

NASA Astrophysics Data System (ADS)

Avagnina, Davide; Lo Presti, Letizia; Mulassano, Paolo

2000-07-01

In this paper a sampling method, based on an irregular and adaptive strategy, is described. It can be used as automatic guide for rovers designed to explore terrestrial and planetary environments. Starting from the hypothesis that a explorative vehicle is equipped with a payload able to acquire measurements of interesting quantities, the method is able to detect objects of interest from measured points and to realize an adaptive sampling, while badly describing the not interesting background.

Automatic localization of backscattering events due to particulate in urban areas

NASA Astrophysics Data System (ADS)

Gaudio, P.; Gelfusa, M.; Malizia, Andrea; Parracino, Stefano; Richetta, M.; Murari, A.; Vega, J.

2014-10-01

Particulate matter (PM), emitted by vehicles in urban traffic, can greatly affect environment air quality and have direct implications on both human health and infrastructure integrity. The consequences for society are relevant and can impact also on national health. Limits and thresholds of pollutants emitted by vehicles are typically regulated by government agencies. In the last few years, the interest in PM emissions has grown substantially due to both air quality issues and global warming. Lidar-Dial techniques are widely recognized as a costeffective alternative to monitor large regions of the atmosphere. To maximize the effectiveness of the measurements and to guarantee reliable, automatic monitoring of large areas, new data analysis techniques are required. In this paper, an original tool, the Universal Multi-Event Locator (UMEL), is applied to the problem of automatically indentifying the time location of peaks in Lidar measurements for the detection of particulate matter emitted by anthropogenic sources like vehicles. The method developed is based on Support Vector Regression and presents various advantages with respect to more traditional techniques. In particular, UMEL is based on the morphological properties of the signals and therefore the method is insensitive to the details of the noise present in the detection system. The approach is also fully general, purely software and can therefore be applied to a large variety of problems without any additional cost. The potential of the proposed technique is exemplified with the help of data acquired during an experimental campaign in the field in Rome.

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

NASA Technical Reports Server (NTRS)

Longendorfer, B. A.

1976-01-01

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.

Day, night and all-weather security surveillance automation synergy from combining two powerful technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morellas, Vassilios; Johnson, Andrew; Johnston, Chris

2006-07-01

Thermal imaging is rightfully a real-world technology proven to bring confidence to daytime, night-time and all weather security surveillance. Automatic image processing intrusion detection algorithms are also a real world technology proven to bring confidence to system surveillance security solutions. Together, day, night and all weather video imagery sensors and automated intrusion detection software systems create the real power to protect early against crime, providing real-time global homeland protection, rather than simply being able to monitor and record activities for post event analysis. These solutions, whether providing automatic security system surveillance at airports (to automatically detect unauthorized aircraft takeoff andmore » landing activities) or at high risk private, public or government facilities (to automatically detect unauthorized people or vehicle intrusion activities) are on the move to provide end users the power to protect people, capital equipment and intellectual property against acts of vandalism and terrorism. As with any technology, infrared sensors and automatic image intrusion detection systems for global homeland security protection have clear technological strengths and limitations compared to other more common day and night vision technologies or more traditional manual man-in-the-loop intrusion detection security systems. This paper addresses these strength and limitation capabilities. False Alarm (FAR) and False Positive Rate (FPR) is an example of some of the key customer system acceptability metrics and Noise Equivalent Temperature Difference (NETD) and Minimum Resolvable Temperature are examples of some of the sensor level performance acceptability metrics. (authors)« less

A Hessian-based methodology for automatic surface crack detection and classification from pavement images

NASA Astrophysics Data System (ADS)

Ghanta, Sindhu; Shahini Shamsabadi, Salar; Dy, Jennifer; Wang, Ming; Birken, Ralf

2015-04-01

Around 3,000,000 million vehicle miles are annually traveled utilizing the US transportation systems alone. In addition to the road traffic safety, maintaining the road infrastructure in a sound condition promotes a more productive and competitive economy. Due to the significant amounts of financial and human resources required to detect surface cracks by visual inspection, detection of these surface defects are often delayed resulting in deferred maintenance operations. This paper introduces an automatic system for acquisition, detection, classification, and evaluation of pavement surface cracks by unsupervised analysis of images collected from a camera mounted on the rear of a moving vehicle. A Hessian-based multi-scale filter has been utilized to detect ridges in these images at various scales. Post-processing on the extracted features has been implemented to produce statistics of length, width, and area covered by cracks, which are crucial for roadway agencies to assess pavement quality. This process has been realized on three sets of roads with different pavement conditions in the city of Brockton, MA. A ground truth dataset labeled manually is made available to evaluate this algorithm and results rendered more than 90% segmentation accuracy demonstrating the feasibility of employing this approach at a larger scale.

Terminal Sliding Mode Tracking Controller Design for Automatic Guided Vehicle

NASA Astrophysics Data System (ADS)

Chen, Hongbin

2018-03-01

Based on sliding mode variable structure control theory, the path tracking problem of automatic guided vehicle is studied, proposed a controller design method based on the terminal sliding mode. First of all, through analyzing the characteristics of the automatic guided vehicle movement, the kinematics model is presented. Then to improve the traditional expression of terminal sliding mode, design a nonlinear sliding mode which the convergence speed is faster than the former, verified by theoretical analysis, the design of sliding mode is steady and fast convergence in the limited time. Finally combining Lyapunov method to design the tracking control law of automatic guided vehicle, the controller can make the automatic guided vehicle track the desired trajectory in the global sense as well as in finite time. The simulation results verify the correctness and effectiveness of the control law.

Speeding response -- saving lives : automatic vehicle location capabilities for emergency vehicles

DOT National Transportation Integrated Search

1999-01-01

This brochure focuses on the application of automatic vehicle location systems to emergency services. It discusses how AVL works with emergency vehicles. how it accommodates a wide range of emergency situations, and the benefits of its use.

The role of looming and attention capture in drivers' braking responses.

PubMed

Terry, Hugh R; Charlton, Samuel G; Perrone, John A

2008-07-01

This study assessed the ability of drivers to detect the deceleration of a preceding vehicle in a simulated vehicle-following task. The size of the preceding vehicles (car, van, or truck) and following speeds (50, 70, or 100 km/h) were systematically varied. Participants selected a preferred following distance by engaging their vehicle's cruise control and when the preceding vehicle began decelerating (no brake lights were illuminated), the participant's braking latency and distances to the lead vehicle were recorded. The experiment also employed a secondary task condition to examine how the attention-capturing properties of a looming vehicle were affected by driver distraction. The results indicated that a looming stimulus is capable of redirecting a driver's attention in a vehicle following task and, as with detection of brake lights, a driver's detection of a looming vehicle is compromised in the presence of a distracting task. Interestingly, increases in vehicle size had the effect of decreasing drivers' braking latencies and drivers engaged in the secondary task were significantly closer to the lead vehicle when they began braking, regardless of the size of the leading vehicle. Performance decrements resulting from the secondary task were reflected in a time-to-collision measure but not in optic expansion rate, lending support to earlier arguments that time-to-collision estimates require explicit cognitive judgements while perception of optic expansion may function in a more automatic fashion to redirect a driver's attention when cognitive resources are low or collision is imminent.

Channel Measurements for Automatic Vehicle Monitoring Systems

DOT National Transportation Integrated Search

1974-03-01

Co-channel and adjacent channel electromagnetic interference measurements were conducted on the Sierra Research Corp. and the Chicago Transit Authority automatic vehicle monitoring systems. These measurements were made to determine if the automatic v...

Exploratory field trial of motorcycle autonomous emergency braking (MAEB): Considerations on the acceptability of unexpected automatic decelerations.

PubMed

Savino, Giovanni; Pierini, Marco; Thompson, Jason; Fitzharris, Michael; Lenné, Michael G

2016-11-16

Autonomous emergency braking (AEB) acts to slow down a vehicle when an unavoidable impending collision is detected. In addition to documented benefits when applied to passenger cars, AEB has also shown potential when applied to motorcycles (MAEB). However, the feasibility of MAEB as practically applied to motorcycles in the real world is not well understood. In this study we performed a field trial involving 16 riders on a test motorcycle subjected to automatic decelerations, thus simulating MAEB activation. The tests were conducted along a rectilinear path at nominal speed of 40 km/h and with mean deceleration of 0.15 g (15% of full braking) deployed at random times. Riders were also exposed to one final undeclared brake activation with the aim of providing genuinely unexpected automatic braking events. Participants were consistently able to manage automatic decelerations of the vehicle with minor to moderate effort. Results of undeclared activations were consistent with those of standard runs. This study demonstrated the feasibility of a moderate automatic deceleration in a scenario of motorcycle travelling in a straight path, supporting the notion that the application of AEB on motorcycles is practicable. Furthermore, the proposed field trial can be used as a reference for future regulation or consumer tests in order to address safety and acceptability of unexpected automatic decelerations on a motorcycle.

Speeding response, saving lives : automatic vehicle location capabilities for emergency services.

DOT National Transportation Integrated Search

1999-01-01

Information from automatic vehicle location systems, when combined with computeraided dispatch software, can provide a rich source of data for analyzing emergency vehicle operations and evaluating agency performance.

On-Board Detection of Pedestrian Intentions

PubMed Central

Fang, Zhijie; Vázquez, David

2017-01-01

Avoiding vehicle-to-pedestrian crashes is a critical requirement for nowadays advanced driver assistant systems (ADAS) and future self-driving vehicles. Accordingly, detecting pedestrians from raw sensor data has a history of more than 15 years of research, with vision playing a central role. During the last years, deep learning has boosted the accuracy of image-based pedestrian detectors. However, detection is just the first step towards answering the core question, namely is the vehicle going to crash with a pedestrian provided preventive actions are not taken? Therefore, knowing as soon as possible if a detected pedestrian has the intention of crossing the road ahead of the vehicle is essential for performing safe and comfortable maneuvers that prevent a crash. However, compared to pedestrian detection, there is relatively little literature on detecting pedestrian intentions. This paper aims to contribute along this line by presenting a new vision-based approach which analyzes the pose of a pedestrian along several frames to determine if he or she is going to enter the road or not. We present experiments showing 750 ms of anticipation for pedestrians crossing the road, which at a typical urban driving speed of 50 km/h can provide 15 additional meters (compared to a pure pedestrian detector) for vehicle automatic reactions or to warn the driver. Moreover, in contrast with state-of-the-art methods, our approach is monocular, neither requiring stereo nor optical flow information. PMID:28946632

Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, Y.; Li, Q.

2017-09-01

Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

Automated Power-Distribution System

NASA Technical Reports Server (NTRS)

Ashworth, Barry; Riedesel, Joel; Myers, Chris; Miller, William; Jones, Ellen F.; Freeman, Kenneth; Walsh, Richard; Walls, Bryan K.; Weeks, David J.; Bechtel, Robert T.

1992-01-01

Autonomous power-distribution system includes power-control equipment and automation equipment. System automatically schedules connection of power to loads and reconfigures itself when it detects fault. Potential terrestrial applications include optimization of consumption of power in homes, power supplies for autonomous land vehicles and vessels, and power supplies for automated industrial processes.

Empirical study on neural network based predictive techniques for automatic number plate recognition

NASA Astrophysics Data System (ADS)

Shashidhara, M. S.; Indrakumar, S. S.

2011-10-01

The objective of this study is to provide an easy, accurate and effective technology for the Bangalore city traffic control. This is based on the techniques of image processing and laser beam technology. The core concept chosen here is an image processing technology by the method of automatic number plate recognition system. First number plate is recognized if any vehicle breaks the traffic rules in the signals. The number is fetched from the database of the RTO office by the process of automatic database fetching. Next this sends the notice and penalty related information to the vehicle owner email-id and an SMS sent to vehicle owner. In this paper, we use of cameras with zooming options & laser beams to get accurate pictures further applied image processing techniques such as Edge detection to understand the vehicle, Identifying the location of the number plate, Identifying the number plate for further use, Plain plate number, Number plate with additional information, Number plates in the different fonts. Accessing the database of the vehicle registration office to identify the name and address and other information of the vehicle number. The updates to be made to the database for the recording of the violation and penalty issues. A feed forward artificial neural network is used for OCR. This procedure is particularly important for glyphs that are visually similar such as '8' and '9' and results in training sets of between 25,000 and 40,000 training samples. Over training of the neural network is prevented by Bayesian regularization. The neural network output value is set to 0.05 when the input is not desired glyph, and 0.95 for correct input.

Phase coherence adaptive processor for automatic signal detection and identification

NASA Astrophysics Data System (ADS)

Wagstaff, Ronald A.

2006-05-01

A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

Introduction To ITS/CVO Participant Manual, Course 1

DOT National Transportation Integrated Search

1999-08-01

WEIGH-IN-MOTION OR WIM, COMMERCIAL VEHICLE INFORMATION SYSTEMS AND NETWORK OR CVISN, AUTOMATIC VEHICLE INDENTIFICATION OR AVI, AUTOMATIC VEHICLE LOCATION OR AVL, ELECTRONIC DATA INTERCHANGE OR EDI, GLOCAL POSITIONING SYSTEM OR GPS, INTERNET OR WORD W...

The Crescent Project : an evaluation of an element of the HELP Program : executive summary

DOT National Transportation Integrated Search

1994-02-01

The HELP/Crescent Project on the West Coast evaluated the applicability of four technologies for screening transponder-equipped vehicles. The technologies included automatic vehicle identification, weigh-in-motion, automatic vehicle classification, a...

Automatic vehicle counting system for traffic monitoring

NASA Astrophysics Data System (ADS)

Crouzil, Alain; Khoudour, Louahdi; Valiere, Paul; Truong Cong, Dung Nghy

2016-09-01

The article is dedicated to the presentation of a vision-based system for road vehicle counting and classification. The system is able to achieve counting with a very good accuracy even in difficult scenarios linked to occlusions and/or presence of shadows. The principle of the system is to use already installed cameras in road networks without any additional calibration procedure. We propose a robust segmentation algorithm that detects foreground pixels corresponding to moving vehicles. First, the approach models each pixel of the background with an adaptive Gaussian distribution. This model is coupled with a motion detection procedure, which allows correctly location of moving vehicles in space and time. The nature of trials carried out, including peak periods and various vehicle types, leads to an increase of occlusions between cars and between cars and trucks. A specific method for severe occlusion detection, based on the notion of solidity, has been carried out and tested. Furthermore, the method developed in this work is capable of managing shadows with high resolution. The related algorithm has been tested and compared to a classical method. Experimental results based on four large datasets show that our method can count and classify vehicles in real time with a high level of performance (>98%) under different environmental situations, thus performing better than the conventional inductive loop detectors.

Denver RTD's computer aided dispatch/automatic vehicle location system : the human factors consequences

DOT National Transportation Integrated Search

1999-09-01

This report documents what happened to employees' work procedures when their employer when their employer installed Computer Aided Disptach/Automatic Vehicle Locator (CAD/AVL) technology to provide real-time surveillance of vehicles and to upgrade ra...

Systems Engineering Approach To Ground Combat Vehicle Survivability In Urban Operations

DTIC Science & Technology

2016-09-01

extinguishing system (AFES), which uses fire wires to detect the presence of fires. The detection of fire automatically triggers the activation of the fire...corresponding wires and connection points also means that it can be more difficult for engineers to integrate distributed architecture systems onto...command signals to the missile via wires trailing behind the missile or via RF signals. See Figure 29 for an illustration of CLOS guidance. Since CLOS

Speeding response, saving lives : automatic vehicle location capabilities for emergency services

DOT National Transportation Integrated Search

1999-01-01

This brochure focuses on the application of automatic vehicle location systems to emergency services. It discusses how AVL works with emergency vehicles and how it accommodates a wide range of emergency situations, and the benefits of ITS use. (3 p.)

Vehicle tracking in wide area motion imagery from an airborne platform

NASA Astrophysics Data System (ADS)

van Eekeren, Adam W. M.; van Huis, Jasper R.; Eendebak, Pieter T.; Baan, Jan

2015-10-01

Airborne platforms, such as UAV's, with Wide Area Motion Imagery (WAMI) sensors can cover multiple square kilometers and produce large amounts of video data. Analyzing all data for information need purposes becomes increasingly labor-intensive for an image analyst. Furthermore, the capacity of the datalink in operational areas may be inadequate to transfer all data to the ground station. Automatic detection and tracking of people and vehicles enables to send only the most relevant footage to the ground station and assists the image analysts in effective data searches. In this paper, we propose a method for detecting and tracking vehicles in high-resolution WAMI images from a moving airborne platform. For the vehicle detection we use a cascaded set of classifiers, using an Adaboost training algorithm on Haar features. This detector works on individual images and therefore does not depend on image motion stabilization. For the vehicle tracking we use a local template matching algorithm. This approach has two advantages. In the first place, it does not depend on image motion stabilization and it counters the inaccuracy of the GPS data that is embedded in the video data. In the second place, it can find matches when the vehicle detector would miss a certain detection. This results in long tracks even when the imagery is of low frame-rate. In order to minimize false detections, we also integrate height information from a 3D reconstruction that is created from the same images. By using the locations of buildings and roads, we are able to filter out false detections and increase the performance of the tracker. In this paper we show that the vehicle tracks can also be used to detect more complex events, such as traffic jams and fast moving vehicles. This enables the image analyst to do a faster and more effective search of the data.

Automatic rapid attachable warhead section

DOEpatents

Trennel, A.J.

1994-05-10

Disclosed are a method and apparatus for automatically selecting warheads or reentry vehicles from a storage area containing a plurality of types of warheads or reentry vehicles, automatically selecting weapon carriers from a storage area containing at least one type of weapon carrier, manipulating and aligning the selected warheads or reentry vehicles and weapon carriers, and automatically coupling the warheads or reentry vehicles with the weapon carriers such that coupling of improperly selected warheads or reentry vehicles with weapon carriers is inhibited. Such inhibition enhances safety of operations and is achieved by a number of means including computer control of the process of selection and coupling and use of connectorless interfaces capable of assuring that improperly selected items will be rejected or rendered inoperable prior to coupling. Also disclosed are a method and apparatus wherein the stated principles pertaining to selection, coupling and inhibition are extended to apply to any item-to-be-carried and any carrying assembly. 10 figures.

Automatic rapid attachable warhead section

DOEpatents

Trennel, Anthony J.

1994-05-10

Disclosed are a method and apparatus for (1) automatically selecting warheads or reentry vehicles from a storage area containing a plurality of types of warheads or reentry vehicles, (2) automatically selecting weapon carriers from a storage area containing at least one type of weapon carrier, (3) manipulating and aligning the selected warheads or reentry vehicles and weapon carriers, and (4) automatically coupling the warheads or reentry vehicles with the weapon carriers such that coupling of improperly selected warheads or reentry vehicles with weapon carriers is inhibited. Such inhibition enhances safety of operations and is achieved by a number of means including computer control of the process of selection and coupling and use of connectorless interfaces capable of assuring that improperly selected items will be rejected or rendered inoperable prior to coupling. Also disclosed are a method and apparatus wherein the stated principles pertaining to selection, coupling and inhibition are extended to apply to any item-to-be-carried and any carrying assembly.

Vehicle tracking for an evasive manoeuvres assistant using low-cost ultrasonic sensors.

PubMed

Jiménez, Felipe; Naranjo, José E; Gómez, Oscar; Anaya, José J

2014-11-28

Many driver assistance systems require knowledge of the vehicle environment. As these systems are increasing in complexity and performance, this knowledge of the environment needs to be more complete and reliable, so sensor fusion combining long, medium and short range sensors is now being used. This paper analyzes the feasibility of using ultrasonic sensors for low cost vehicle-positioning and tracking in the lane adjacent to the host vehicle in order to identify free areas around the vehicle and provide information to an automatic avoidance collision system that can perform autonomous braking and lane change manoeuvres. A laser scanner is used for the early detection of obstacles in the direction of travel while two ultrasonic sensors monitor the blind spot of the host vehicle. The results of tests on a test track demonstrate the ability of these sensors to accurately determine the kinematic variables of the obstacles encountered, despite a clear limitation in range.

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

Evaluation of Particle Counter Technology for Detection of Fuel Contamination Detection Utilizing Fuel System Supply Point

DTIC Science & Technology

2014-06-19

product used as a diesel product for ground use (1). Free water contamination (droplets) may appear as fine droplets or slugs of water in the fuel...methods and test procedures for the calibration and use of automatic particle counters. The transition of this technology to the fuel industry is...UNCLASSIFIED 6 UNCLASSIFIED Receipt Vehicle Fuel Tank Fuel Injector Aviation Fuel DEF (AUST) 5695B 18/16/13 Parker 18

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images

PubMed Central

Ortega-Terol, Damian; Ballesteros, Rocio

2017-01-01

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology. PMID:29036930

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

PubMed

Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

2017-10-15

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

An automatically-shifted two-speed transaxle system for an electric vehicle

NASA Technical Reports Server (NTRS)

Gordon, H. S.; Hassman, G. V.

1980-01-01

An automatic shifting scheme for a two speed transaxle for use with an electric vehicle propulsion system is described. The transaxle system was to be installed in an instrumented laboratory propulsion system of an ac electric vehicle drive train. The transaxle which had been fabricated is also described.

Automatic Fault Recognition of Photovoltaic Modules Based on Statistical Analysis of Uav Thermography

NASA Astrophysics Data System (ADS)

Kim, D.; Youn, J.; Kim, C.

2017-08-01

As a malfunctioning PV (Photovoltaic) cell has a higher temperature than adjacent normal cells, we can detect it easily with a thermal infrared sensor. However, it will be a time-consuming way to inspect large-scale PV power plants by a hand-held thermal infrared sensor. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule based on the mean intensity and standard deviation range was developed to detect defective PV modules from individual array automatically. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97 % or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule.

Aviation Careers Series: Airline Non-Flying Careers

DOT National Transportation Integrated Search

1996-01-01

TRAVLINK demonstrated the use of Automatic Vehicle Location (AVL), ComputerAided dispatch (CAD), and Automatic Vehicle Identification (AVI) systems on Metropolitan Council Transit Operations (MCTO) buses in Minneapolis, Minnesota and western suburbs,...

Analysis and Comparison of Some Automatic Vehicle Monitoring Systems

DOT National Transportation Integrated Search

1973-07-01

In 1970 UMTA solicited proposals and selected four companies to develop systems to demonstrate the feasibility of different automatic vehicle monitoring techniques. The demonstrations culminated in experiments in Philadelphia to assess the performanc...

Crescent Evaluation : appendix D : crescent computer system components evaluation report

DOT National Transportation Integrated Search

1994-02-01

In 1990, Lockheed Integrated Systems Company (LISC) was awarded a contract, under the Crescent Demonstration Project, to demonstrate the integration of Weigh In Motion (WIM), Automatic Vehicle Classification (AVC) and Automatic Vehicle Identification...

On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels.

PubMed

Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho; Kim, Hee-Kang

2018-03-11

Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services.

On the Deployment and Noise Filtering of Vehicular Radar Application for Detection Enhancement in Roads and Tunnels

PubMed Central

Kim, Young-Duk; Son, Guk-Jin; Song, Chan-Ho

2018-01-01

Recently, radar technology has attracted attention for the realization of an intelligent transportation system (ITS) to monitor, track, and manage vehicle traffic on the roads as well as adaptive cruise control (ACC) and automatic emergency braking (AEB) for driving assistance of vehicles. However, when radar is installed on roads or in tunnels, the detection performance is significantly dependent on the deployment conditions and environment around the radar. In particular, in the case of tunnels, the detection accuracy for a moving vehicle drops sharply owing to the diffuse reflection of radio frequency (RF) signals. In this paper, we propose an optimal deployment condition based on height and tilt angle as well as a noise-filtering scheme for RF signals so that the performance of vehicle detection can be robust against external conditions on roads and in tunnels. To this end, first, we gather and analyze the misrecognition patterns of the radar by tracking a number of randomly selected vehicles on real roads. In order to overcome the limitations, we implement a novel road watch module (RWM) that is easily integrated into a conventional radar system such as Delphi ESR. The proposed system is able to perform real-time distributed data processing of the target vehicles by providing independent queues for each object of information that is incoming from the radar RF. Based on experiments with real roads and tunnels, the proposed scheme shows better performance than the conventional method with respect to the detection accuracy and delay time. The implemented system also provides a user-friendly interface to monitor and manage all traffic on roads and in tunnels. This will accelerate the popularization of future ITS services. PMID:29534483

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Assessment of the Denver Regional Transportation District's automatic vehicle location system

DOT National Transportation Integrated Search

2000-08-01

The purpose of this evaluation was to determine how well the Denver Regional Transportation District's (RTD) automatic vehicle location (AVL) system achieved its major objectives of improving scheduling efficiency, improving the ability of dispatcher...

Estimating spatial travel times using automatic vehicle identification data

DOT National Transportation Integrated Search

2001-01-01

Prepared ca. 2001. The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, ...

Roadway weather information system and automatic vehicle location (AVL) coordination.

DOT National Transportation Integrated Search

2011-02-28

Roadway Weather Information System and Automatic Vehicle Location Coordination involves the : development of an Inclement Weather Console that provides a new capability for the state of Oklahoma : to monitor weather-related roadway conditions. The go...

Evaluation of the Monitor-CTA Automatic Vehicle Monitoring System

DOT National Transportation Integrated Search

1974-03-01

In June 1972 the Urban Mass Transportation Administration requested that the Transportation System Center of DOT perform an evaluation of the CTA (Chicago Transit Authority) Monitor-Automatic Vehicle Monitor (AVM) system. TSC planned the overall eval...

Design of a steering stabilizer based on CAN bus

NASA Astrophysics Data System (ADS)

Zhan, Zhaomin; Yan, Yibin

2018-04-01

This design realizes a posture correction device of griping steering wheel based on CAN bus, which is embedded in the steering wheel of vehicles. The system aims to detect the drivers' abnormal griping postures and provides drivers with classification alerts, by combining the recorded griping postures data and the vehicle speed data that are obtained via the CAN bus. The warning information are automatically stored and retained in the device for 12 months. To enhance the alerting effect, the count of this warning message for both the latest month and the last 12 months are displayed on the dashboard panel. In addition to prevent itself from being blocked and self-detect any faults in advance, the appliance also provide a self-test function, which will communicate with the integrated instrument system in vehicle and do simulation test right after the vehicle power on. This appliance can help to urge and ensure drivers to operate the steering wheel correctly, effectively, and timely; prevent some typical incorrect behaviors which commonly happen along with the change of griping postures, such as the using cellphone, and ultimately, reduce the incidence of traffic accidents.

Information processing requirements for on-board monitoring of automatic landing

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Karmarkar, J. S.

1977-01-01

A systematic procedure is presented for determining the information processing requirements for on-board monitoring of automatic landing systems. The monitoring system detects landing anomalies through use of appropriate statistical tests. The time-to-correct aircraft perturbations is determined from covariance analyses using a sequence of suitable aircraft/autoland/pilot models. The covariance results are used to establish landing safety and a fault recovery operating envelope via an event outcome tree. This procedure is demonstrated with examples using the NASA Terminal Configured Vehicle (B-737 aircraft). The procedure can also be used to define decision height, assess monitoring implementation requirements, and evaluate alternate autoland configurations.

Evaluation of Automatic Vehicle Location accuracy

DOT National Transportation Integrated Search

1999-01-01

This study assesses the accuracy of the Automatic Vehicle Location (AVL) data provided for the buses of the Ann Arbor Transportation Authority with Global Positioning System (GPS) technology. In a sample of eighty-nine bus trips two kinds of accuracy...

Roadway system assessment using bluetooth-based automatic vehicle identification travel time data.

DOT National Transportation Integrated Search

2012-12-01

This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection : systems. This includes considerations in the physical setup of the collection system as well as the interpretation of...

Socioeconomic Impact Assessment of the Los Angeles Automatic Vehicle Monitoring (AVM) Demonstration

DOT National Transportation Integrated Search

1982-09-01

This report presents a socioeconomic impact assessment of the Automatic Vehicle Monitoring (AVM) Demonstration in Los Angeles. An AVM system uses location, communication, and data processing subsystems to monitor the locations of appropriately equipp...

Understanding ITS/CVO Technology Applications, Student Manual, Course 3

DOT National Transportation Integrated Search

1999-01-01

WEIGHT-IN-MOTION OR WIM, COMMERCIAL VEHICLE INFORMATION SYSTEMS AND NETWORK OR CVISN, AUTOMATIC VEHICLE IDENTIFICATION OR AVI, AUTOMATIC LOCATION OR AVL, ELECTRONIC DATA INTERCHANGE OR EDI, GLOBAL POSITIONING SYSTEM OR GPS, INTERNET OR WORLD WIDE WEB...

Towards the Automatic Detection of Pre-Existing Termite Mounds through UAS and Hyperspectral Imagery.

PubMed

Sandino, Juan; Wooler, Adam; Gonzalez, Felipe

2017-09-24

The increased technological developments in Unmanned Aerial Vehicles (UAVs) combined with artificial intelligence and Machine Learning (ML) approaches have opened the possibility of remote sensing of extensive areas of arid lands. In this paper, a novel approach towards the detection of termite mounds with the use of a UAV, hyperspectral imagery, ML and digital image processing is intended. A new pipeline process is proposed to detect termite mounds automatically and to reduce, consequently, detection times. For the classification stage, several ML classification algorithms' outcomes were studied, selecting support vector machines as the best approach for their role in image classification of pre-existing termite mounds. Various test conditions were applied to the proposed algorithm, obtaining an overall accuracy of 68%. Images with satisfactory mound detection proved that the method is "resolution-dependent". These mounds were detected regardless of their rotation and position in the aerial image. However, image distortion reduced the number of detected mounds due to the inclusion of a shape analysis method in the object detection phase, and image resolution is still determinant to obtain accurate results. Hyperspectral imagery demonstrated better capabilities to classify a huge set of materials than implementing traditional segmentation methods on RGB images only.

Vehicle Tracking for an Evasive Manoeuvres Assistant Using Low-Cost Ultrasonic Sensors

PubMed Central

Jiménez, Felipe; Naranjo, José E.; Gómez, Oscar; Anaya, José J.

2014-01-01

Many driver assistance systems require knowledge of the vehicle environment. As these systems are increasing in complexity and performance, this knowledge of the environment needs to be more complete and reliable, so sensor fusion combining long, medium and short range sensors is now being used. This paper analyzes the feasibility of using ultrasonic sensors for low cost vehicle-positioning and tracking in the lane adjacent to the host vehicle in order to identify free areas around the vehicle and provide information to an automatic avoidance collision system that can perform autonomous braking and lane change manoeuvres. A laser scanner is used for the early detection of obstacles in the direction of travel while two ultrasonic sensors monitor the blind spot of the host vehicle. The results of tests on a test track demonstrate the ability of these sensors to accurately determine the kinematic variables of the obstacles encountered, despite a clear limitation in range. PMID:25460817

Pc-based car license plate reading

NASA Astrophysics Data System (ADS)

Tanabe, Katsuyoshi; Marubayashi, Eisaku; Kawashima, Harumi; Nakanishi, Tadashi; Shio, Akio

1994-03-01

A PC-based car license plate recognition system has been developed. The system recognizes Chinese characters and Japanese phonetic hiragana characters as well as six digits on Japanese license plates. The system consists of a CCD camera, vehicle sensors, a strobe unit, a monitoring center, and an i486-based PC. The PC includes in its extension slots: a vehicle detector board, a strobe emitter board, and an image grabber board. When a passing vehicle is detected by the vehicle sensors, the strobe emits a pulse of light. The light pulse is synchronized with the time the vehicle image is frozen on an image grabber board. The recognition process is composed of three steps: image thresholding, character region extraction, and matching-based character recognition. The recognition software can handle obscured characters. Experimental results for hundreds of outdoor images showed high recognition performance within relatively short performance times. The results confirmed that the system is applicable to a wide variety of applications such as automatic vehicle identification and travel time measurement.

Two-dimensional statistical linear discriminant analysis for real-time robust vehicle-type recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, S.; Bez, H. E.

2007-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic License Plate Recognition (ALPR) systems. Several car MMR systems have been proposed in literature. However these approaches are based on feature detection algorithms that can perform sub-optimally under adverse lighting and/or occlusion conditions. In this paper we propose a real time, appearance based, car MMR approach using Two Dimensional Linear Discriminant Analysis that is capable of addressing this limitation. We provide experimental results to analyse the proposed algorithm's robustness under varying illumination and occlusions conditions. We have shown that the best performance with the proposed 2D-LDA based car MMR approach is obtained when the eigenvectors of lower significance are ignored. For the given database of 200 car images of 25 different make-model classifications, a best accuracy of 91% was obtained with the 2D-LDA approach. We use a direct Principle Component Analysis (PCA) based approach as a benchmark to compare and contrast the performance of the proposed 2D-LDA approach to car MMR. We conclude that in general the 2D-LDA based algorithm supersedes the performance of the PCA based approach.

Loran Automatic Vehicle Monitoring System, Phase I : Volume 2. Appendices.

DOT National Transportation Integrated Search

1977-08-01

Presents results of the evaluation phase of a two phase program to develop an Automatic Vehicle Monitoring (AVM) system for the Southern California Rapid Transit District in Los Angeles, California. Tests were previously conducted on a Loran based lo...

Experiments on Four Different Techniques for Automatically Locating Land Vehicles - A Summary of Results

DOT National Transportation Integrated Search

1977-06-01

In 1975, to further the development and to refine and dmonstrate multiuser Automatic Vehicle Monitoring (AVM) application, the Urban Mass Transportation Administration and the Transportation Systems Center (TSC) initiated a two-phase program. Phase I...

Remotely piloted vehicles. Citations from the International Aerospace abstracts data base

NASA Technical Reports Server (NTRS)

Mauk, S. C.

1980-01-01

These citations from the international literature cover various aspects of remotely piloted vehicles. Included are articles concerning aircraft design, flight tests, aircraft control, cost effectiveness, automatic flight control, automatic pilots, and data links. Civil aviation applications are included, although military uses of remotely piloted vehicles are stressed. This updated bibliography contains 224 citations, 43 of which are new additions to the previous edition.

Report on Phase 1 Tests of Fairchild Automatic Vehicle Monitoring (AVM) System

DOT National Transportation Integrated Search

1977-08-01

During the winter of 1976-77 four different techniques for automatically locating land vehicles were tested in both the low and high-rise regions in Philadelphia, Pennsylvania. The tests were carried out by four different companies under separate con...

Loran Automatic Vehicle Monitoring System, Phase I : Volume 1. Test Results.

DOT National Transportation Integrated Search

1977-08-01

Presents results of the evaluation phase of a two phase program to develop an Automatic Vehicle Monitoring (AVM) system for the Southern California Rapid Transit District in Los Angeles, California. Tests were previously conducted on a Loran based lo...

Modern Control Aspects of Automatically Steered Vehicles

DOT National Transportation Integrated Search

1971-12-01

In the study of automatically steered rubber tired vehicles, little emphasis in the past has been placed on the steering control laws. The report examines the control law problem from the state variable point of view and it is shown that, except for ...

Multibody simulation of vehicles equipped with an automatic transmission

NASA Astrophysics Data System (ADS)

Olivier, B.; Kouroussis, G.

2016-09-01

Nowadays automotive vehicles remain as one of the most used modes of transportation. Furthermore automatic transmissions are increasingly used to provide a better driving comfort and a potential optimization of the engine performances (by placing the gear shifts at specific engine and vehicle speeds). This paper presents an effective modeling of the vehicle using the multibody methodology (numerically computed under EasyDyn, an open source and in-house library dedicated to multibody simulations). However, the transmission part of the vehicle is described by the usual equations of motion computed using a systematic matrix approach: del Castillo's methodology for planetary gear trains. By coupling the analytic equations of the transmission and the equations computed by the multibody methodology, the performances of any vehicle can be obtained if the characteristics of each element in the vehicle are known. The multibody methodology offers the possibilities to develop the vehicle modeling from 1D-motion to 3D-motion by taking into account the rotations and implementing tire models. The modeling presented in this paper remains very efficient and provides an easy and quick vehicle simulation tool which could be used in order to calibrate the automatic transmission.

Autonomous Docking Based on Infrared System for Electric Vehicle Charging in Urban Areas

PubMed Central

Pérez, Joshué; Nashashibi, Fawzi; Lefaudeux, Benjamin; Resende, Paulo; Pollard, Evangeline

2013-01-01

Electric vehicles are progressively introduced in urban areas, because of their ability to reduce air pollution, fuel consumption and noise nuisance. Nowadays, some big cities are launching the first electric car-sharing projects to clear traffic jams and enhance urban mobility, as an alternative to the classic public transportation systems. However, there are still some problems to be solved related to energy storage, electric charging and autonomy. In this paper, we present an autonomous docking system for electric vehicles recharging based on an embarked infrared camera performing infrared beacons detection installed in the infrastructure. A visual servoing system coupled with an automatic controller allows the vehicle to dock accurately to the recharging booth in a street parking area. The results show good behavior of the implemented system, which is currently deployed as a real prototype system in the city of Paris. PMID:23429581

Autonomous docking based on infrared system for electric vehicle charging in urban areas.

PubMed

Pérez, Joshué; Nashashibi, Fawzi; Lefaudeux, Benjamin; Resende, Paulo; Pollard, Evangeline

2013-02-21

Electric vehicles are progressively introduced in urban areas, because of their ability to reduce air pollution, fuel consumption and noise nuisance. Nowadays, some big cities are launching the first electric car-sharing projects to clear traffic jams and enhance urban mobility, as an alternative to the classic public transportation systems. However, there are still some problems to be solved related to energy storage, electric charging and autonomy. In this paper, we present an autonomous docking system for electric vehicles recharging based on an embarked infrared camera performing infrared beacons detection installed in the infrastructure. A visual servoing system coupled with an automatic controller allows the vehicle to dock accurately to the recharging booth in a street parking area. The results show good behavior of the implemented system, which is currently deployed as a real prototype system in the city of Paris.

A discrete optimization approach for locating automatic vehicle identification readers for the provision of roadway travel times

DOT National Transportation Integrated Search

2002-11-01

This paper develops an algorithm for optimally locating surveillance technologies with an emphasis on Automatic Vehicle Identification tag readers by maximizing the benefit that would accrue from measuring travel times on a transportation network. Th...

Night vision: requirements and possible roadmap for FIR and NIR systems

NASA Astrophysics Data System (ADS)

Källhammer, Jan-Erik

2006-04-01

A night vision system must increase visibility in situations where only low beam headlights can be used today. As pedestrians and animals have the highest risk increase in night time traffic due to darkness, the ability of detecting those objects should be the main performance criteria, and the system must remain effective when facing the headlights of oncoming vehicles. Far infrared system has been shown to be superior to near infrared system in terms of pedestrian detection distance. Near infrared images were rated to have significantly higher visual clutter compared with far infrared images. Visual clutter has been shown to correlate with reduction in detection distance of pedestrians. Far infrared images are perceived as being more unusual and therefore more difficult to interpret, although the image appearance is likely related to the lower visual clutter. However, the main issue comparing the two technologies should be how well they solve the driver's problem with insufficient visibility under low beam conditions, especially of pedestrians and other vulnerable road users. With the addition of an automatic detection aid, a main issue will be whether the advantage of FIR systems will vanish given NIR systems with well performing automatic pedestrian detection functionality. The first night vision introductions did not generate the sales volumes initially expected. A renewed interest in night vision systems are however to be expected after the release of night vision systems by BMW, Mercedes and Honda, the latter with automatic pedestrian detection.

Automatic vehicle counting using background subtraction method on gray scale images and morphology operation

NASA Astrophysics Data System (ADS)

Adi, K.; Widodo, A. P.; Widodo, C. E.; Pamungkas, A.; Putranto, A. B.

2018-05-01

Traffic monitoring on road needs to be done, the counting of the number of vehicles passing the road is necessary. It is more emphasized for highway transportation management in order to prevent efforts. Therefore, it is necessary to develop a system that is able to counting the number of vehicles automatically. Video processing method is able to counting the number of vehicles automatically. This research has development a system of vehicle counting on toll road. This system includes processes of video acquisition, frame extraction, and image processing for each frame. Video acquisition is conducted in the morning, at noon, in the afternoon, and in the evening. This system employs of background subtraction and morphology methods on gray scale images for vehicle counting. The best vehicle counting results were obtained in the morning with a counting accuracy of 86.36 %, whereas the lowest accuracy was in the evening, at 21.43 %. Differences in morning and evening results are caused by different illumination in the morning and evening. This will cause the values in the image pixels to be different.

Automatic voltage imbalance detector

DOEpatents

Bobbett, Ronald E.; McCormick, J. Byron; Kerwin, William J.

1984-01-01

A device for indicating and preventing damage to voltage cells such as galvanic cells and fuel cells connected in series by detecting sequential voltages and comparing these voltages to adjacent voltage cells. The device is implemented by using operational amplifiers and switching circuitry is provided by transistors. The device can be utilized in battery powered electric vehicles to prevent galvanic cell damage and also in series connected fuel cells to prevent fuel cell damage.

Real-time road detection in infrared imagery

NASA Astrophysics Data System (ADS)

Andre, Haritini E.; McCoy, Keith

1990-09-01

Automatic road detection is an important part in many scene recognition applications. The extraction of roads provides a means of navigation and position update for remotely piloted vehicles or autonomous vehicles. Roads supply strong contextual information which can be used to improve the performance of automatic target recognition (ATh) systems by directing the search for targets and adjusting target classification confidences. This paper will describe algorithmic techniques for labeling roads in high-resolution infrared imagery. In addition, realtime implementation of this structural approach using a processor array based on the Martin Marietta Geometric Arithmetic Parallel Processor (GAPPTh) chip will be addressed. The algorithm described is based on the hypothesis that a road consists of pairs of line segments separated by a distance "d" with opposite gradient directions (antiparallel). The general nature of the algorithm, in addition to its parallel implementation in a single instruction, multiple data (SIMD) machine, are improvements to existing work. The algorithm seeks to identify line segments meeting the road hypothesis in a manner that performs well, even when the side of the road is fragmented due to occlusion or intersections. The use of geometrical relationships between line segments is a powerful yet flexible method of road classification which is independent of orientation. In addition, this approach can be used to nominate other types of objects with minor parametric changes.

Retarding potential analyzer for the Pioneer-Venus Orbiter Mission

NASA Technical Reports Server (NTRS)

Knudsen, W. C.; Bakke, J.; Spenner, K.; Novak, V.

1979-01-01

The retarding potential analyzer on the Pioneer-Venus Orbiter Mission has been designed to measure most of the thermal plasma parameters within and near the Venusian ionosphere. Parameters include total ion concentration, concentrations of the more abundant ions, ion temperatures, ion drift velocity, electron temperature, and low-energy (0-50 eV) electron distribution function. To accomplish these measurements on a spinning vehicle with a small telemetry bit rate, several functions, including decision functions not previously used in RPA's, have been developed and incorporated into this instrument. The more significant functions include automatic electrometer ranging with background current compensation; digital, quadratic retarding potential step generation for the ion and low-energy electron scans; a current sampling interval of 2 ms throughout all scans; digital logic inflection point detection and data selection; and automatic ram direction detection. Extensive numerical simulation and plasma chamber tests have been conducted to verify adequacy of the design for the Pioneer Mission.

Parametric Testing of Launch Vehicle FDDR Models

NASA Technical Reports Server (NTRS)

Schumann, Johann; Bajwa, Anupa; Berg, Peter; Thirumalainambi, Rajkumar

2011-01-01

For the safe operation of a complex system like a (manned) launch vehicle, real-time information about the state of the system and potential faults is extremely important. The on-board FDDR (Failure Detection, Diagnostics, and Response) system is a software system to detect and identify failures, provide real-time diagnostics, and to initiate fault recovery and mitigation. The ERIS (Evaluation of Rocket Integrated Subsystems) failure simulation is a unified Matlab/Simulink model of the Ares I Launch Vehicle with modular, hierarchical subsystems and components. With this model, the nominal flight performance characteristics can be studied. Additionally, failures can be injected to see their effects on vehicle state and on vehicle behavior. A comprehensive test and analysis of such a complicated model is virtually impossible. In this paper, we will describe, how parametric testing (PT) can be used to support testing and analysis of the ERIS failure simulation. PT uses a combination of Monte Carlo techniques with n-factor combinatorial exploration to generate a small, yet comprehensive set of parameters for the test runs. For the analysis of the high-dimensional simulation data, we are using multivariate clustering to automatically find structure in this high-dimensional data space. Our tools can generate detailed HTML reports that facilitate the analysis.

Lessons learned from a pilot project of an automatic vehicle location system in an urban winter maintenance operations setting.

DOT National Transportation Integrated Search

2002-01-01

This report documents the lessons learned during the evolution of the Virginia Department of Transportation's pilot project to use an automatic vehicle location (AVL) system during winter maintenance operations in an urban setting. AVL is a technolog...

Bridge damage detection using spatiotemporal patterns extracted from dense sensor network

NASA Astrophysics Data System (ADS)

Liu, Chao; Gong, Yongqiang; Laflamme, Simon; Phares, Brent; Sarkar, Soumik

2017-01-01

The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. With the advent of ubiquitous sensing and communication capabilities, scalable data-driven approaches is of great interest, as it can utilize large volume of streaming data without requiring detailed physical models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is proposed to explore spatiotemporal behaviors in a bridge network. Data from strain gauges installed on two bridges are generated using finite element simulation for three types of sensor networks from a density perspective (dense, nominal, sparse). Causal relationships among spatially distributed strain data streams are extracted and analyzed for vehicle identification and detection, and for localization of structural degradation in bridges. Multiple case studies show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, (iii) detecting and localizing damage via comparison of bridge responses to similar vehicle loads, and (iv) implementing real-time health monitoring and decision making work flow for bridge networks. Also, the results demonstrate increased sensitivity in detecting damages and higher reliability in quantifying the damage level with increase in sensor network density.

Automatic circuit interrupter

NASA Technical Reports Server (NTRS)

Dwinell, W. S.

1979-01-01

In technique, voice circuits connecting crew's cabin to launch station through umbilical connector disconnect automatically unused, or deadened portion of circuits immediately after vehicle is launched, eliminating possibility that unused wiring interferes with voice communications inside vehicle or need for manual cutoff switch and its associated wiring. Technique is applied to other types of electrical actuation circuits, also launch of mapped vehicles, such as balloons, submarines, test sleds, and test chambers-all requiring assistance of ground crew.

Automatic Control of Personal Rapid Transit Vehicles

NASA Technical Reports Server (NTRS)

Smith, P. D.

1972-01-01

The requirements for automatic longitudinal control of a string of closely packed personal vehicles are outlined. Optimal control theory is used to design feedback controllers for strings of vehicles. An important modification of the usual optimal control scheme is the inclusion of jerk in the cost functional. While the inclusion of the jerk term was considered, the effect of its inclusion was not sufficiently studied. Adding the jerk term will increase passenger comfort.

Automatic vehicle monitoring systems study. Report of phase O. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1977-01-01

A set of planning guidelines is presented to help law enforcement agencies and vehicle fleet operators decide which automatic vehicle monitoring (AVM) system could best meet their performance requirements. Improvements in emergency response times and resultant cost benefits obtainable with various operational and planned AVM systems may be synthesized and simulated by means of special computer programs for model city parameters applicable to small, medium, and large urban areas. Design characteristics of various AVM systems and the implementation requirements are illustrated and cost estimated for the vehicles, the fixed sites, and the base equipments. Vehicle location accuracies for different RF links and polling intervals are analyzed.

Power-based Shift Schedule for Pure Electric Vehicle with a Two-speed Automatic Transmission

NASA Astrophysics Data System (ADS)

Wang, Jiaqi; Liu, Yanfang; Liu, Qiang; Xu, Xiangyang

2016-11-01

This paper introduces a comprehensive shift schedule for a two-speed automatic transmission of pure electric vehicle. Considering about driving ability and efficiency performance of electric vehicles, the power-based shift schedule is proposed with three principles. This comprehensive shift schedule regards the vehicle current speed and motor load power as input parameters to satisfy the vehicle driving power demand with lowest energy consumption. A simulation model has been established to verify the dynamic and economic performance of comprehensive shift schedule. Compared with traditional dynamic and economic shift schedules, simulation results indicate that the power-based shift schedule is superior to traditional shift schedules.

Automatic detection of zebra crossings from mobile LiDAR data

NASA Astrophysics Data System (ADS)

Riveiro, B.; González-Jorge, H.; Martínez-Sánchez, J.; Díaz-Vilariño, L.; Arias, P.

2015-07-01

An algorithm for the automatic detection of zebra crossings from mobile LiDAR data is developed and tested to be applied for road management purposes. The algorithm consists of several subsequent processes starting with road segmentation by performing a curvature analysis for each laser cycle. Then, intensity images are created from the point cloud using rasterization techniques, in order to detect zebra crossing using the Standard Hough Transform and logical constrains. To optimize the results, image processing algorithms are applied to the intensity images from the point cloud. These algorithms include binarization to separate the painting area from the rest of the pavement, median filtering to avoid noisy points, and mathematical morphology to fill the gaps between the pixels in the border of white marks. Once the road marking is detected, its position is calculated. This information is valuable for inventorying purposes of road managers that use Geographic Information Systems. The performance of the algorithm has been evaluated over several mobile LiDAR strips accounting for a total of 30 zebra crossings. That test showed a completeness of 83%. Non-detected marks mainly come from painting deterioration of the zebra crossing or by occlusions in the point cloud produced by other vehicles on the road.

Automatic Mechetronic Wheel Light Device

DOEpatents

Khan, Mohammed John Fitzgerald

2004-09-14

A wheel lighting device for illuminating a wheel of a vehicle to increase safety and enhance aesthetics. The device produces the appearance of a "ring of light" on a vehicle's wheels as the vehicle moves. The "ring of light" can automatically change in color and/or brightness according to a vehicle's speed, acceleration, jerk, selection of transmission gears, and/or engine speed. The device provides auxiliary indicator lights by producing light in conjunction with a vehicle's turn signals, hazard lights, alarm systems, and etc. The device comprises a combination of mechanical and electronic components and can be placed on the outer or inner surface of a wheel or made integral to a wheel or wheel cover. The device can be configured for all vehicle types, and is electrically powered by a vehicle's electrical system and/or battery.

System and method for charging a plug-in electric vehicle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bassham, Marjorie A.; Spigno, Jr., Ciro A.; Muller, Brett T.

2017-05-02

A charging system and method that may be used to automatically apply customized charging settings to a plug-in electric vehicle, where application of the settings is based on the vehicle's location. According to an exemplary embodiment, a user may establish and save a separate charging profile with certain customized charging settings for each geographic location where they plan to charge their plug-in electric vehicle. Whenever the plug-in electric vehicle enters a new geographic area, the charging method may automatically apply the charging profile that corresponds to that area. Thus, the user does not have to manually change or manipulate themore » charging settings every time they charge the plug-in electric vehicle in a new location.« less

Automatic exposure control for space sequential camera

NASA Technical Reports Server (NTRS)

Mcatee, G. E., Jr.; Stoap, L. J.; Solheim, C. D.; Sharpsteen, J. T.

1975-01-01

The final report for the automatic exposure control study for space sequential cameras, for the NASA Johnson Space Center is presented. The material is shown in the same sequence that the work was performed. The purpose of the automatic exposure control is to automatically control the lens iris as well as the camera shutter so that the subject is properly exposed on the film. A study of design approaches is presented. Analysis of the light range of the spectrum covered indicates that the practical range would be from approximately 20 to 6,000 foot-lamberts, or about nine f-stops. Observation of film available from space flights shows that optimum scene illumination is apparently not present in vehicle interior photography as well as in vehicle-to-vehicle situations. The evaluation test procedure for a breadboard, and the results, which provided information for the design of a brassboard are given.

An object detection and tracking system for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Yang, Jian; Xiao, Yang; Fang, Zhiwen; Zhang, Naiwen; Wang, Li; Li, Tao

2017-10-01

Object detection and tracking are critical parts of unmanned surface vehicles(USV) to achieve automatic obstacle avoidance. Off-the-shelf object detection methods have achieved impressive accuracy in public datasets, though they still meet bottlenecks in practice, such as high time consumption and low detection quality. In this paper, we propose a novel system for USV, which is able to locate the object more accurately while being fast and stable simultaneously. Firstly, we employ Faster R-CNN to acquire several initial raw bounding boxes. Secondly, the image is segmented to a few superpixels. For each initial box, the superpixels inside will be grouped into a whole according to a combination strategy, and a new box is thereafter generated as the circumscribed bounding box of the final superpixel. Thirdly, we utilize KCF to track these objects after several frames, Faster-RCNN is again used to re-detect objects inside tracked boxes to prevent tracking failure as well as remove empty boxes. Finally, we utilize Faster R-CNN to detect objects in the next image, and refine object boxes by repeating the second module of our system. The experimental results demonstrate that our system is fast, robust and accurate, which can be applied to USV in practice.

Experience of the ARGO autonomous vehicle

NASA Astrophysics Data System (ADS)

Bertozzi, Massimo; Broggi, Alberto; Conte, Gianni; Fascioli, Alessandra

1998-07-01

This paper presents and discusses the first results obtained by the GOLD (Generic Obstacle and Lane Detection) system as an automatic driver of ARGO. ARGO is a Lancia Thema passenger car equipped with a vision-based system that allows to extract road and environmental information from the acquired scene. By means of stereo vision, obstacles on the road are detected and localized, while the processing of a single monocular image allows to extract the road geometry in front of the vehicle. The generality of the underlying approach allows to detect generic obstacles (without constraints on shape, color, or symmetry) and to detect lane markings even in dark and in strong shadow conditions. The hardware system consists of a PC Pentium 200 Mhz with MMX technology and a frame-grabber board able to acquire 3 b/w images simultaneously; the result of the processing (position of obstacles and geometry of the road) is used to drive an actuator on the steering wheel, while debug information are presented to the user on an on-board monitor and a led-based control panel.

Robotic vehicle uses acoustic sensors for voice detection and diagnostics

NASA Astrophysics Data System (ADS)

Young, Stuart H.; Scanlon, Michael V.

2000-07-01

An acoustic sensor array that cues an imaging system on a small tele- operated robotic vehicle was used to detect human voice and activity inside a building. The advantage of acoustic sensors is that it is a non-line of sight (NLOS) sensing technology that can augment traditional LOS sensors such as visible and IR cameras. Acoustic energy emitted from a target, such as from a person, weapon, or radio, will travel through walls and smoke, around corners, and down corridors, whereas these obstructions would cripple an imaging detection system. The hardware developed and tested used an array of eight microphones to detect the loudest direction and automatically setter a camera's pan/tilt toward the noise centroid. This type of system has applicability for counter sniper applications, building clearing, and search/rescue. Data presented will be time-frequency representations showing voice detected within rooms and down hallways at various ranges. Another benefit of acoustics is that it provides the tele-operator some situational awareness clues via low-bandwidth transmission of raw audio data for the operator to interpret with either headphones or through time-frequency analysis. This data can be useful to recognize familiar sounds that might indicate the presence of personnel, such as talking, equipment, movement noise, etc. The same array also detects the sounds of the robot it is mounted on, and can be useful for engine diagnostics and trouble shooting, or for self-noise emanations for stealthy travel. Data presented will characterize vehicle self noise over various surfaces such as tiles, carpets, pavement, sidewalk, and grass. Vehicle diagnostic sounds will indicate a slipping clutch and repeated unexpected application of emergency braking mechanism.

An overload behavior detection system for engineering transport vehicles based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Libo; Wu, Gang

2018-04-01

This paper builds an overloaded truck detect system called ITMD to help traffic department automatically identify the engineering transport vehicles (commonly known as `dirt truck') in CCTV and determine whether the truck is overloaded or not. We build the ITMD system based on the Single Shot MultiBox Detector (SSD) model. By constructing the image dataset of the truck and adjusting hyper-parameters of the original SSD neural network, we successfully trained a basic network model which the ITMD system depends on. The basic ITMD system achieves 83.01% mAP on classifying overload/non-overload truck, which is a not bad result. Still, some shortcomings of basic ITMD system have been targeted to enhance: it is easy for the ITMD system to misclassify other similar vehicle as truck. In response to this problem, we optimized the basic ITMD system, which effectively reduced basic model's false recognition rate. The optimized ITMD system achieved 86.18% mAP on the test set, which is better than the 83.01% mAP of the basic ITMD system.

Global Positioning System Synchronized Active Light Autonomous Docking System

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor); Bell, Joseph L. (Inventor)

1996-01-01

A Global Positioning System Synchronized Active Light Autonomous Docking System (GPSSALADS) for automatically docking a chase vehicle with a target vehicle comprising at least one active light emitting target which is operatively attached to the target vehicle. The target includes a three-dimensional array of concomitantly flashing lights which flash at a controlled common frequency. The GPSSALADS further comprises a visual tracking sensor operatively attached to the chase vehicle for detecting and tracking the target vehicle. Its performance is synchronized with the flash frequency of the lights by a synchronization means which is comprised of first and second internal clocks operatively connected to the active light target and visual tracking sensor, respectively, for providing timing control signals thereto, respectively. The synchronization means further includes first and second Global Positioning System receivers operatively connected to the first and second internal clocks, respectively, for repeatedly providing simultaneous synchronization pulses to the internal clocks, respectively. In addition, the GPSSALADS includes a docking process controller means which is operatively attached to the chase vehicle and is responsive to the visual tracking sensor for producing commands for the guidance and propulsion system of the chase vehicle.

Global Positioning System Synchronized Active Light Autonomous Docking System

NASA Technical Reports Server (NTRS)

Howard, Richard (Inventor)

1994-01-01

A Global Positioning System Synchronized Active Light Autonomous Docking System (GPSSALADS) for automatically docking a chase vehicle with a target vehicle comprises at least one active light emitting target which is operatively attached to the target vehicle. The target includes a three-dimensional array of concomitantly flashing lights which flash at a controlled common frequency. The GPSSALADS further comprises a visual tracking sensor operatively attached to the chase vehicle for detecting and tracking the target vehicle. Its performance is synchronized with the flash frequency of the lights by a synchronization means which is comprised of first and second internal clocks operatively connected to the active light target and visual tracking sensor, respectively, for providing timing control signals thereto, respectively. The synchronization means further includes first and second Global Positioning System receivers operatively connected to the first and second internal clocks, respectively, for repeatedly providing simultaneous synchronization pulses to the internal clocks, respectively. In addition, the GPSSALADS includes a docking process controller means which is operatively attached to the chase vehicle and is responsive to the visual tracking sensor for producing commands for the guidance and propulsion system of the chase vehicle.

Evaluation of a computer-generated perspective tunnel display for flight path following

NASA Technical Reports Server (NTRS)

Grunwald, A. J.; Robertson, J. B.; Hatfield, J. J.

1980-01-01

The display was evaluated by monitoring pilot performance in a fixed base simulator with the vehicle dynamics of a CH-47 tandem rotor helicopter. Superposition of the predicted future vehicle position on the tunnel image was also investigated to determine whether, and to what extent, it contributes to better system performance (the best predicted future vehicle position was sought). Three types of simulator experiments were conducted: following a desired trajectory in the presence of disturbances; entering the trajectory from a random position, outside the trajectory; detecting and correcting failures in automatic flight. The tunnel display with superimposed predictor/director symbols was shown to be a very successful combination, which outperformed the other two displays in all three experiments. A prediction time of 4 to 7 sec. was found to optimize trajectory tracking for the given vehicle dynamics and flight condition. Pilot acceptance of the tunnel plus predictor/director display was found to be favorable and the time the pilot needed for familiarization with the display was found to be relatively short.

Automatic license plate reader: a solution to avoiding vehicle pursuit

NASA Astrophysics Data System (ADS)

Jordan, Stanley K.

1997-01-01

The Massachusetts Governor's Auto Theft Strike Force has tested an automatic license plate reader (LPR) to recover stolen cars and catch car thieves, without vehicle pursuit. Experiments were conducted at the Sumner Tunnel in Boston, and proved the feasibility of a LPR for identifying stolen cars instantly. The same technology can be applied to other law-enforcement objectives.

Integrating LPR with CCTV systems: problems and solutions

NASA Astrophysics Data System (ADS)

Bissessar, David; Gorodnichy, Dmitry O.

2011-06-01

A new generation of high-resolution surveillance cameras makes it possible to apply video processing and recognition techniques on live video feeds for the purpose of automatically detecting and identifying objects and events of interest. This paper addresses a particular application of detecting and identifying vehicles passing through a checkpoint. This application is of interest to border services agencies and is also related to many other applications. With many commercial automated License Plate Recognition (LPR) systems available on the market, some of which are available as a plug-in for surveillance systems, this application still poses many unresolved technological challenges, the main two of which are: i) multiple and often noisy license plate readings generated for the same vehicle, and ii) failure to detect a vehicle or license plate altogether when the license plate is occluded or not visible. This paper presents a solution to both of these problems. A data fusion technique based on the Levenshtein distance is used to resolve the first problem. An integration of a commercial LPR system with the in-house built Video Analytic Platform is used to solve the latter. The developed solution has been tested in field environments and has been shown to yield a substantial improvement over standard off-the-shelf LPR systems.

Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition

PubMed Central

Cui, Zhiming; Zhao, Pengpeng

2014-01-01

A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045

Vehicle-to-Grid Automatic Load Sharing with Driver Preference in Micro-Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Yubo; Nazaripouya, Hamidreza; Chu, Chi-Cheng

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities for distributed storage and generation. This paper comprehensively models and analyzes distributed Vehicle-to-Grid (V2G) for automatic load sharing with driver preference. In a micro-grid with limited communications, V2G EVs need to decide load sharing based on their own power and voltage profile. A droop based controller taking into account driver preference is proposed in this paper to address the distributed control of EVs. Simulations are designed for three fundamental V2G automatic load sharing scenarios that include all system dynamics of suchmore » applications. Simulation results demonstrate that active power sharing is achieved proportionally among V2G EVs with consideration of driver preference. In additional, the results also verify the system stability and reactive power sharing analysis in system modelling, which sheds light on large scale V2G automatic load sharing in more complicated cases.« less

a Novel Approach to Camera Calibration Method for Smart Phones Under Road Environment

NASA Astrophysics Data System (ADS)

Lee, Bijun; Zhou, Jian; Ye, Maosheng; Guo, Yuan

2016-06-01

Monocular vision-based lane departure warning system has been increasingly used in advanced driver assistance systems (ADAS). By the use of the lane mark detection and identification, we proposed an automatic and efficient camera calibration method for smart phones. At first, we can detect the lane marker feature in a perspective space and calculate edges of lane markers in image sequences. Second, because of the width of lane marker and road lane is fixed under the standard structural road environment, we can automatically build a transformation matrix between perspective space and 3D space and get a local map in vehicle coordinate system. In order to verify the validity of this method, we installed a smart phone in the `Tuzhi' self-driving car of Wuhan University and recorded more than 100km image data on the road in Wuhan. According to the result, we can calculate the positions of lane markers which are accurate enough for the self-driving car to run smoothly on the road.

Short-term change detection for UAV video

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer IOSB, see Heinze et. al. 2010.1 In a further step we plan to incorporate more information from the video sequences to the change detection input images, e.g., by image enhancement or by along-track stereo which are available in the ABUL system.

Operational strategies for rural transportation

DOT National Transportation Integrated Search

1996-03-01

ARC Transits AVL (Automatic Vehicle Location) project was funded by the Florida Department : of Transportation in May of 1994 with $40,937 in state Service Development funds. Fourteen : vehicle modules, the AVL base station, and several vehicle ra...

Biosignal Analysis to Assess Mental Stress in Automatic Driving of Trucks: Palmar Perspiration and Masseter Electromyography

PubMed Central

Zheng, Rencheng; Yamabe, Shigeyuki; Nakano, Kimihiko; Suda, Yoshihiro

2015-01-01

Nowadays insight into human-machine interaction is a critical topic with the large-scale development of intelligent vehicles. Biosignal analysis can provide a deeper understanding of driver behaviors that may indicate rationally practical use of the automatic technology. Therefore, this study concentrates on biosignal analysis to quantitatively evaluate mental stress of drivers during automatic driving of trucks, with vehicles set at a closed gap distance apart to reduce air resistance to save energy consumption. By application of two wearable sensor systems, a continuous measurement was realized for palmar perspiration and masseter electromyography, and a biosignal processing method was proposed to assess mental stress levels. In a driving simulator experiment, ten participants completed automatic driving with 4, 8, and 12 m gap distances from the preceding vehicle, and manual driving with about 25 m gap distance as a reference. It was found that mental stress significantly increased when the gap distances decreased, and an abrupt increase in mental stress of drivers was also observed accompanying a sudden change of the gap distance during automatic driving, which corresponded to significantly higher ride discomfort according to subjective reports. PMID:25738768

Recurrent neural network based virtual detection line

NASA Astrophysics Data System (ADS)

Kadikis, Roberts

2018-04-01

The paper proposes an efficient method for detection of moving objects in the video. The objects are detected when they cross a virtual detection line. Only the pixels of the detection line are processed, which makes the method computationally efficient. A Recurrent Neural Network processes these pixels. The machine learning approach allows one to train a model that works in different and changing outdoor conditions. Also, the same network can be trained for various detection tasks, which is demonstrated by the tests on vehicle and people counting. In addition, the paper proposes a method for semi-automatic acquisition of labeled training data. The labeling method is used to create training and testing datasets, which in turn are used to train and evaluate the accuracy and efficiency of the detection method. The method shows similar accuracy as the alternative efficient methods but provides greater adaptability and usability for different tasks.

Method and appartus for converting static in-ground vehicle scales into weigh-in-motion systems

DOEpatents

Muhs, Jeffrey D.; Scudiere, Matthew B.; Jordan, John K.

2002-01-01

An apparatus and method for converting in-ground static weighing scales for vehicles to weigh-in-motion systems. The apparatus upon conversion includes the existing in-ground static scale, peripheral switches and an electronic module for automatic computation of the weight. By monitoring the velocity, tire position, axle spacing, and real time output from existing static scales as a vehicle drives over the scales, the system determines when an axle of a vehicle is on the scale at a given time, monitors the combined weight output from any given axle combination on the scale(s) at any given time, and from these measurements automatically computes the weight of each individual axle and gross vehicle weight by an integration, integration approximation, and/or signal averaging technique.

Hybrid neuro-fuzzy approach for automatic vehicle license plate recognition

NASA Astrophysics Data System (ADS)

Lee, Hsi-Chieh; Jong, Chung-Shi

1998-03-01

Most currently available vehicle identification systems use techniques such as R.F., microwave, or infrared to help identifying the vehicle. Transponders are usually installed in the vehicle in order to transmit the corresponding information to the sensory system. It is considered expensive to install a transponder in each vehicle and the malfunction of the transponder will result in the failure of the vehicle identification system. In this study, novel hybrid approach is proposed for automatic vehicle license plate recognition. A system prototype is built which can be used independently or cooperating with current vehicle identification system in identifying a vehicle. The prototype consists of four major modules including the module for license plate region identification, the module for character extraction from the license plate, the module for character recognition, and the module for the SimNet neuro-fuzzy system. To test the performance of the proposed system, three hundred and eighty vehicle image samples are taken by a digital camera. The license plate recognition success rate of the prototype is approximately 91% while the character recognition success rate of the prototype is approximately 97%.

Video change detection for fixed wing UAVs

NASA Astrophysics Data System (ADS)

Bartelsen, Jan; Müller, Thomas; Ring, Jochen; Mück, Klaus; Brüstle, Stefan; Erdnüß, Bastian; Lutz, Bastian; Herbst, Theresa

2017-10-01

In this paper we proceed the work of Bartelsen et al.1 We present the draft of a process chain for an image based change detection which is designed for videos acquired by fixed wing unmanned aerial vehicles (UAVs). From our point of view, automatic video change detection for aerial images can be useful to recognize functional activities which are typically caused by the deployment of improvised explosive devices (IEDs), e.g. excavations, skid marks, footprints, left-behind tooling equipment, and marker stones. Furthermore, in case of natural disasters, like flooding, imminent danger can be recognized quickly. Due to the necessary flight range, we concentrate on fixed wing UAVs. Automatic change detection can be reduced to a comparatively simple photogrammetric problem when the perspective change between the "before" and "after" image sets is kept as small as possible. Therefore, the aerial image acquisition demands a mission planning with a clear purpose including flight path and sensor configuration. While the latter can be enabled simply by a fixed and meaningful adjustment of the camera, ensuring a small perspective change for "before" and "after" videos acquired by fixed wing UAVs is a challenging problem. Concerning this matter, we have performed tests with an advanced commercial off the shelf (COTS) system which comprises a differential GPS and autopilot system estimating the repetition accuracy of its trajectory. Although several similar approaches have been presented,23 as far as we are able to judge, the limits for this important issue are not estimated so far. Furthermore, we design a process chain to enable the practical utilization of video change detection. It consists of a front-end of a database to handle large amounts of video data, an image processing and change detection implementation, and the visualization of the results. We apply our process chain on the real video data acquired by the advanced COTS fixed wing UAV and synthetic data. For the image processing and change detection, we use the approach of Muller.4 Although it was developed for unmanned ground vehicles (UGVs), it enables a near real time video change detection for aerial videos. Concluding, we discuss the demands on sensor systems in the matter of change detection.

Automatic safety belt systems owner usage and attitudes in GM Chevettes and VW Rabbits

DOT National Transportation Integrated Search

1980-05-01

Author's abstract: The study was designed to: (1) evaluate the effectiveness of automatic restraint systems in increasing belt usage, and (2) determine owner attitudes toward the system. Information gathered from owners of vehicles with automatic sys...

Automatic safety belt systems owner usage and attitudes in GM Chevettes and VW Rabbits

DOT National Transportation Integrated Search

1981-02-01

This study was designed to: (1) evaluate the effectiveness of automatic restraint systems in increasing belt usage, and (2) determine owner attitudes toward the systems. The information gathered from owners of vehicles with automatic systems will ass...

Semantic Information Extraction of Lanes Based on Onboard Camera Videos

NASA Astrophysics Data System (ADS)

Tang, L.; Deng, T.; Ren, C.

2018-04-01

In the field of autonomous driving, semantic information of lanes is very important. This paper proposes a method of automatic detection of lanes and extraction of semantic information from onboard camera videos. The proposed method firstly detects the edges of lanes by the grayscale gradient direction, and improves the Probabilistic Hough transform to fit them; then, it uses the vanishing point principle to calculate the lane geometrical position, and uses lane characteristics to extract lane semantic information by the classification of decision trees. In the experiment, 216 road video images captured by a camera mounted onboard a moving vehicle were used to detect lanes and extract lane semantic information. The results show that the proposed method can accurately identify lane semantics from video images.

Emergency automatic signalling system using time scheduling

NASA Astrophysics Data System (ADS)

Rayavel, P.; Surenderanath, S.; Rathnavel, P.; Prakash, G.

2018-04-01

It is difficult to handle traffic congestion and maintain roads during traffic mainly in India. As the people migrate from rural to urban and sub-urban areas, it becomes still more critical. Presently Roadways is a standout amongst the most vital transportation. At the point when a car crash happens, crisis vehicles, for example, ambulances and fire trucks must rush to the mischance scene. There emerges a situation where a portion of the crisis vehicles may cause another car crash. Therefore it becomes still more difficult for emergency vehicle to reach the destination within a predicted time. To avoid that kind of problem we have come out with an effective idea which can reduce the potential in the traffic system. The traffic system is been modified using a wireless technology and high speed micro controller to provide smooth and clear flow of traffic for ambulance to reach the destination on time. This is achieved by using RFID Tag at the ambulance and RFID Reader at the traffic system i.e., traffic signal. This mainly deals with identifying the emergency vehicle and providing a green signal to traffic signal at time of traffic jam. — By assigning priorities to various traffic movements, we can control the traffic jam. In some moments like ambulance emergency, high delegates arrive people facing lot of trouble. To overcome this problem in this paper we propose a time priority based traffic system achieved by using RFID transmitter at the emergency vehicle and RFID receiver at the traffic system i.e., traffic signal. The signal from the emergency vehicle is sent to traffic system which after detecting it sends it to microcontroller which controls the traffic signal. If any emergency vehicle is detected the system goes to emergency system mode where signal switch to green and if it is not detected normal system mode.

System transfer modelling for automatic target recognizer evaluations

NASA Astrophysics Data System (ADS)

Clark, Lloyd G.

1991-11-01

Image processing to accomplish automatic recognition of military vehicles has promised increased weapons systems effectiveness and reduced timelines for a number of Department of Defense missions. Automatic Target Recognizers (ATR) are often claimed to be able to recognize many different ground vehicles as possible targets in military air-to- surface targeting applications. The targeting scenario conditions include different vehicle poses and histories as well as a variety of imaging geometries, intervening atmospheres, and background environments. Testing these ATR subsystems in most cases has been limited to a handful of the scenario conditions of interest, as is represented by imagery collected with the desired imaging sensor. The question naturally arises as to how robust the performance of the ATR is for all scenario conditions of interest, not just for the set of imagery upon which an algorithm was trained.

49 CFR 38.73 - Doorways.

Code of Federal Regulations, 2010 CFR

2010-10-01

.... Vertical alignment may be accomplished by vehicle air suspension, automatic ramps or lifts, or any... SPECIFICATIONS FOR TRANSPORTATION VEHICLES Light Rail Vehicles and Systems § 38.73 Doorways. (a) Clear width—(1) All passenger doorways on vehicle sides shall have minimum clear openings of 32 inches when open. (2...

Sensor Architecture and Task Classification for Agricultural Vehicles and Environments

PubMed Central

Rovira-Más, Francisco

2010-01-01

The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way. PMID:22163522

Sensor architecture and task classification for agricultural vehicles and environments.

PubMed

Rovira-Más, Francisco

2010-01-01

The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way.

47 CFR 15.251 - Operation within the bands 2.9-3.26 GHz, 3.267-3.332 GHz, 3.339-3.3458 GHz, and 3.358-3.6 GHz.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., and 3.358-3.6 GHz. (a) Operation under the provisions of this section is limited to automatic vehicle identification systems (AVIS) which use swept frequency techniques for the purpose of automatically identifying transportation vehicles. (b) The field strength anywhere within the frequency range swept by the signal shall not...

47 CFR 15.251 - Operation within the bands 2.9-3.26 GHz, 3.267-3.332 GHz, 3.339-3.3458 GHz, and 3.358-3.6 GHz.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., and 3.358-3.6 GHz. (a) Operation under the provisions of this section is limited to automatic vehicle identification systems (AVIS) which use swept frequency techniques for the purpose of automatically identifying transportation vehicles. (b) The field strength anywhere within the frequency range swept by the signal shall not...

47 CFR 15.251 - Operation within the bands 2.9-3.26 GHz, 3.267-3.332 GHz, 3.339-3.3458 GHz, and 3.358-3.6 GHz.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., and 3.358-3.6 GHz. (a) Operation under the provisions of this section is limited to automatic vehicle identification systems (AVIS) which use swept frequency techniques for the purpose of automatically identifying transportation vehicles. (b) The field strength anywhere within the frequency range swept by the signal shall not...

47 CFR 15.251 - Operation within the bands 2.9-3.26 GHz, 3.267-3.332 GHz, 3.339-3.3458 GHz, and 3.358-3.6 GHz.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., and 3.358-3.6 GHz. (a) Operation under the provisions of this section is limited to automatic vehicle identification systems (AVIS) which use swept frequency techniques for the purpose of automatically identifying transportation vehicles. (b) The field strength anywhere within the frequency range swept by the signal shall not...

78 FR 19363 - Petition for Exemption From the Vehicle Theft Prevention Standard; Honda

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-29

... immobilizer device occurs automatically when the vehicle is started without any further action by the driver... From the Vehicle Theft Prevention Standard; Honda AGENCY: National Highway Traffic Safety... Honda Civic vehicle line in accordance with 49 CFR part 543, Exemption from the Theft Prevention...

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

PubMed Central

Moussa, Adel; El-Sheimy, Naser; Habib, Ayman

2017-01-01

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research. PMID:29057847

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

PubMed

Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

2017-10-18

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

Vehicle rollover risk and electronic stability control systems.

PubMed

MacLennan, P A; Marshall, T; Griffin, R; Purcell, M; McGwin, G; Rue, L W

2008-06-01

Electronic stability control (ESC) systems were developed to reduce motor vehicle collisions (MVCs) caused by loss of control. Introduced in Europe in 1995 and in the USA in 1996, ESC is designed to improve vehicle lateral stability by electronically detecting and automatically assisting drivers in unfavorable situations. To examine the relationship between vehicle rollover risk and presence of ESC using a large national database of MVCs. A retrospective cohort study for the period 1995 through 2006 was carried out using data obtained from the National Automotive Sampling System General Estimates System. All passenger cars and sport utility vehicles (SUVs)/vans of model year 1996 and later were eligible. Vehicle ESC (unavailable, optional, standard) was determined on the basis of make, model, and model year. Risk ratios (RRs) and 95% CIs were calculated to compare rollover risk by vehicle ESC group. For all crashes, vehicles equipped with standard ESC had decreased risk of rollover (RR = 0.62, 95% CI 0.50 to 0.77) compared with vehicles with ESC unavailable. The association was consistent for single-vehicle MVCs (RR = 0.61, 95% CI 0.46 to 0.82); passenger cars had decreased rollover risk (RR = 0.77, 95% CI 0.52 to 1.12), but SUVs/vans had a more dramatically decreased risk (RR = 0.40, 95% CI 0.26 to 0.61). This study supports previous results showing ESC to be effective in reducing the risk of rollover. ESC is more effective in SUVs/vans for rollovers related to single-vehicle MVCs.

Machine learning for real time remote detection

NASA Astrophysics Data System (ADS)

Labbé, Benjamin; Fournier, Jérôme; Henaff, Gilles; Bascle, Bénédicte; Canu, Stéphane

2010-10-01

Infrared systems are key to providing enhanced capability to military forces such as automatic control of threats and prevention from air, naval and ground attacks. Key requirements for such a system to produce operational benefits are real-time processing as well as high efficiency in terms of detection and false alarm rate. These are serious issues since the system must deal with a large number of objects and categories to be recognized (small vehicles, armored vehicles, planes, buildings, etc.). Statistical learning based algorithms are promising candidates to meet these requirements when using selected discriminant features and real-time implementation. This paper proposes a new decision architecture benefiting from recent advances in machine learning by using an effective method for level set estimation. While building decision function, the proposed approach performs variable selection based on a discriminative criterion. Moreover, the use of level set makes it possible to manage rejection of unknown or ambiguous objects thus preserving the false alarm rate. Experimental evidences reported on real world infrared images demonstrate the validity of our approach.

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Hamledari, Hesam

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.

Prescription and over-the-counter medications tool kit.

DOT National Transportation Integrated Search

2011-04-01

Automatic vehicle location (AVL) is a computer-based vehicle tracking system. For transit, the actual real-time position of each vehicle is measured and its location is relayed to a control center. Actual position determination and relay techniques v...

Advanced sensors and applications : commercial motor vehicle tire pressure monitoring and maintenance : [technology brief].

DOT National Transportation Integrated Search

2014-04-01

Tire pressure monitoring and automatic tire inflation technologies show significant promise for improving safety and reducing costs in the commercial vehicle industry. Improved tire pressure management directly relates to improved vehicle stability, ...

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

Automatic vehicle monitoring systems study. Report of phase O. Volume 2: Problem definition and derivation of AVM system selection techniques

NASA Technical Reports Server (NTRS)

1976-01-01

A set of planning guidelines is presented to help law enforcement agencies and vehicle fleet operators decide which automatic vehicle monitoring (AVM) system could best meet their performance requirements. Improvements in emergency response times and resultant cost benefits obtainable with various operational and planned AVM systems may be synthesized and simulated by means of special computer programs for model city parameters applicable to small, medium and large urban areas. Design characteristics of various AVM systems and the implementation requirements are illustrated and cost estimated for the vehicles, the fixed sites and the base equipments. Vehicle location accuracies for different RF links and polling intervals are analyzed. Actual applications and coverage data are tabulated for seven cities whose police departments actively cooperated in the study.

Automated Guided Vehicle For Phsically Handicapped People - A Cost Effective Approach

NASA Astrophysics Data System (ADS)

Kumar, G. Arun, Dr.; Sivasubramaniam, Mr. A.

2017-12-01

Automated Guided vehicle (AGV) is like a robot that can deliver the materials from the supply area to the technician automatically. This is faster and more efficient. The robot can be accessed wirelessly. A technician can directly control the robot to deliver the components rather than control it via a human operator (over phone, computer etc. who has to program the robot or ask a delivery person to make the delivery). The vehicle is automatically guided through its ways. To avoid collisions a proximity sensor is attached to the system. The sensor senses the signals of the obstacles and can stop the vehicle in the presence of obstacles. Thus vehicle can avoid accidents that can be very useful to the present industrial trend and material handling and equipment handling will be automated and easy time saving methodology.

Modeling and Prototyping of Automatic Clutch System for Light Vehicles

NASA Astrophysics Data System (ADS)

Murali, S.; Jothi Prakash, V. M.; Vishal, S.

2017-03-01

Nowadays, recycling or regenerating the waste in to something useful is appreciated all around the globe. It reduces greenhouse gas emissions that contribute to global climate change. This study deals with provision of the automatic clutch mechanism in vehicles to facilitate the smooth changing of gears. This study proposed to use the exhaust gases which are normally expelled out as a waste from the turbocharger to actuate the clutch mechanism in vehicles to facilitate the smooth changing of gears. At present, clutches are operated automatically by using an air compressor in the four wheelers. In this study, a conceptual design is proposed in which the clutch is operated by the exhaust gas from the turbocharger and this will remove the usage of air compressor in the existing system. With this system, usage of air compressor is eliminated and the riders need not to operate the clutch manually. This work involved in development, analysation and validation of the conceptual design through simulation software. Then the developed conceptual design of an automatic pneumatic clutch system is tested with proto type.

Piloted Simulation Evaluation of a Model-Predictive Automatic Recovery System to Prevent Vehicle Loss of Control on Approach

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Liu, Yuan; Sowers, T. Shane; Owen, A. Karl; Guo, Ten-Huei

2014-01-01

This paper describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.

A machine learning approach for detecting cell phone usage

NASA Astrophysics Data System (ADS)

Xu, Beilei; Loce, Robert P.

2015-03-01

Cell phone usage while driving is common, but widely considered dangerous due to distraction to the driver. Because of the high number of accidents related to cell phone usage while driving, several states have enacted regulations that prohibit driver cell phone usage while driving. However, to enforce the regulation, current practice requires dispatching law enforcement officers at road side to visually examine incoming cars or having human operators manually examine image/video records to identify violators. Both of these practices are expensive, difficult, and ultimately ineffective. Therefore, there is a need for a semi-automatic or automatic solution to detect driver cell phone usage. In this paper, we propose a machine-learning-based method for detecting driver cell phone usage using a camera system directed at the vehicle's front windshield. The developed method consists of two stages: first, the frontal windshield region localization using the deformable part model (DPM), next, we utilize Fisher vectors (FV) representation to classify the driver's side of the windshield into cell phone usage violation and non-violation classes. The proposed method achieved about 95% accuracy with a data set of more than 100 images with drivers in a variety of challenging poses with or without cell phones.

Automatic Transmissions and Transaxles. Auto Mechanics Curriculum Guide. Module 8. Instructor's Guide.

ERIC Educational Resources Information Center

Hevel, David; Tannehill, Dana, Ed.

This module is the eighth of nine modules in the competency-based Missouri Auto Mechanics Curriculum Guide. Six units cover: introduction to automatic transmission/transaxle; hydraulic control systems; transmission/transaxle diagnosis; automatic transmission/transaxle maintenance and adjustment; in-vehicle transmission repair; and off-car…

Prediction Study on Anti-Slide Control of Railway Vehicle Based on RBF Neural Networks

NASA Astrophysics Data System (ADS)

Yang, Lijun; Zhang, Jimin

While railway vehicle braking, Anti-slide control system will detect operating status of each wheel-sets e.g. speed difference and deceleration etc. Once the detected value on some wheel-set is over pre-defined threshold, brake effort on such wheel-set will be adjusted automatically to avoid blocking. Such method takes effect on guarantee safety operation of vehicle and avoid wheel-set flatness, however it cannot adapt itself to the rail adhesion variation. While wheel-sets slide, the operating status is chaotic time series with certain law, and can be predicted with the law and experiment data in certain time. The predicted values can be used as the input reference signals of vehicle anti-slide control system, to judge and control the slide status of wheel-sets. In this article, the RBF neural networks is taken to predict wheel-set slide status in multi-step with weight vector adjusted based on online self-adaptive algorithm, and the center & normalizing parameters of active function of the hidden unit of RBF neural networks' hidden layer computed with K-means clustering algorithm. With multi-step prediction simulation, the predicted signal with appropriate precision can be used by anti-slide system to trace actively and adjust wheel-set slide tendency, so as to adapt to wheel-rail adhesion variation and reduce the risk of wheel-set blocking.

49 CFR 571.102 - Standard No. 102; Transmission shift position sequence, starter interlock, and transmission...

Code of Federal Regulations, 2010 CFR

2010-10-01

... position. S3.1.2Transmission braking effect. In vehicles having more than one forward transmission gear... driver has activated the vehicle's propulsion system: (a) The engine may stop and restart automatically... activated the vehicle's propulsion system if the vehicle can meet the requirements specified in paragraphs...

Development and Testing of an Automatic Transmission Shift Schedule Algorithm for Vehicle Simulation (SAE Paper 2015-01-1142)

EPA Science Inventory

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) modeling tool was created by EPA to estimate greenhouse gas (GHG) emissions of light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle type...

Real-time inspection by submarine images

NASA Astrophysics Data System (ADS)

Tascini, Guido; Zingaretti, Primo; Conte, Giuseppe

1996-10-01

A real-time application of computer vision concerning tracking and inspection of a submarine pipeline is described. The objective is to develop automatic procedures for supporting human operators in the real-time analysis of images acquired by means of cameras mounted on underwater remotely operated vehicles (ROV) Implementation of such procedures gives rise to a human-machine system for underwater pipeline inspection that can automatically detect and signal the presence of the pipe, of its structural or accessory elements, and of dangerous or alien objects in its neighborhood. The possibility of modifying the image acquisition rate in the simulations performed on video- recorded images is used to prove that the system performs all necessary processing with an acceptable robustness working in real-time up to a speed of about 2.5 kn, widely greater than that the actual ROVs and the security features allow.

Interactive computer aided technology, evolution in the design/manufacturing process

NASA Technical Reports Server (NTRS)

English, C. H.

1975-01-01

A powerful computer-operated three dimensional graphic system and associated auxiliary computer equipment used in advanced design, production design, and manufacturing was described. This system has made these activities more productive than when using older and more conventional methods to design and build aerospace vehicles. With the use of this graphic system, designers are now able to define parts using a wide variety of geometric entities, define parts as fully surface 3-dimensional models as well as "wire-frame" models. Once geometrically defined, the designer is able to take section cuts of the surfaced model and automatically determine all of the section properties of the planar cut, lightpen detect all of the surface patches and automatically determine the volume and weight of the part. Further, his designs are defined mathematically at a degree of accuracy never before achievable.

Automatic guidance control of an articulated all-wheel-steered vehicle

NASA Astrophysics Data System (ADS)

Kim, Young Chol; Yun, Kyong-Han; Min, Kyung-Deuk

2014-04-01

This paper presents automatic guidance control of a single-articulated all-wheel-steered vehicle being developed by the Korea Railroad Research Institute. The vehicle has an independent drive motor on each wheel except for the front axle. The guidance controller is designed so that the vehicle follows the given reference path within permissible lateral deviations. We use a three-input/three-output linearised model derived from the nonlinear dynamic model of the vehicle. For the purpose of simplifying the controller and making it tunable, we consider a decentralised control configuration. We first design a second-order decoupling compensator for the two-input/two-output system that is strongly coupled and then design a first-order controller for each decoupled feedback loop by using the characteristic ratio assignment method. The simulation results for the nonlinear dynamic model indicate that the proposed control configuration successfully achieves the design objectives.

Dust-Tolerant Intelligent Electrical Connection System

NASA Technical Reports Server (NTRS)

Lewis, Mark; Dokos, Adam; Perotti, Jose; Calle, Carlos; Mueller, Robert; Bastin, Gary; Carlson, Jeffrey; Townsend, Ivan, III; Immer, Chirstopher; Medelius, Pedro

2012-01-01

Faults in wiring systems are a serious concern for the aerospace and aeronautic (commercial, military, and civilian) industries. Circuit failures and vehicle accidents have occurred and have been attributed to faulty wiring created by open and/or short circuits. Often, such circuit failures occur due to vibration during vehicle launch or operation. Therefore, developing non-intrusive fault-tolerant techniques is necessary to detect circuit faults and automatically route signals through alternate recovery paths while the vehicle or lunar surface systems equipment is in operation. Electrical connector concepts combining dust mitigation strategies and cable diagnostic technologies have significant application for lunar and Martian surface systems, as well as for dusty terrestrial applications. The dust-tolerant intelligent electrical connection system has several novel concepts and unique features. It combines intelligent cable diagnostics (health monitoring) and automatic circuit routing capabilities into a dust-tolerant electrical umbilical. It retrofits a clamshell protective dust cover to an existing connector for reduced gravity operation, and features a universal connector housing with three styles of dust protection: inverted cap, rotating cap, and clamshell. It uses a self-healing membrane as a dust barrier for electrical connectors where required, while also combining lotus leaf technology for applications where a dust-resistant coating providing low surface tension is needed to mitigate Van der Waals forces, thereby disallowing dust particle adhesion to connector surfaces. It also permits using a ruggedized iris mechanism with an embedded electrodynamic dust shield as a dust barrier for electrical connectors where required.

Study of automatic and manual terminal guidance and control systems for space shuttle vehicles. Volume 2: Section 4 through appendix B

NASA Technical Reports Server (NTRS)

Osder, S.; Keller, R.

1971-01-01

Guidance and control design studies that were performed for three specific space shuttle candidate vehicles are described. Three types of simulation were considered. The manual control investigations and pilot evaluations of the automatic system performance is presented. Recommendations for systems and equipment, both airborne and ground-based, necessary to flight test the guidance and control concepts for shuttlecraft terminal approach and landing are reported.

Application of automatic vehicle location in law enforcement: An introductory planning guide

NASA Technical Reports Server (NTRS)

Hansen, G. R.; Leflang, W. G.

1976-01-01

A set of planning guidelines for the application of automatic vehicle location (AVL) to law enforcement is presented. Some essential characteristics and applications of AVL are outlined; systems in the operational or planning phases are discussed. Requirements analysis, system concept design, implementation planning, and performance and cost modeling are described and demonstrated with numerous examples. A detailed description of a typical law enforcement AVL system, and a list of vendor sources are given in appendixes.

Current development of UAV sense and avoid system

NASA Astrophysics Data System (ADS)

Zhahir, A.; Razali, A.; Mohd Ajir, M. R.

2016-10-01

As unmanned aerial vehicles (UAVs) are now gaining high interests from civil and commercialised market, the automatic sense and avoid (SAA) system is currently one of the essential features in research spotlight of UAV. Several sensor types employed in current SAA research and technology of sensor fusion that offers a great opportunity in improving detection and tracking system are presented here. The purpose of this paper is to provide an overview of SAA system development in general, as well as the current challenges facing UAV researchers and designers.

The Visual Representation and Acquisition of Driving Knowledge for Autonomous Vehicle

NASA Astrophysics Data System (ADS)

Zhang, Zhaoxia; Jiang, Qing; Li, Ping; Song, LiangTu; Wang, Rujing; Yu, Biao; Mei, Tao

2017-09-01

In this paper, the driving knowledge base of autonomous vehicle is designed. Based on the driving knowledge modeling system, the driving knowledge of autonomous vehicle is visually acquired, managed, stored, and maintenanced, which has vital significance for creating the development platform of intelligent decision-making systems of automatic driving expert systems for autonomous vehicle.

Experiences with Acquiring Highly Redundant Spatial Data to Support Driverless Vehicle Technologies

NASA Astrophysics Data System (ADS)

Koppanyi, Z.; Toth, C. K.

2018-05-01

As vehicle technology is moving towards higher autonomy, the demand for highly accurate geospatial data is rapidly increasing, as accurate maps have a huge potential of increasing safety. In particular, high definition 3D maps, including road topography and infrastructure, as well as city models along the transportation corridors represent the necessary support for driverless vehicles. In this effort, a vehicle equipped with high-, medium- and low-resolution active and passive cameras acquired data in a typical traffic environment, represented here by the OSU campus, where GPS/GNSS data are available along with other navigation sensor data streams. The data streams can be used for two purposes. First, high-definition 3D maps can be created by integrating all the sensory data, and Data Analytics/Big Data methods can be tested for automatic object space reconstruction. Second, the data streams can support algorithmic research for driverless vehicle technologies, including object avoidance, navigation/positioning, detecting pedestrians and bicyclists, etc. Crucial cross-performance analyses on map database resolution and accuracy with respect to sensor performance metrics to achieve economic solution for accurate driverless vehicle positioning can be derived. These, in turn, could provide essential information on optimizing the choice of geospatial map databases and sensors' quality to support driverless vehicle technologies. The paper reviews the data acquisition and primary data processing challenges and performance results.

Traffic-Light-Preemption Vehicle-Transponder Software Module

NASA Technical Reports Server (NTRS)

Bachelder, Aaron; Foster, Conrad

2005-01-01

A prototype wireless data-communication and control system automatically modifies the switching of traffic lights to give priority to emergency vehicles. The system, which was reported in several NASA Tech Briefs articles at earlier stages of development, includes a transponder on each emergency vehicle, a monitoring and control unit (an intersection controller) at each intersection equipped with traffic lights, and a central monitoring subsystem. An essential component of the system is a software module executed by a microcontroller in each transponder. This module integrates and broadcasts data on the position, velocity, acceleration, and emergency status of the vehicle. The position, velocity, and acceleration data are derived partly from the Global Positioning System, partly from deductive reckoning, and partly from a diagnostic computer aboard the vehicle. The software module also monitors similar broadcasts from other vehicles and from intersection controllers, informs the driver of which intersections it controls, and generates visible and audible alerts to inform the driver of any other emergency vehicles that are close enough to create a potential hazard. The execution of the software module can be monitored remotely and the module can be upgraded remotely and, hence, automatically

Vector Pursuit Path Tracking for Autonomous Ground Vehicles

DTIC Science & Technology

2000-08-01

vi INTRODUCTION ...........................................................................................................1...other geometric path-tracking techniques. 1 CHAPTER 1 INTRODUCTION An autonomous vehicle is one that is capable of automatic navigation. It is...Joint Architecture for Unmanned Ground Vehicles ( JAUGS ) working group meeting held at the University of Florida. 5 Figure 1.5: Autonomous

Radar signatures of road vehicles: airborne SAR experiments

NASA Astrophysics Data System (ADS)

Palubinskas, G.; Runge, H.; Reinartz, P.

2005-10-01

The German radar satellite TerraSAR-X is a high resolution, dual receive antenna SAR satellite, which will be launched in spring 2006. Since it will have the capability to measure the velocity of moving targets, the acquired interferometric data can be useful for traffic monitoring applications on a global scale. DLR has started already the development of an automatic and operational processing system which will detect cars, measure their speed and assign them to a road. Statistical approaches are used to derive the vehicle detection algorithm, which require the knowledge of the radar signatures of vehicles, especially under consideration of the geometry of the radar look direction and the vehicle orientation. Simulation of radar signatures is a very difficult task due to the lack of realistic models of vehicles. In this paper the radar signatures of the parking cars are presented. They are estimated experimentally from airborne E-SAR X-band data, which have been collected during flight campaigns in 2003-2005. Several test cars of the same type placed in carefully selected orientation angles and several over-flights with different heading angles made it possible to cover the whole range of aspect angles from 0° to 180°. The large synthetic aperture length or beam width angle of 7° can be divided into several looks. Thus processing of each look separately allows to increase the angle resolution. Such a radar signature profile of one type of vehicle over the whole range of aspect angles in fine resolution can be used further for the verification of simulation studies and for the performance prediction for traffic monitoring with TerraSAR-X.

Person detection and tracking with a 360° lidar system

NASA Astrophysics Data System (ADS)

Hammer, Marcus; Hebel, Marcus; Arens, Michael

2017-10-01

Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks. In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed. The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.

A group filter algorithm for sea mine detection

NASA Astrophysics Data System (ADS)

Cobb, J. Tory; An, Myoung; Tolimieri, Richard

2005-06-01

Automatic detection of sea mines in coastal regions is a difficult task due to the highly variable sea bottom conditions present in the underwater environment. Detection systems must be able to discriminate objects which vary in size, shape, and orientation from naturally occurring and man-made clutter. Additionally, these automated systems must be computationally efficient to be incorporated into unmanned underwater vehicle (UUV) sensor systems characterized by high sensor data rates and limited processing abilities. Using noncommutative group harmonic analysis, a fast, robust sea mine detection system is created. A family of unitary image transforms associated to noncommutative groups is generated and applied to side scan sonar image files supplied by Naval Surface Warfare Center Panama City (NSWC PC). These transforms project key image features, geometrically defined structures with orientations, and localized spectral information into distinct orthogonal components or feature subspaces of the image. The performance of the detection system is compared against the performance of an independent detection system in terms of probability of detection (Pd) and probability of false alarm (Pfa).

NREL Transportation Project to Reduce Fuel Usage

Science.gov Websites

and communication software was developed by NREL researchers to display a vehicle's location automatically and transmit a map of the its location over the Internet. After developing the communication vehicle location and communication technology to track and direct vehicle fleet movements," said the

49 CFR 38.73 - Doorways.

Code of Federal Regulations, 2014 CFR

2014-10-01

... inches and the height of the vehicle floor shall be within plus or minus 5/8 inch of the platform height. Vertical alignment may be accomplished by vehicle air suspension, automatic ramps or lifts, or any combination. (2) Exception. New vehicles operating in existing stations may have a floor height within plus or...

49 CFR 38.73 - Doorways.

Code of Federal Regulations, 2013 CFR

2013-10-01

... inches and the height of the vehicle floor shall be within plus or minus 5/8 inch of the platform height. Vertical alignment may be accomplished by vehicle air suspension, automatic ramps or lifts, or any combination. (2) Exception. New vehicles operating in existing stations may have a floor height within plus or...

49 CFR 38.73 - Doorways.

Code of Federal Regulations, 2012 CFR

2012-10-01

... inches and the height of the vehicle floor shall be within plus or minus 5/8 inch of the platform height. Vertical alignment may be accomplished by vehicle air suspension, automatic ramps or lifts, or any combination. (2) Exception. New vehicles operating in existing stations may have a floor height within plus or...

49 CFR 38.73 - Doorways.

Code of Federal Regulations, 2011 CFR

2011-10-01

... inches and the height of the vehicle floor shall be within plus or minus 5/8 inch of the platform height. Vertical alignment may be accomplished by vehicle air suspension, automatic ramps or lifts, or any combination. (2) Exception. New vehicles operating in existing stations may have a floor height within plus or...

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

A new license plate extraction framework based on fast mean shift

NASA Astrophysics Data System (ADS)

Pan, Luning; Li, Shuguang

2010-08-01

License plate extraction is considered to be the most crucial step of Automatic license plate recognition (ALPR) system. In this paper, a region-based license plate hybrid detection method is proposed to solve practical problems under complex background in which existing large quantity of disturbing information. In this method, coarse license plate location is carried out firstly to get the head part of a vehicle. Then a new Fast Mean Shift method based on random sampling of Kernel Density Estimate (KDE) is adopted to segment the color vehicle images, in order to get candidate license plate regions. The remarkable speed-up it brings makes Mean Shift segmentation more suitable for this application. Feature extraction and classification is used to accurately separate license plate from other candidate regions. At last, tilted license plate regulation is used for future recognition steps.

Port-of-entry advanced sorting system (PASS) operational test

DOT National Transportation Integrated Search

1998-12-01

In 1992 the Oregon Department of Transportation undertook an operational test of the Port-of-Entry Advanced Sorting System (PASS), which uses a two-way communication automatic vehicle identification system, integrated with weigh-in-motion, automatic ...

Performance of an Automated-Mixed-Traffic-Vehicle /AMTV/ System. [urban people mover

NASA Technical Reports Server (NTRS)

Peng, T. K. C.; Chon, K.

1978-01-01

This study analyzes the operation and evaluates the expected performance of a proposed automatic guideway transit system which uses low-speed Automated Mixed Traffic Vehicles (AMTV's). Vehicle scheduling and headway control policies are evaluated with a transit system simulation model. The effect of mixed-traffic interference on the average vehicle speed is examined with a vehicle-pedestrian interface model. Control parameters regulating vehicle speed are evaluated for safe stopping and passenger comfort.

49 CFR 325.59 - Measurement procedure; stationary test.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) If the motor vehicle's engine radiator fan drive is equipped with a clutch or similar device that... minutes, to permit the engine radiator fan to automatically disengage when the vehicle's noise emissions...

Practical automatic Arabic license plate recognition system

NASA Astrophysics Data System (ADS)

Mohammad, Khader; Agaian, Sos; Saleh, Hani

2011-02-01

Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

A study on special test stand of automatic and manual descent control in presence of simulated g-load effect

NASA Astrophysics Data System (ADS)

Glazkov, Yury; Artjuchin, Yury; Astakhov, Alexander; Vas'kov, Alexander; Malyshev, Veniamin; Mitroshin, Edward; Glinsky, Valery; Moiseenko, Vasily; Makovlev, Vyacheslav

The development of aircraft-type reusable space vehicles (RSV) involves the problem of complete compatibility of automatic, director and manual control. Task decision is complicated, in particular, due to considerable quantitative and qualitative changes of vehicle dynamic characteristics, little stability margins (and even of unstability) of the RSV, and stringent requirements to control accuracy at some flight phases. Besides, during control a pilot is affected by g-loads which hamper motor activity and deteriorate its accuracy, alter the functional status of the visual analyser, and influence higher nervous activity. A study of g-load effects on the control efficiency, especially in manual and director modes, is of primary importance. The main tools for study of a rational selection of manual and director vehicle control systems and as an aid in formulating recommendations for optimum crew-automatic control system interactions are special complex and functional flight simulator test stands. The proposed simulator stand includes a powerful digital computer complex combined with the control system of the centrifuge. The interior of a pilot's vehicle cabin is imitated. A situation image system, pyscho-physical monitoring system, physician, centrifuge operator, and instructor stations are linked with the test stand.

An Injury Severity-, Time Sensitivity-, and Predictability-Based Advanced Automatic Crash Notification Algorithm Improves Motor Vehicle Crash Occupant Triage.

PubMed

Stitzel, Joel D; Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Schoell, Samantha L; Doud, Andrea N; Martin, R Shayn; Meredith, J Wayne

2016-06-01

Advanced Automatic Crash Notification algorithms use vehicle telemetry measurements to predict risk of serious motor vehicle crash injury. The objective of the study was to develop an Advanced Automatic Crash Notification algorithm to reduce response time, increase triage efficiency, and improve patient outcomes by minimizing undertriage (<5%) and overtriage (<50%), as recommended by the American College of Surgeons. A list of injuries associated with a patient's need for Level I/II trauma center treatment known as the Target Injury List was determined using an approach based on 3 facets of injury: severity, time sensitivity, and predictability. Multivariable logistic regression was used to predict an occupant's risk of sustaining an injury on the Target Injury List based on crash severity and restraint factors for occupants in the National Automotive Sampling System - Crashworthiness Data System 2000-2011. The Advanced Automatic Crash Notification algorithm was optimized and evaluated to minimize triage rates, per American College of Surgeons recommendations. The following rates were achieved: <50% overtriage and <5% undertriage in side impacts and 6% to 16% undertriage in other crash modes. Nationwide implementation of our algorithm is estimated to improve triage decisions for 44% of undertriaged and 38% of overtriaged occupants. Annually, this translates to more appropriate care for >2,700 seriously injured occupants and reduces unnecessary use of trauma center resources for >162,000 minimally injured occupants. The algorithm could be incorporated into vehicles to inform emergency personnel of recommended motor vehicle crash triage decisions. Lower under- and overtriage was achieved, and nationwide implementation of the algorithm would yield improved triage decision making for an estimated 165,000 occupants annually. Copyright © 2016. Published by Elsevier Inc.

A Ground-Based Near Infrared Camera Array System for UAV Auto-Landing in GPS-Denied Environment.

PubMed

Yang, Tao; Li, Guangpo; Li, Jing; Zhang, Yanning; Zhang, Xiaoqiang; Zhang, Zhuoyue; Li, Zhi

2016-08-30

This paper proposes a novel infrared camera array guidance system with capability to track and provide real time position and speed of a fixed-wing Unmanned air vehicle (UAV) during a landing process. The system mainly include three novel parts: (1) Infrared camera array and near infrared laser lamp based cooperative long range optical imaging module; (2) Large scale outdoor camera array calibration module; and (3) Laser marker detection and 3D tracking module. Extensive automatic landing experiments with fixed-wing flight demonstrate that our infrared camera array system has the unique ability to guide the UAV landing safely and accurately in real time. Moreover, the measurement and control distance of our system is more than 1000 m. The experimental results also demonstrate that our system can be used for UAV automatic accurate landing in Global Position System (GPS)-denied environments.

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery

PubMed Central

Tamouridou, Afroditi A.; Lagopodi, Anastasia L.; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-01-01

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery. PMID:29019957

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery.

PubMed

Tamouridou, Afroditi A; Alexandridis, Thomas K; Pantazi, Xanthoula E; Lagopodi, Anastasia L; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-10-11

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery.

The charging security study of electric vehicle charging spot based on automatic testing platform

NASA Astrophysics Data System (ADS)

Li, Yulan; Yang, Zhangli; Zhu, Bin; Ran, Shengyi

2018-03-01

With the increasing of charging spots, the testing of charging security and interoperability becomes more and more urgent and important. In this paper, an interface simulator for ac charging test is designed, the automatic testing platform for electric vehicle charging spots is set up and used to test and analyze the abnormal state during the charging process. On the platform, the charging security and interoperability of ac charging spots and IC-CPD can be checked efficiently, the test report can be generated automatically with No artificial reading error. From the test results, the main reason why the charging spot is not qualified is that the power supply cannot be cut off in the prescribed time when the charging anomaly occurs.

Port-of-entry Advanced Sorting System (PASS) operational test : final report

DOT National Transportation Integrated Search

1998-12-01

In 1992 the Oregon Department of Transportation undertook an operational test of the Port-of-Entry Advanced Sorting System (PASS), which uses a two-way communication automatic vehicle identification system, integrated with weigh-in-motion, automatic ...

Pixel color feature enhancement for road signs detection

NASA Astrophysics Data System (ADS)

Zhang, Qieshi; Kamata, Sei-ichiro

2010-02-01

Road signs play an important role in our daily life which used to guide drivers to notice variety of road conditions and cautions. They provide important visual information that can help drivers operating their vehicles in a manner for enhancing traffic safety. The occurrence of some accidents can be reduced by using automatic road signs recognition system which can alert the drivers. This research attempts to develop a warning system to alert the drivers to notice the important road signs early enough to refrain road accidents from happening. For solving this, a non-linear weighted color enhancement method by pixels is presented. Due to the advantage of proposed method, different road signs can be detected from videos effectively. With suitably coefficients and operations, the experimental results have proved that the proposed method is robust, accurate and powerful in road signs detection.

Alternative Fuels Data Center: Propane Related Links

Science.gov Websites

Amerex Corporation's Vehicle Fire Suppression Systems are designed to warn the vehicle operator and suppress the fire, protecting both equipment and employees. Automatic systems suppress the fire in its

49 CFR 599.303 - Agency disposition of dealer application for reimbursement.

Code of Federal Regulations, 2010 CFR

2010-10-01

... correct a non-conforming submission. (d) Electronic rejection. An application is automatically rejected... transaction, or identifies the vehicle identification number of a new or trade-in vehicle that was involved in...

Assessment of computer dispatch technology in the paratransit industry

DOT National Transportation Integrated Search

Intelligent Vehicle-Highway Systems (IVHS) technologies include a range of communications and control technologies. The U.S. Department of Transportation has applied IVHS technologies, such as electronic payment media, automatic vehicle locator syste...

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1984-01-01

A unified control synthesis methodology for complex and/or non-conventional flight vehicles are developed. Prediction techniques for the handling characteristics of such vehicles and pilot parameter identification from experimental data are addressed.

Advanced Vehicle Control Systems Potential Tort Liability For Developers

DOT National Transportation Integrated Search

1993-12-01

AUTOMOBILE ACCIDENTS AVOIDED BECAUSE THE AUTOMATIC COLLISION AVOIDANCE SYSTEM APPLIES THE BRAKES, HIGHWAYS WHICH ACCOMMODATE MORE VEHICLES WITH FEWER ACCIDENTS, AND EVEN CARS WHICH ARE PILOTED ENTIRELY BY SOPHISTICATED ELECTRONIC SYSTEMS -- ALL OF TH...

Adaptive video-based vehicle classification technique for monitoring traffic : [executive summary].

DOT National Transportation Integrated Search

2015-08-01

Federal Highway Administration (FHWA) recommends axle-based classification standards to map : passenger vehicles, single unit trucks, and multi-unit trucks, at Automatic Traffic Recorder (ATR) stations : statewide. Many state Departments of Transport...

Designing Effective In-vehicle Icons

DOT National Transportation Integrated Search

1975-04-01

The design of a system for scanning sequences of aerial photographs with a computer-controlled flying-spot scanner and automatically measuring vehicle locations is described. Hardware and software requirements for an operational system of this type a...

Microwave Radiometers for Fire Detection in Trains: Theory and Feasibility Study.

PubMed

Alimenti, Federico; Roselli, Luca; Bonafoni, Stefania

2016-06-17

This paper introduces the theory of fire detection in moving vehicles by microwave radiometers. The system analysis is discussed and a feasibility study is illustrated on the basis of two implementation hypotheses. The basic idea is to have a fixed radiometer and to look inside the glass windows of the wagon when it passes in front of the instrument antenna. The proposed sensor uses a three-pixel multi-beam configuration that allows an image to be formed by the movement of the train itself. Each pixel is constituted by a direct amplification microwave receiver operating at 31.4 GHz. At this frequency, the antenna can be a 34 cm offset parabolic dish, whereas a 1 K brightness temperature resolution is achievable with an overall system noise figure of 6 dB, an observation bandwidth of 2 GHz and an integration time of 1 ms. The effect of the detector noise is also investigated and several implementation hypotheses are discussed. The presented study is important since it could be applied to the automatic fire alarm in trains and moving vehicles with dielectric wall/windows.

Microwave Radiometers for Fire Detection in Trains: Theory and Feasibility Study †

PubMed Central

Alimenti, Federico; Roselli, Luca; Bonafoni, Stefania

2016-01-01

This paper introduces the theory of fire detection in moving vehicles by microwave radiometers. The system analysis is discussed and a feasibility study is illustrated on the basis of two implementation hypotheses. The basic idea is to have a fixed radiometer and to look inside the glass windows of the wagon when it passes in front of the instrument antenna. The proposed sensor uses a three-pixel multi-beam configuration that allows an image to be formed by the movement of the train itself. Each pixel is constituted by a direct amplification microwave receiver operating at 31.4 GHz. At this frequency, the antenna can be a 34 cm offset parabolic dish, whereas a 1 K brightness temperature resolution is achievable with an overall system noise figure of 6 dB, an observation bandwidth of 2 GHz and an integration time of 1 ms. The effect of the detector noise is also investigated and several implementation hypotheses are discussed. The presented study is important since it could be applied to the automatic fire alarm in trains and moving vehicles with dielectric wall/windows. PMID:27322280

A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles.

PubMed

Suhr, Jae Kyu; Jung, Ho Gi

2018-04-16

An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision.

A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles

PubMed Central

2018-01-01

An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision. PMID:29659512

49 CFR 393.43 - Breakaway and emergency braking.

Code of Federal Regulations, 2010 CFR

2010-10-01

... protection system. Every motor vehicle, if used to tow a trailer equipped with brakes, shall be equipped with... protection valve or similar device shall operate automatically when the air pressure on the towing vehicle is... brake systems installed on towed vehicles shall be so designed, by the use of “no-bleed-back” relay...

49 CFR 393.43 - Breakaway and emergency braking.

Code of Federal Regulations, 2011 CFR

2011-10-01

... protection system. Every motor vehicle, if used to tow a trailer equipped with brakes, shall be equipped with... protection valve or similar device shall operate automatically when the air pressure on the towing vehicle is... brake systems installed on towed vehicles shall be so designed, by the use of “no-bleed-back” relay...

The impact of artificial vehicle sounds for pedestrians on driver stress.

PubMed

Cottrell, Nicholas D; Barton, Benjamin K

2012-01-01

Electrically based vehicles have produced some concern over their lack of sound, but the impact of artificial sounds now being implemented have not been examined in respect to their effects upon the driver. The impact of two different implementations of vehicle sound on driver stress in electric vehicles was examined. A Nissan HEV running in electric vehicle mode was driven by participants in an area of congestion using three sound implementations: (1) no artificial sounds, (2) manually engaged sounds and (3) automatically engaged sounds. Physiological and self-report questionnaire measures were collected to determine stress and acceptance of the automated sound protocol. Driver stress was significantly higher in the manually activated warning condition, compared to both no artificial sounds and automatically engaged sounds. Implications for automation usage and measurement methods are discussed and future research directions suggested. The advent of hybrid- and all-electric vehicles has created a need for artificial warning signals for pedestrian safety that place task demands on drivers. We investigated drivers' stress differences in response to varying conditions of warning signals for pedestrians. Driver stress was lower when noises were automated.

Development of a DC propulsion system for an electric vehicle

NASA Technical Reports Server (NTRS)

Kelledes, W. L.

1984-01-01

The suitability of the Eaton automatically shifted mechanical transaxle concept for use in a near-term dc powered electric vehicle is evaluated. A prototype dc propulsion system for a passenger electric vehicle was designed, fabricated, tested, installed in a modified Mercury Lynx vehicle and track tested at the contractor's site. The system consisted of a two-axis, three-speed, automatically-shifted mechanical transaxle, 15.2 Kw rated, separately excited traction motor, and a transistorized motor controller with a single chopper providing limited armature current below motor base speed and full range field control above base speed at up to twice rated motor current. The controller utilized a microprocessor to perform motor and vehicle speed monitoring and shift sequencing by means of solenoids applying hydraulic pressure to the transaxle clutches. Bench dynamometer and track testing was performed. Track testing showed best system efficiency for steady-state cruising speeds of 65-80 Km/Hz (40-50 mph). Test results include acceleration, steady speed and SAE J227A/D cycle energy consumption, braking tests and coast down to characterize the vehicle road load.

The Perfect Mate for Safe Fueling

NASA Technical Reports Server (NTRS)

2004-01-01

Referred to as the "lifeline for any space launch vehicle" by NASA Space Launch Initiative Program Manager Warren Wiley, an umbilical is a large device that transports power, communications, instrument readings, and fluids such as propellants, pressurization gases, and coolants from one source to another. Numerous launch vehicles, planetary systems, and rovers require umbilical "mating". This process is a driving factor for dependable and affordable space access. With future-generation space vehicles in mind, NASA recently designed a smart, automated method for quickly and reliably mating and demating electrical and fluid umbilical connectors. The new umbilical concept is expected to replace NASA s traditional umbilical systems that release at vehicle lift-off (T-0). The idea is to increase safety by automatically performing hazardous tasks, thus reducing potential failure modes and the time and labor hours necessary to prepare for launch. The new system will also be used as a test bed for quick disconnect development and for advance control and leak detection. It incorporates concepts such as a secondary mate plate, robotic machine vision, and compliant motor motion control, and is destined to advance usage of automated umbilicals in a variety of aerospace and commercial applications.

Adaptive road crack detection system by pavement classification.

PubMed

Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F; Sotelo, Miguel A; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

2011-01-01

This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement.

Adaptive Road Crack Detection System by Pavement Classification

PubMed Central

Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F.; Sotelo, Miguel A.; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

2011-01-01

This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement. PMID:22163717

Vision-Based Steering Control, Speed Assistance and Localization for Inner-City Vehicles

PubMed Central

Olivares-Mendez, Miguel Angel; Sanchez-Lopez, Jose Luis; Jimenez, Felipe; Campoy, Pascual; Sajadi-Alamdari, Seyed Amin; Voos, Holger

2016-01-01

Autonomous route following with road vehicles has gained popularity in the last few decades. In order to provide highly automated driver assistance systems, different types and combinations of sensors have been presented in the literature. However, most of these approaches apply quite sophisticated and expensive sensors, and hence, the development of a cost-efficient solution still remains a challenging problem. This work proposes the use of a single monocular camera sensor for an automatic steering control, speed assistance for the driver and localization of the vehicle on a road. Herein, we assume that the vehicle is mainly traveling along a predefined path, such as in public transport. A computer vision approach is presented to detect a line painted on the road, which defines the path to follow. Visual markers with a special design painted on the road provide information to localize the vehicle and to assist in its speed control. Furthermore, a vision-based control system, which keeps the vehicle on the predefined path under inner-city speed constraints, is also presented. Real driving tests with a commercial car on a closed circuit finally prove the applicability of the derived approach. In these tests, the car reached a maximum speed of 48 km/h and successfully traveled a distance of 7 km without the intervention of a human driver and any interruption. PMID:26978365

Vision-Based Steering Control, Speed Assistance and Localization for Inner-City Vehicles.

PubMed

Olivares-Mendez, Miguel Angel; Sanchez-Lopez, Jose Luis; Jimenez, Felipe; Campoy, Pascual; Sajadi-Alamdari, Seyed Amin; Voos, Holger

2016-03-11

Autonomous route following with road vehicles has gained popularity in the last few decades. In order to provide highly automated driver assistance systems, different types and combinations of sensors have been presented in the literature. However, most of these approaches apply quite sophisticated and expensive sensors, and hence, the development of a cost-efficient solution still remains a challenging problem. This work proposes the use of a single monocular camera sensor for an automatic steering control, speed assistance for the driver and localization of the vehicle on a road. Herein, we assume that the vehicle is mainly traveling along a predefined path, such as in public transport. A computer vision approach is presented to detect a line painted on the road, which defines the path to follow. Visual markers with a special design painted on the road provide information to localize the vehicle and to assist in its speed control. Furthermore, a vision-based control system, which keeps the vehicle on the predefined path under inner-city speed constraints, is also presented. Real driving tests with a commercial car on a closed circuit finally prove the applicability of the derived approach. In these tests, the car reached a maximum speed of 48 km/h and successfully traveled a distance of 7 km without the intervention of a human driver and any interruption.

Headway Deviation Effects on Bus Passenger Loads : Analysis of Tri-Met's Archived AVL-APC Data

DOT National Transportation Integrated Search

2003-01-01

In this paper we empirically analyze the relationship between transit service headway deviations and passenger loads, using archived data from Tri-Met's automatic vehicle location and automatic passenger counter systems. The analysis employs twostage...

Data visualization as a tool for improved decision making within transit agencies

DOT National Transportation Integrated Search

2007-02-01

TriMet, the regional transit provider in the Portland, OR, area has been a leader in bus transit performance monitoring using data collected via automatic vehicle location and automatic passenger counter technologies. This information is collected an...

Automatic Vehicle Location: Successful Transit Applications

DOT National Transportation Integrated Search

2002-11-01

Belief in the value of AVL is substantiated by statements of benefits contained earlier in this study. Even so, none of the study agencies are making full use of the voluminous amount of AVL data automatically recorded by the system. Efforts to make ...

Small passenger car transmission test-Chevrolet 200 transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1980-01-01

The small passenger car transmission was tested to supply electric vehicle manufacturers with technical information regarding the performance of commerically available transmissions which would enable them to design a more energy efficient vehicle. With this information the manufacturers could estimate vehicle driving range as well as speed and torque requirements for specific road load performance characteristics. A 1979 Chevrolet Model 200 automatic transmission was tested per a passenger car automatic transmission test code (SAE J651b) which required drive performance, coast performance, and no load test conditions. The transmission attained maximum efficiencies in the mid-eighty percent range for both drive performance tests and coast performance tests. Torque, speed and efficiency curves map the complete performance characteristics for Chevrolet Model 200 transmission.

A Real-Time Knowledge Based Expert System For Diagnostic Problem Solving

NASA Astrophysics Data System (ADS)

Esteva, Juan C.; Reynolds, Robert G.

1986-03-01

This paper is a preliminary report of a real-time expert system which is concerned with the detection and diagnosis of electrical deviations in on-board vehicle-based electrical systems. The target systems are being tested at radio frequencies to evaluate their capability to be operated at designed levels of efficiency in an electromagnetic environment. The measurement of this capability is known as ElectroMagnetic Compatibility (EMC). The Intelligent Deviation Diagnosis (IDD) system consists of two basic modules the Automatic Data Acquisition Module (ADAM) and the Diagnosis System (DS). In this paper only the diagnosis system is described.

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 6 2011-10-01 2011-10-01 false Automatic fire detecting system, power supply. 161.002-9 Section 161.002-9 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT...-9 Automatic fire detecting system, power supply. The power supply for an automatic fire detecting...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Automatic fire detecting system, power supply. 161.002-9 Section 161.002-9 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT...-9 Automatic fire detecting system, power supply. The power supply for an automatic fire detecting...

76 FR 53072 - Certification; Importation of Vehicles and Equipment Subject to Federal Safety, Bumper, and Theft...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-25

... used as a basis for the non-automatic suspension of an RI registration, deletes redundant text from... Part 592 as a Basis for the Non-Automatic Suspension or Revocation of an RI Registration B. Deletion of... violations of the regulations in part 592 as a basis for the non-automatic suspension or revocation of an RI...

New York State Thruway Authority automatic vehicle classification (AVC) : research report.

DOT National Transportation Integrated Search

2008-03-31

In December 2007, the N.Y.S. Thruway Authority (Thruway) concluded a Federal : funded research effort to study technology and develop a design for retrofitting : devices required in implementing a fully automated vehicle classification system i...

Crash involvement of motor vehicles in relationship to the number and severity of traffic offenses. An exploratory analysis of Dutch traffic offenses and crash data.

PubMed

Goldenbeld, Charles; Reurings, Martine; Van Norden, Yvette; Stipdonk, Henk

2013-01-01

To establish the statistical relationship between offenses and crashes when the unit of analysis is the vehicle instead of the driver, to show the influence of the severity (e.g., minor speed offenses) on this relationship, and to research whether the form of this relationship is similar in different enforcement contexts. An exploratory analysis was conducted using Dutch traffic offense and crash data. Crash data included all police-registered crashes involving motorized and registered vehicles in 2009; offense data included all non-criminal traffic offenses registered during 2005-2009 (mostly camera detected). Together these comprise an estimated 97 percent of all traffic offenses registered in this period. The analysis was done on a level of identified vehicles rather than persons. Vehicles involved in crashes were matched to vehicles involved in traffic offenses. The offense frequency distributions of registered crash involved vehicles and a random selection of vehicles was analyzed. Two comparisons were made: (1) privately owned vehicles versus company-owned vehicles and (2) vehicles for which only minor speed offenses were registered versus vehicles for which at least one major speed offense was registered. An increase in traffic offense frequency coincides with a stronger increase in relative crash involvement. This relationship was adequately described by a power function. The slightly more than linear increase in the crash risk for vehicles with only minor speed offenses suggests that minor speed offenses (<10 km/h over the limit) contributed slightly to crashes. This relationship was unlikely to be caused by increased distance traveled only. For vehicles with at least one or more major speed violation an approximately quadratic increase of crash risk with increasing speed offense frequency was found. A comparison of Dutch and Canadian data showed a much more progressive offense-crash relationship in the Dutch data. The crash involvement of vehicles increased more than linearly with the number of minor traffic violations. Thus, automatic detection of minor offenses bears relevance to safety. The substantial increase in crash rates with speed offense frequency for vehicles with at least one major speed violation suggests that these vehicles represent a specific group with a significantly increased crash risk, especially in the case of many minor offenses. The more progressive relationship between offenses and crashes in The Netherlands when compared to Canada was hypothesized to result from the higher intensity camera enforcement levels and less severe consequences in the Dutch enforcement and adjudication system.

Research on application of LADAR in ground vehicle recognition

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Shen, Zhuoxun

2009-11-01

For the requirement of many practical applications in the field of military, the research of 3D target recognition is active. The representation that captures the salient attributes of a 3D target independent of the viewing angle will be especially useful to the automatic 3D target recognition system. This paper presents a new approach of image generation based on Laser Detection and Ranging (LADAR) data. Range image of target is obtained by transformation of point cloud. In order to extract features of different ground vehicle targets and to recognize targets, zernike moment properties of typical ground vehicle targets are researched in this paper. A technique of support vector machine is applied to the classification and recognition of target. The new method of image generation and feature representation has been applied to the outdoor experiments. Through outdoor experiments, it can be proven that the method of image generation is stability, the moments are effective to be used as features for recognition, and the LADAR can be applied to the field of 3D target recognition.

Automatic detection and recognition of traffic signs in stereo images based on features and probabilistic neural networks

NASA Astrophysics Data System (ADS)

Sheng, Yehua; Zhang, Ka; Ye, Chun; Liang, Cheng; Li, Jian

2008-04-01

Considering the problem of automatic traffic sign detection and recognition in stereo images captured under motion conditions, a new algorithm for traffic sign detection and recognition based on features and probabilistic neural networks (PNN) is proposed in this paper. Firstly, global statistical color features of left image are computed based on statistics theory. Then for red, yellow and blue traffic signs, left image is segmented to three binary images by self-adaptive color segmentation method. Secondly, gray-value projection and shape analysis are used to confirm traffic sign regions in left image. Then stereo image matching is used to locate the homonymy traffic signs in right image. Thirdly, self-adaptive image segmentation is used to extract binary inner core shapes of detected traffic signs. One-dimensional feature vectors of inner core shapes are computed by central projection transformation. Fourthly, these vectors are input to the trained probabilistic neural networks for traffic sign recognition. Lastly, recognition results in left image are compared with recognition results in right image. If results in stereo images are identical, these results are confirmed as final recognition results. The new algorithm is applied to 220 real images of natural scenes taken by the vehicle-borne mobile photogrammetry system in Nanjing at different time. Experimental results show a detection and recognition rate of over 92%. So the algorithm is not only simple, but also reliable and high-speed on real traffic sign detection and recognition. Furthermore, it can obtain geometrical information of traffic signs at the same time of recognizing their types.

Automatic Recognition of Road Signs

NASA Astrophysics Data System (ADS)

Inoue, Yasuo; Kohashi, Yuuichirou; Ishikawa, Naoto; Nakajima, Masato

2002-11-01

The increase in traffic accidents is becoming a serious social problem with the recent rapid traffic increase. In many cases, the driver"s carelessness is the primary factor of traffic accidents, and the driver assistance system is demanded for supporting driver"s safety. In this research, we propose the new method of automatic detection and recognition of road signs by image processing. The purpose of this research is to prevent accidents caused by driver"s carelessness, and call attention to a driver when the driver violates traffic a regulation. In this research, high accuracy and the efficient sign detecting method are realized by removing unnecessary information except for a road sign from an image, and detect a road sign using shape features. At first, the color information that is not used in road signs is removed from an image. Next, edges except for circular and triangle ones are removed to choose sign shape. In the recognition process, normalized cross correlation operation is carried out to the two-dimensional differentiation pattern of a sign, and the accurate and efficient method for detecting the road sign is realized. Moreover, the real-time operation in a software base was realized by holding down calculation cost, maintaining highly precise sign detection and recognition. Specifically, it becomes specifically possible to process by 0.1 sec(s)/frame using a general-purpose PC (CPU: Pentium4 1.7GHz). As a result of in-vehicle experimentation, our system could process on real time and has confirmed that detection and recognition of a sign could be performed correctly.

49 CFR 393.53 - Automatic brake adjusters and brake adjustment indicators.

Code of Federal Regulations, 2010 CFR

2010-10-01

... indicators. 393.53 Section 393.53 Transportation Other Regulations Relating to Transportation (Continued... brake adjustment indicators. (a) Automatic brake adjusters (hydraulic brake systems). Each commercial... vehicle at the time it was manufactured. (c) Brake adjustment indicator (air brake systems). On each...

49 CFR 393.53 - Automatic brake adjusters and brake adjustment indicators.

Code of Federal Regulations, 2011 CFR

2011-10-01

... indicators. 393.53 Section 393.53 Transportation Other Regulations Relating to Transportation (Continued... brake adjustment indicators. (a) Automatic brake adjusters (hydraulic brake systems). Each commercial... vehicle at the time it was manufactured. (c) Brake adjustment indicator (air brake systems). On each...

Using deep learning in image hyper spectral segmentation, classification, and detection

NASA Astrophysics Data System (ADS)

Zhao, Xiuying; Su, Zhenyu

2018-02-01

Recent years have shown that deep learning neural networks are a valuable tool in the field of computer vision. Deep learning method can be used in applications like remote sensing such as Land cover Classification, Detection of Vehicle in Satellite Images, Hyper spectral Image classification. This paper addresses the use of the deep learning artificial neural network in Satellite image segmentation. Image segmentation plays an important role in image processing. The hue of the remote sensing image often has a large hue difference, which will result in the poor display of the images in the VR environment. Image segmentation is a pre processing technique applied to the original images and splits the image into many parts which have different hue to unify the color. Several computational models based on supervised, unsupervised, parametric, probabilistic region based image segmentation techniques have been proposed. Recently, one of the machine learning technique known as, deep learning with convolution neural network has been widely used for development of efficient and automatic image segmentation models. In this paper, we focus on study of deep neural convolution network and its variants for automatic image segmentation rather than traditional image segmentation strategies.

The Vehicle Control Systems Branch at the Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Barret, Chris

1990-01-01

This paper outlines the responsibility of the Vehicle Control Systems Branch at the Marshall Space Flight Center (MSFC) to analyze, evaluate, define, design, verify, and specify requirements for advanced launch vehicles and related space projects, and to conduct research in advanced flight control concepts. Attention is given to branch responsibilities which include Shuttle-C, Shuttle-C Block II, Shuttle-Z, lunar cargo launch vehicles, Mars cargo launch vehicles, orbital maneuvering vehicle, automatic docking, tethered satellite, aeroassisted flight experiment, and solid rocket booster parachute recovery system design.

Behavioral aspects of automatic vehicle guidance : relationship between headway and driver comfort

DOT National Transportation Integrated Search

1997-01-01

Automation of road traffic has the potential to greatly improve the performance of traffic systems. The acceptance of automated driving may play an important role in the feasibility of automated vehicle guidance (AVG), comparable to automated highway...

Integrated corridor management transit vehicle real-time data demonstration: Dallas case study

DOT National Transportation Integrated Search

2014-12-01

As part of the U.S. Department of Transportations Integrated Corridor Management (ICM) Initiative, Dallas Area Rapid Transit (DART) purchased new automatic passenger counter (APC) technology for its Red and Orange line light rail vehicles to provi...

Development and preliminary testing of an automatic turning movements identification system : final report, February 2010.

DOT National Transportation Integrated Search

2010-02-01

It is important for many applications, such as intersection delay estimation and adaptive signal : control, to obtain vehicle turning movement information at signalized intersections. However, : vehicle turning movement information is very time consu...

Digital Map Requirements For Automatic Vehicle Location

DOT National Transportation Integrated Search

1998-12-01

New Jersey Transit (NJT) is currently investigating acquisition of an automated vehicle locator (AVL) system. The purpose of the AVL system is to monitor the location of buses. Knowing the location of a bus enables the agency to manage the bus fleet ...

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories.

PubMed

Yang, Wei; Ai, Tinghua; Lu, Wei

2018-04-19

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories

PubMed Central

Yang, Wei

2018-01-01

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality. PMID:29671792

Centralized Alert-Processing and Asset Planning for Sensorwebs

NASA Technical Reports Server (NTRS)

Castano, Rebecca; Chien, Steve A.; Rabideau, Gregg R.; Tang, Benyang

2010-01-01

A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly.

Contrast, size, and orientation-invariant target detection in infrared imagery

NASA Astrophysics Data System (ADS)

Zhou, Yi-Tong; Crawshaw, Richard D.

1991-08-01

Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.

Flash LIDAR Emulator for HIL Simulation

NASA Technical Reports Server (NTRS)

Brewster, Paul F.

2010-01-01

NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project is building a system for detecting hazards and automatically landing controlled vehicles safely anywhere on the Moon. The Flash Light Detection And Ranging (LIDAR) sensor is used to create on-the-fly a 3D map of the unknown terrain for hazard detection. As part of the ALHAT project, a hardware-in-the-loop (HIL) simulation testbed was developed to test the data processing, guidance, and navigation algorithms in real-time to prove their feasibility for flight. Replacing the Flash LIDAR camera with an emulator in the testbed provided a cheaper, safer, more feasible way to test the algorithms in a controlled environment. This emulator must have the same hardware interfaces as the LIDAR camera, have the same performance characteristics, and produce images similar in quality to the camera. This presentation describes the issues involved and the techniques used to create a real-time flash LIDAR emulator to support HIL simulation.

Detection of Road Surface States from Tire Noise Using Neural Network Analysis

NASA Astrophysics Data System (ADS)

Kongrattanaprasert, Wuttiwat; Nomura, Hideyuki; Kamakura, Tomoo; Ueda, Koji

This report proposes a new processing method for automatically detecting the states of road surfaces from tire noises of passing vehicles. In addition to multiple indicators of the signal features in the frequency domain, we propose a few feature indicators in the time domain to successfully classify the road states into four categories: snowy, slushy, wet, and dry states. The method is based on artificial neural networks. The proposed classification is carried out in multiple neural networks using learning vector quantization. The outcomes of the networks are then integrated by the voting decision-making scheme. Experimental results obtained from recorded signals for ten days in the snowy season demonstrated that an accuracy of approximately 90% can be attained for predicting road surface states using only tire noise data.

Autonomous navigation of structured city roads

NASA Astrophysics Data System (ADS)

Aubert, Didier; Kluge, Karl C.; Thorpe, Chuck E.

1991-03-01

Autonomous road following is a domain which spans a range of complexity from poorly defined unmarked dirt roads to well defined well marked highly struc-. tured highways. The YARF system (for Yet Another Road Follower) is designed to operate in the middle of this range of complexity driving on urban streets. Our research program has focused on the use of feature- and situation-specific segmentation techniques driven by an explicit model of the appearance and geometry of the road features in the environment. We report results in robust detection of white and yellow painted stripes fitting a road model to detected feature locations to determine vehicle position and local road geometry and automatic location of road features in an initial image. We also describe our planned extensions to include intersection navigation.

A unique concept for automatically controlling the braking action of wheeled vehicles during minimum distance stops

NASA Technical Reports Server (NTRS)

Barthlome, D. E.

1975-01-01

Test results of a unique automatic brake control system are outlined and a comparison is made of its mode of operation to that of an existing skid control system. The purpose of the test system is to provide automatic control of braking action such that hydraulic brake pressure is maintained at a near constant, optimum value during minimum distance stops.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve the speed and orientation efficiency of target identification effectively, and validate the feasibility of this method primarily.

A comparison of the comfort and convenience of automatic safety belt systems among selected 1988-1989 model year automobiles

DOT National Transportation Integrated Search

1989-06-01

Author's abstract: A nonrandom sample of 120 disproportionately short, tall, and overweight drivers compared the comfort and convenience of the automatic safety belt systems used in seventeen automobiles. Nine vehicles had motorized shoulder belts wi...

Innovative telecommunications for law enforcement

NASA Technical Reports Server (NTRS)

Sohn, R. L.

1976-01-01

The operation of computer-aided dispatch, mobile digital communications, and automatic vehicle location systems used in law enforcement is discussed, and characteristics of systems used by different agencies are compared. With reference to computer-aided dispatch systems, the data base components, dispatcher work load, extent of usage, and design trends are surveyed. The capabilities, levels of communication, and traffic load of mobile digital communications systems are examined. Different automatic vehicle location systems are distinguished, and two systems are evaluated. Other aspects of the application of innovative technology to operational command, control, and communications systems for law enforcement agencies are described.

Highway extraction from high resolution aerial photography using a geometric active contour model

NASA Astrophysics Data System (ADS)

Niu, Xutong

Highway extraction and vehicle detection are two of the most important steps in traffic-flow analysis from multi-frame aerial photographs. The traditional method of deriving traffic flow trajectories relies on manual vehicle counting from a sequence of aerial photographs, which is tedious and time-consuming. This research presents a new framework for semi-automatic highway extraction. The basis of the new framework is an improved geometric active contour (GAC) model. This novel model seeks to minimize an objective function that transforms a problem of propagation of regular curves into an optimization problem. The implementation of curve propagation is based on level set theory. By using an implicit representation of a two-dimensional curve, a level set approach can be used to deal with topological changes naturally, and the output is unaffected by different initial positions of the curve. However, the original GAC model, on which the new model is based, only incorporates boundary information into the curve propagation process. An error-producing phenomenon called leakage is inevitable wherever there is an uncertain weak edge. In this research, region-based information is added as a constraint into the original GAC model, thereby, giving this proposed method the ability of integrating both boundary and region-based information during the curve propagation. Adding the region-based constraint eliminates the leakage problem. This dissertation applies the proposed augmented GAC model to the problem of highway extraction from high-resolution aerial photography. First, an optimized stopping criterion is designed and used in the implementation of the GAC model. It effectively saves processing time and computations. Second, a seed point propagation framework is designed and implemented. This framework incorporates highway extraction, tracking, and linking into one procedure. A seed point is usually placed at an end node of highway segments close to the boundary of the image or at a position where possible blocking may occur, such as at an overpass bridge or near vehicle crowds. These seed points can be automatically propagated throughout the entire highway network. During the process, road center points are also extracted, which introduces a search direction for solving possible blocking problems. This new framework has been successfully applied to highway network extraction from a large orthophoto mosaic. In the process, vehicles on the highway extracted from mosaic were detected with an 83% success rate.

40 CFR 1051.320 - What happens if one of my production-line vehicles or engines fails to meet emission standards?

Code of Federal Regulations, 2012 CFR

2012-07-01

...-line vehicles or engines fails to meet emission standards? 1051.320 Section 1051.320 Protection of... of my production-line vehicles or engines fails to meet emission standards? (a) If you have a... standards (see § 1051.315(a)), the certificate of conformity is automatically suspended for that failing...

40 CFR 1051.320 - What happens if one of my production-line vehicles or engines fails to meet emission standards?

Code of Federal Regulations, 2011 CFR

2011-07-01

...-line vehicles or engines fails to meet emission standards? 1051.320 Section 1051.320 Protection of... of my production-line vehicles or engines fails to meet emission standards? (a) If you have a... standards (see § 1051.315(a)), the certificate of conformity is automatically suspended for that failing...

77 FR 15843 - Petition for Exemption From the Vehicle Theft Prevention Standard; Nissan

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-16

... vehicle and the vehicle itself from being stolen when the back door and all of the side doors are closed... automatically when the ignition key is turned to the ``OFF'' position and all the doors are closed and locked through the use of the key or the remote control mechanism. Deactivation occurs when all the doors are...

Predicting crash-relevant violations at stop sign-controlled intersections for the development of an intersection driver assistance system.

PubMed

Scanlon, John M; Sherony, Rini; Gabler, Hampton C

2016-09-01

Intersection crashes resulted in over 5,000 fatalities in the United States in 2014. Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that seek to help drivers safely traverse intersections. I-ADAS uses onboard sensors to detect oncoming vehicles and, in the event of an imminent crash, can either alert the driver or take autonomous evasive action. The objective of this study was to develop and evaluate a predictive model for detecting whether a stop sign violation was imminent. Passenger vehicle intersection approaches were extracted from a data set of typical driver behavior (100-Car Naturalistic Driving Study) and violations (event data recorders downloaded from real-world crashes) and were assigned weighting factors based on real-world frequency. A k-fold cross-validation procedure was then used to develop and evaluate 3 hypothetical stop sign warning algorithms (i.e., early, intermediate, and delayed) for detecting an impending violation during the intersection approach. Violation detection models were developed using logistic regression models that evaluate likelihood of a violation at various locations along the intersection approach. Two potential indicators of driver intent to stop-that is, required deceleration parameter (RDP) and brake application-were used to develop the predictive models. The earliest violation detection opportunity was then evaluated for each detection algorithm in order to (1) evaluate the violation detection accuracy and (2) compare braking demand versus maximum braking capabilities. A total of 38 violating and 658 nonviolating approaches were used in the analysis. All 3 algorithms were able to detect a violation at some point during the intersection approach. The early detection algorithm, as designed, was able to detect violations earlier than all other algorithms during the intersection approach but gave false alarms for 22.3% of approaches. In contrast, the delayed detection algorithm sacrificed some time for detecting violations but was able to substantially reduce false alarms to only 3.3% of all nonviolating approaches. Given good surface conditions (maximum braking capabilities = 0.8 g) and maximum effort, most drivers (55.3-71.1%) would be able to stop the vehicle regardless of the detection algorithm. However, given poor surface conditions (maximum braking capabilities = 0.4 g), few drivers (10.5-26.3%) would be able to stop the vehicle. Automatic emergency braking (AEB) would allow for early braking prior to driver reaction. If equipped with an AEB system, the results suggest that, even for the poor surface conditions scenario, over one half (55.3-65.8%) of the vehicles could have been stopped. This study demonstrates the potential of I-ADAS to incorporate a stop sign violation detection algorithm. Repeating the analysis on a larger, more extensive data set will allow for the development of a more comprehensive algorithm to further validate the findings.

Automatic generation of the non-holonomic equations of motion for vehicle stability analysis

NASA Astrophysics Data System (ADS)

Minaker, B. P.; Rieveley, R. J.

2010-09-01

The mathematical analysis of vehicle stability has been utilised as an important tool in the design, development, and evaluation of vehicle architectures and stability controls. This paper presents a novel method for automatic generation of the linearised equations of motion for mechanical systems that is well suited to vehicle stability analysis. Unlike conventional methods for generating linearised equations of motion in standard linear second order form, the proposed method allows for the analysis of systems with non-holonomic constraints. In the proposed method, the algebraic constraint equations are eliminated after linearisation and reduction to first order. The described method has been successfully applied to an assortment of classic dynamic problems of varying complexity including the classic rolling coin, the planar truck-trailer, and the bicycle, as well as in more recent problems such as a rotor-stator and a benchmark road vehicle with suspension. This method has also been applied in the design and analysis of a novel three-wheeled narrow tilting vehicle with zero roll-stiffness. An application for determining passively stable configurations using the proposed method together with a genetic search algorithm is detailed. The proposed method and software implementation has been shown to be robust and provides invaluable conceptual insight into the stability of vehicles and mechanical systems.

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

EPA and California Air Resources Board Approve Remedy to Reduce Excess NOx Emissions from Automatic Transmission “Generation 2” 2.0-Liter Diesel Vehicles

EPA Pesticide Factsheets

On May 17, 2017, EPA and the California Air Resources Board (CARB) approved an emissions modification proposed by Volkswagen that will reduce NOx emissions from automatic transmission diesel Passats for model years 2012-2014.

Automatic Vehicle Location successful transit applications : a cross-cutting study : improving service and safety

DOT National Transportation Integrated Search

2000-08-01

Belief in the value of AVL is substantiated by statements of benefits contained earlier in this study. Even so, none of the study agencies are making full use of the voluminous amount of AVL data automatically recorded by the system. Efforts to make ...

Large scale track analysis for wide area motion imagery surveillance

NASA Astrophysics Data System (ADS)

van Leeuwen, C. J.; van Huis, J. R.; Baan, J.

2016-10-01

Wide Area Motion Imagery (WAMI) enables image based surveillance of areas that can cover multiple square kilometers. Interpreting and analyzing information from such sources, becomes increasingly time consuming as more data is added from newly developed methods for information extraction. Captured from a moving Unmanned Aerial Vehicle (UAV), the high-resolution images allow detection and tracking of moving vehicles, but this is a highly challenging task. By using a chain of computer vision detectors and machine learning techniques, we are capable of producing high quality track information of more than 40 thousand vehicles per five minutes. When faced with such a vast number of vehicular tracks, it is useful for analysts to be able to quickly query information based on region of interest, color, maneuvers or other high-level types of information, to gain insight and find relevant activities in the flood of information. In this paper we propose a set of tools, combined in a graphical user interface, which allows data analysts to survey vehicles in a large observed area. In order to retrieve (parts of) images from the high-resolution data, we developed a multi-scale tile-based video file format that allows to quickly obtain only a part, or a sub-sampling of the original high resolution image. By storing tiles of a still image according to a predefined order, we can quickly retrieve a particular region of the image at any relevant scale, by skipping to the correct frames and reconstructing the image. Location based queries allow a user to select tracks around a particular region of interest such as landmark, building or street. By using an integrated search engine, users can quickly select tracks that are in the vicinity of locations of interest. Another time-reducing method when searching for a particular vehicle, is to filter on color or color intensity. Automatic maneuver detection adds information to the tracks that can be used to find vehicles based on their behavior.

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

Development of a unified control synthesis methodology for complex and/or non-conventional flight vehicles, and prediction techniques for the handling characteristics of such vehicles are reported. Identification of pilot dynamics and objectives, using time domain and frequency domain methods is proposed.

Robust automatic control system of vessel descent-rise device for plant with distributed parameters “cable – towed underwater vehicle”

NASA Astrophysics Data System (ADS)

Chupina, K. V.; Kataev, E. V.; Khannanov, A. M.; Korshunov, V. N.; Sennikov, I. A.

2018-05-01

The paper is devoted to a problem of synthesis of the robust control system for a distributed parameters plant. The vessel descent-rise device has a heave compensation function for stabilization of the towed underwater vehicle on a set depth. A sea state code, parameters of the underwater vehicle and cable vary during underwater operations, the vessel heave is a stochastic process. It means that the plant and external disturbances have uncertainty. That is why it is necessary to use the robust theory for synthesis of an automatic control system, but without use of traditional methods of optimization, because this cable has distributed parameters. The offered technique has allowed one to design an effective control system for stabilization of immersion depth of the towed underwater vehicle for various degrees of sea roughness and to provide its robustness to deviations of parameters of the vehicle and cable’s length.

Change detection on UGV patrols with respect to a reference tour using VIS imagery

NASA Astrophysics Data System (ADS)

Müller, Thomas

2015-05-01

Autonomous driving robots (UGVs, Unmanned Ground Vehicles) equipped with visual-optical (VIS) cameras offer a high potential to automatically detect suspicious occurrences and dangerous or threatening situations on patrol. In order to explore this potential, the scene of interest is recorded first on a reference tour representing the 'everything okay' situation. On further patrols changes are detected with respect to the reference in a two step processing scheme. In the first step, an image retrieval is done to find the reference images that are closest to the current camera image on patrol. This is done efficiently based on precalculated image-to-image registrations of the reference by optimizing image overlap in a local reference search (after a global search when that is needed). In the second step, a robust spatio-temporal change detection is performed that widely compensates 3-D parallax according to variations of the camera position. Various results document the performance of the presented approach.

Automatic road sign detecion and classification based on support vector machines and HOG descriptos

NASA Astrophysics Data System (ADS)

Adam, A.; Ioannidis, C.

2014-05-01

This paper examines the detection and classification of road signs in color-images acquired by a low cost camera mounted on a moving vehicle. A new method for the detection and classification of road signs is proposed based on color based detection, in order to locate regions of interest. Then, a circular Hough transform is applied to complete detection taking advantage of the shape properties of the road signs. The regions of interest are finally represented using HOG descriptors and are fed into trained Support Vector Machines (SVMs) in order to be recognized. For the training procedure, a database with several training examples depicting Greek road sings has been developed. Many experiments have been conducted and are presented, to measure the efficiency of the proposed methodology especially under adverse weather conditions and poor illumination. For the experiments training datasets consisting of different number of examples were used and the results are presented, along with some possible extensions of this work.

Automated mixed traffic vehicle control and scheduling study

NASA Technical Reports Server (NTRS)

Peng, T. K. C.; Chon, K.

1976-01-01

The operation and the expected performance of a proposed automatic guideway transit system which uses low speed automated mixed traffic vehicles (AMTVs) were analyzed. Vehicle scheduling and headway control policies were evaluated with a transit system simulation model. The effect of mixed traffic interference on the average vehicle speed was examined with a vehicle pedestrian interface model. Control parameters regulating vehicle speed were evaluated for safe stopping and passenger comfort. Some preliminary data on the cost and operation of an experimental AMTV system are included. These data were the result of a separate task conducted at JPL, and were included as background information.

Hazardous sign detection for safety applications in traffic monitoring

NASA Astrophysics Data System (ADS)

Benesova, Wanda; Kottman, Michal; Sidla, Oliver

2012-01-01

The transportation of hazardous goods in public streets systems can pose severe safety threats in case of accidents. One of the solutions for these problems is an automatic detection and registration of vehicles which are marked with dangerous goods signs. We present a prototype system which can detect a trained set of signs in high resolution images under real-world conditions. This paper compares two different methods for the detection: bag of visual words (BoW) procedure and our approach presented as pairs of visual words with Hough voting. The results of an extended series of experiments are provided in this paper. The experiments show that the size of visual vocabulary is crucial and can significantly affect the recognition success rate. Different code-book sizes have been evaluated for this detection task. The best result of the first method BoW was 67% successfully recognized hazardous signs, whereas the second method proposed in this paper - pairs of visual words and Hough voting - reached 94% of correctly detected signs. The experiments are designed to verify the usability of the two proposed approaches in a real-world scenario.

Automatic control of a robotic vehicle

NASA Technical Reports Server (NTRS)

Mcreynolds, S. R.

1976-01-01

Over the last several years Jet Propulsion Laboratory has been engaged in a project to develop some of the technology required to build a robotic vehicle for exploring planetary surfaces. An overview of hardware and software being developed for this project is given. Particular emphasis is placed on the description of the current design for the Vehicle System required for locomotion and the path planning algorithm.

Integrated Inverter And Battery Charger

NASA Technical Reports Server (NTRS)

Rippel, Wally E.

1988-01-01

Circuit combines functions of dc-to-ac inversion (for driving ac motor in battery-powered vehicle) and ac-to-dc conversion (for charging battery from ac line when vehicle not in use). Automatically adapts to either mode. Design of integrated inverter/charger eliminates need for duplicate components, saves space, reduces weight and cost of vehicle. Advantages in other applications : load-leveling systems, standby ac power systems, and uninterruptible power supplies.

Autonomous RPRV Navigation, Guidance and Control

NASA Technical Reports Server (NTRS)

Johnston, Donald E.; Myers, Thomas T.; Zellner, John W.

1983-01-01

Dryden Flight Research Center has the responsibility for flight testing of advanced remotely piloted research vehicles (RPRV) to explore highly maneuverable aircraft technology, and to test advanced structural concepts, and related aeronautical technologies which can yield important research results with significant cost benefits. The primary purpose is to provide the preliminary design of an upgraded automatic approach and landing control system and flight director display to improve landing performance and reduce pilot workload. A secondary purpose is to determine the feasibility of an onboard autonomous navigation, orbit, and landing capability for safe vehicle recovery in the event of loss of telemetry uplink communication with the vehicles. The current RPRV approach and landing method, the proposed automatic and manual approach and autoland system, and an autonomous navigation, orbit, and landing system concept which is based on existing operational technology are described.

Application of the SNoW machine learning paradigm to a set of transportation imaging problems

NASA Astrophysics Data System (ADS)

Paul, Peter; Burry, Aaron M.; Wang, Yuheng; Kozitsky, Vladimir

2012-01-01

Machine learning methods have been successfully applied to image object classification problems where there is clear distinction between classes and where a comprehensive set of training samples and ground truth are readily available. The transportation domain is an area where machine learning methods are particularly applicable, since the classification problems typically have well defined class boundaries and, due to high traffic volumes in most applications, massive roadway data is available. Though these classes tend to be well defined, the particular image noises and variations can be challenging. Another challenge is the extremely high accuracy typically required in most traffic applications. Incorrect assignment of fines or tolls due to imaging mistakes is not acceptable in most applications. For the front seat vehicle occupancy detection problem, classification amounts to determining whether one face (driver only) or two faces (driver + passenger) are detected in the front seat of a vehicle on a roadway. For automatic license plate recognition, the classification problem is a type of optical character recognition problem encompassing multiple class classification. The SNoW machine learning classifier using local SMQT features is shown to be successful in these two transportation imaging applications.

Job expansion : an additional benefit of a computer aided dispatch/automatic vehicle locator (CAD/AVL) system

DOT National Transportation Integrated Search

2000-03-01

The Denver Regional Transportation District (RTD) acquired a CAD/AVL system that became fully operational in 1996. The CAD/AVL system added radio channels and covert alarms in buses, located vehicles in real time, and monitored schedule adherence. Th...

Evaluation of experimental UAV video change detection

NASA Astrophysics Data System (ADS)

Bartelsen, J.; Saur, G.; Teutsch, C.

2016-10-01

During the last ten years, the availability of images acquired from unmanned aerial vehicles (UAVs) has been continuously increasing due to the improvements and economic success of flight and sensor systems. From our point of view, reliable and automatic image-based change detection may contribute to overcoming several challenging problems in military reconnaissance, civil security, and disaster management. Changes within a scene can be caused by functional activities, i.e., footprints or skid marks, excavations, or humidity penetration; these might be recognizable in aerial images, but are almost overlooked when change detection is executed manually. With respect to the circumstances, these kinds of changes may be an indication of sabotage, terroristic activity, or threatening natural disasters. Although image-based change detection is possible from both ground and aerial perspectives, in this paper we primarily address the latter. We have applied an extended approach to change detection as described by Saur and Kruger,1 and Saur et al.2 and have built upon the ideas of Saur and Bartelsen.3 The commercial simulation environment Virtual Battle Space 3 (VBS3) is used to simulate aerial "before" and "after" image acquisition concerning flight path, weather conditions and objects within the scene and to obtain synthetic videos. Video frames, which depict the same part of the scene, including "before" and "after" changes and not necessarily from the same perspective, are registered pixel-wise against each other by a photogrammetric concept, which is based on a homography. The pixel-wise registration is used to apply an automatic difference analysis, which, to a limited extent, is able to suppress typical errors caused by imprecise frame registration, sensor noise, vegetation and especially parallax effects. The primary concern of this paper is to seriously evaluate the possibilities and limitations of our current approach for image-based change detection with respect to the flight path, viewpoint change and parametrization. Hence, based on synthetic "before" and "after" videos of a simulated scene, we estimated the precision and recall of automatically detected changes. In addition and based on our approach, we illustrate the results showing the change detection in short, but real video sequences. Future work will improve the photogrammetric approach for frame registration, and extensive real video material, capable of change detection, will be acquired.

The ac propulsion system for an electric vehicle, phase 1

NASA Astrophysics Data System (ADS)

Geppert, S.

1981-08-01

A functional prototype of an electric vehicle ac propulsion system was built consisting of a 18.65 kW rated ac induction traction motor, pulse width modulated (PWM) transistorized inverter, two speed mechanically shifted automatic transmission, and an overall drive/vehicle controller. Design developmental steps, and test results of individual components and the complex system on an instrumented test frame are described. Computer models were developed for the inverter, motor and a representative vehicle. A preliminary reliability model and failure modes effects analysis are given.

The ac propulsion system for an electric vehicle, phase 1

NASA Technical Reports Server (NTRS)

Geppert, S.

1981-01-01

A functional prototype of an electric vehicle ac propulsion system was built consisting of a 18.65 kW rated ac induction traction motor, pulse width modulated (PWM) transistorized inverter, two speed mechanically shifted automatic transmission, and an overall drive/vehicle controller. Design developmental steps, and test results of individual components and the complex system on an instrumented test frame are described. Computer models were developed for the inverter, motor and a representative vehicle. A preliminary reliability model and failure modes effects analysis are given.

Automotive Control Systems: For Engine, Driveline, and Vehicle

NASA Astrophysics Data System (ADS)

Kiencke, Uwe; Nielsen, Lars

Advances in automotive control systems continue to enhance safety and comfort and to reduce fuel consumption and emissions. Reflecting the trend to optimization through integrative approaches for engine, driveline, and vehicle control, this valuable book enables control engineers to understand engine and vehicle models necessary for controller design, and also introduces mechanical engineers to vehicle-specific signal processing and automatic control. The emphasis on measurement, comparisons between performance and modeling, and realistic examples derive from the authors' unique industrial experience

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample extraction smoke detection systems, watchman's supervisory systems, and combinations of these systems. (b) Automatic fire detecting systems. For the purpose of this subpart, automatic fire and smoke detecting...

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample extraction smoke detection systems, watchman's supervisory systems, and combinations of these systems. (b) Automatic fire detecting systems. For the purpose of this subpart, automatic fire and smoke detecting...

Automatic control of the Skylab Astronaut Maneuvering Research Vehicle.

NASA Technical Reports Server (NTRS)

Murtagh, T. B.; Goodwin, M. A.; Greenlee, J. E.; Whitsett , C. E.

1973-01-01

The two automatic control modes of the Astronaut Maneuvering Research Vehicle (AMRV) are analyzed: the control moment gyro (CMG) and the rate gyro (RG). The AMRV is an autonomous maneuvering unit which translates and rotates the pilot by means of hand-controller input commands. The CMG normal operation, desaturation, and cage/lock dynamics are described in terms of a realistic AMRV mass property configuration. No propellant is used for normal operation in the CMG mode, and the maximum rotation rate is 5 deg/sec about each AMRV axis. The RG attitude maneuvering and limit cycle submode dynamic are described in terms of the same AMRV mass property configuration.

76 FR 11415 - Federal Motor Vehicle Safety Standards; Power-Operated Window, Partition, and Roof Panel Systems

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-02

... automatic reversal systems (ARS) for power windows and to make a final decision. The agency has decided not... requirements for automatic reversal systems (ARS) and are withdrawing our 2009 proposal regarding ARS. This... of proposed rulemaking (NPRM) proposing new requirements for ARS. The proposal discussed the agency's...

Research on regional intrusion prevention and control system based on target tracking

NASA Astrophysics Data System (ADS)

Liu, Yanfei; Wang, Jieling; Jiang, Ke; He, Yanhui; Wu, Zhilin

2017-08-01

In view of the fact that China’s border is very long and the border prevention and control measures are single, we designed a regional intrusion prevention and control system which based on target-tracking. The system consists of four parts: solar panel, radar, electro-optical equipment, unmanned aerial vehicle and intelligent tracking platform. The solar panel provides independent power for the entire system. The radar detects the target in real time and realizes the high precision positioning of suspicious targets, then through the linkage of electro-optical equipment, it can achieve full-time automatic precise tracking of targets. When the target appears within the range of detection, the drone will be launched to continue the tracking. The system is mainly to realize the full time, full coverage, whole process integration and active realtime control of the border area.

Alternating-Current Motor Drive for Electric Vehicles

NASA Technical Reports Server (NTRS)

Krauthamer, S.; Rippel, W. E.

1982-01-01

New electric drive controls speed of a polyphase as motor by varying frequency of inverter output. Closed-loop current-sensing circuit automatically adjusts frequency of voltage-controlled oscillator that controls inverter frequency, to limit starting and accelerating surges. Efficient inverter and ac motor would give electric vehicles extra miles per battery charge.

Computer systems for automatic earthquake detection

USGS Publications Warehouse

Stewart, S.W.

1974-01-01

U.S Geological Survey seismologists in Menlo park, California, are utilizing the speed, reliability, and efficiency of minicomputers to monitor seismograph stations and to automatically detect earthquakes. An earthquake detection computer system, believed to be the only one of its kind in operation, automatically reports about 90 percent of all local earthquakes recorded by a network of over 100 central California seismograph stations. The system also monitors the stations for signs of malfunction or abnormal operation. Before the automatic system was put in operation, all of the earthquakes recorded had to be detected by manually searching the records, a time-consuming process. With the automatic detection system, the stations are efficiently monitored continuously. 

Landmark-aided localization for air vehicles using learned object detectors

NASA Astrophysics Data System (ADS)

DeAngelo, Mark Patrick

This research presents two methods to localize an aircraft without GPS using fixed landmarks observed from an optical sensor. Onboard absolute localization is useful for vehicle navigation free from an external network. The objective is to achieve practical navigation performance using available autopilot hardware and a downward pointing camera. The first method uses computer vision cascade object detectors, which are trained to detect predetermined, distinct landmarks prior to a flight. The first method also concurrently explores aircraft localization using roads between landmark updates. During a flight, the aircraft navigates with attitude, heading, airspeed, and altitude measurements and obtains measurement updates when landmarks are detected. The sensor measurements and landmark coordinates extracted from the aircraft's camera images are combined into an unscented Kalman filter to obtain an estimate of the aircraft's position and wind velocities. The second method uses computer vision object detectors to detect abundant generic landmarks referred as buildings, fields, trees, and road intersections from aerial perspectives. Various landmark attributes and spatial relationships to other landmarks are used to help associate observed landmarks with reference landmarks. The computer vision algorithms automatically extract reference landmarks from maps, which are processed offline before a flight. During a flight, the aircraft navigates with attitude, heading, airspeed, and altitude measurements and obtains measurement corrections by processing aerial photos with similar generic landmark detection techniques. The method also combines sensor measurements and landmark coordinates into an unscented Kalman filter to obtain an estimate of the aircraft's position and wind velocities.

X33 Reusable Launch Vehicle Control on Sliding Modes: Concepts for a Control System Development

NASA Technical Reports Server (NTRS)

Shtessel, Yuri B.

1998-01-01

Control of the X33 reusable launch vehicle is considered. The launch control problem consists of automatic tracking of the launch trajectory which is assumed to be optimally precalculated. It requires development of a reliable, robust control algorithm that can automatically adjust to some changes in mission specifications (mass of payload, target orbit) and the operating environment (atmospheric perturbations, interconnection perturbations from the other subsystems of the vehicle, thrust deficiencies, failure scenarios). One of the effective control strategies successfully applied in nonlinear systems is the Sliding Mode Control. The main advantage of the Sliding Mode Control is that the system's state response in the sliding surface remains insensitive to certain parameter variations, nonlinearities and disturbances. Employing the time scaling concept, a new two (three)-loop structure of the control system for the X33 launch vehicle was developed. Smoothed sliding mode controllers were designed to robustly enforce the given closed-loop dynamics. Simulations of the 3-DOF model of the X33 launch vehicle with the table-look-up models for Euler angle reference profiles and disturbance torque profiles showed a very accurate, robust tracking performance.

Vision-based vehicle detection and tracking algorithm design

NASA Astrophysics Data System (ADS)

Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

2009-12-01

The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

Adherent Raindrop Modeling, Detectionand Removal in Video.

PubMed

You, Shaodi; Tan, Robby T; Kawakami, Rei; Mukaigawa, Yasuhiro; Ikeuchi, Katsushi

2016-09-01

Raindrops adhered to a windscreen or window glass can significantly degrade the visibility of a scene. Modeling, detecting and removing raindrops will, therefore, benefit many computer vision applications, particularly outdoor surveillance systems and intelligent vehicle systems. In this paper, a method that automatically detects and removes adherent raindrops is introduced. The core idea is to exploit the local spatio-temporal derivatives of raindrops. To accomplish the idea, we first model adherent raindrops using law of physics, and detect raindrops based on these models in combination with motion and intensity temporal derivatives of the input video. Having detected the raindrops, we remove them and restore the images based on an analysis that some areas of raindrops completely occludes the scene, and some other areas occlude only partially. For partially occluding areas, we restore them by retrieving as much as possible information of the scene, namely, by solving a blending function on the detected partially occluding areas using the temporal intensity derivative. For completely occluding areas, we recover them by using a video completion technique. Experimental results using various real videos show the effectiveness of our method.

First tests of a multi-wavelength mini-DIAL system for the automatic detection of greenhouse gases

NASA Astrophysics Data System (ADS)

Parracino, S.; Gelfusa, M.; Lungaroni, M.; Murari, A.; Peluso, E.; Ciparisse, J. F.; Malizia, A.; Rossi, R.; Ventura, P.; Gaudio, P.

2017-10-01

Considering the increase of atmospheric pollution levels in our cities, due to emissions from vehicles and domestic heating, and the growing threat of terrorism, it is necessary to develop instrumentation and gather know-how for the automatic detection and measurement of dangerous substances as quickly and far away as possible. The Multi- Wavelength DIAL, an extension of the conventional DIAL technique, is one of the most powerful remote sensing methods for the identification of multiple substances and seems to be a promising solution compared to existing alternatives. In this paper, first in-field tests of a smart and fully automated Multi-Wavelength mini-DIAL will be presented and discussed in details. The recently developed system, based on a long-wavelength infrared (IR-C) CO2 laser source, has the potential of giving an early warning, whenever something strange is found in the atmosphere, followed by identification and simultaneous concentration measurements of many chemical species, ranging from the most important Greenhouse Gases (GHG) to other harmful Volatile Organic Compounds (VOCs). Preliminary studies, regarding the fingerprint of the investigated substances, have been carried out by cross-referencing database of infrared (IR) spectra, obtained using in-cell measurements, and typical Mixing Ratios in the examined region, extrapolated from the literature. First experiments in atmosphere have been performed into a suburban and moderately-busy area of Rome. Moreover, to optimize the automatic identification of the harmful species to be recognized on the basis of in cell measurements of the absorption coefficient spectra, an advanced multivariate statistical method for classification has been developed and tested.

The Design and Operation of Suborbital Low Cost and Low Risk Vehicle to the Edge of Space (SOLVES)

NASA Astrophysics Data System (ADS)

Ridzuan Zakaria, Norul; Nasrun, Nasri; Rashidy Zulkifi, Mohd; Izmir Yamin, Mohd; Othman, Jamaludin; Rafidi Zakaria, Norul

2013-09-01

Inclusive in the planning of Spaceport Malaysia are 2 local suborbital vehicles development. One of the vehicles is called SOLVES or Suborbital Low Cost and Low Risk Vehicle to the Edge of Space. The emphasis on the design and operation of SOLVES is green and robotic technology, where both green technology and robotic technology are used to protect the environment and enhance safety. As SOLVES climbs, its center of gravity stabilizes and remains at the bottom as its propellant being used until it depletes, due to the position of the vehicle's passenger cabin and its engines at its lower end. It will reach 80km from sea level generally known as "the edge of space" due to its momentum although its propellant will be depleted at a lower altitude. As the suborbital vehicle descends tail first, its wings automatically extend and rotate at horizontal axes perpendicular to the fuselage. These naturally and passively rotating wings ensure controlled low velocity and stable descend of the vehicle. The passenger cabin also rotates automatically at a steady low speed at the centerline of its fuselage as it descends, caused naturally by the lift force, enabling its passengers a surrounding 360 degrees view. SOLVES is steered automatically to its landing point by an electrical propulsion system with a vectoring nozzle. The electrical propulsion minimizes space and weight and is free of pollution and noise. Its electrical power comes from a battery aided by power generated by the naturally rotating wings. When the vehicle lands, it is in the safest mode as its propellant is depleted and its center of gravity remains at the bottom of its cabin. The cabin, being located at the bottom of the fuselage, enables very convenient, rapid and safe entry and exit of its passengers. SOLVES will be a robotic suborbital vehicle with green technology. The vehicle will carry 4 passengers and each passenger will be trained to land the vehicle manually if the fully automated landing system fails and therefore it will be engineered for simple operation by trained passengers. However, for certification by aviation authorities the vehicle may be operational with 3 passengers and a pilot. A specific operation considered for SOLVES is navaloperation where the suborbital vehicle will be operating from a seaborne spaceport, probably a superyacht with spacepad for the vertical launching and landing of the vehicle. Such naval operation enables the vehicle to fly above exotic locations reachable by sea. SOLVES is also planned for further development into reusable rocket booster to carry small suborbiter to 160km from sea level, enables the passengers aboard the suborbiter to experience longer zero gravity time and more effective suborbital flight.

Using Visual Odometry to Estimate Position and Attitude

NASA Technical Reports Server (NTRS)

Maimone, Mark; Cheng, Yang; Matthies, Larry; Schoppers, Marcel; Olson, Clark

2007-01-01

A computer program in the guidance system of a mobile robot generates estimates of the position and attitude of the robot, using features of the terrain on which the robot is moving, by processing digitized images acquired by a stereoscopic pair of electronic cameras mounted rigidly on the robot. Developed for use in localizing the Mars Exploration Rover (MER) vehicles on Martian terrain, the program can also be used for similar purposes on terrestrial robots moving in sufficiently visually textured environments: examples include low-flying robotic aircraft and wheeled robots moving on rocky terrain or inside buildings. In simplified terms, the program automatically detects visual features and tracks them across stereoscopic pairs of images acquired by the cameras. The 3D locations of the tracked features are then robustly processed into an estimate of overall vehicle motion. Testing has shown that by use of this software, the error in the estimate of the position of the robot can be limited to no more than 2 percent of the distance traveled, provided that the terrain is sufficiently rich in features. This software has proven extremely useful on the MER vehicles during driving on sandy and highly sloped terrains on Mars.

Remote sensing-based detection and quantification of roadway debris following natural disasters

NASA Astrophysics Data System (ADS)

Axel, Colin; van Aardt, Jan A. N.; Aros-Vera, Felipe; Holguín-Veras, José

2016-05-01

Rapid knowledge of road network conditions is vital to formulate an efficient emergency response plan following any major disaster. Fallen buildings, immobile vehicles, and other forms of debris often render roads impassable to responders. The status of roadways is generally determined through time and resource heavy methods, such as field surveys and manual interpretation of remotely sensed imagery. Airborne lidar systems provide an alternative, cost-effective option for performing network assessments. The 3D data can be collected quickly over a wide area and provide valuable insight about the geometry and structure of the scene. This paper presents a method for automatically detecting and characterizing debris in roadways using airborne lidar data. Points falling within the road extent are extracted from the point cloud and clustered into individual objects using region growing. Objects are classified as debris or non-debris using surface properties and contextual cues. Debris piles are reconstructed as surfaces using alpha shapes, from which an estimate of debris volume can be computed. Results using real lidar data collected after a natural disaster are presented. Initial results indicate that accurate debris maps can be automatically generated using the proposed method. These debris maps would be an invaluable asset to disaster management and emergency response teams attempting to reach survivors despite a crippled transportation network.

Automatic content-based analysis of georeferenced image data: Detection of Beggiatoa mats in seafloor video mosaics from the HÅkon Mosby Mud Volcano

NASA Astrophysics Data System (ADS)

Jerosch, K.; Lüdtke, A.; Schlüter, M.; Ioannidis, G. T.

2007-02-01

The combination of new underwater technology as remotely operating vehicles (ROVs), high-resolution video imagery, and software to compute georeferenced mosaics of the seafloor provides new opportunities for marine geological or biological studies and applications in offshore industry. Even during single surveys by ROVs or towed systems large amounts of images are compiled. While these underwater techniques are now well-engineered, there is still a lack of methods for the automatic analysis of the acquired image data. During ROV dives more than 4200 georeferenced video mosaics were compiled for the HÅkon Mosby Mud Volcano (HMMV). Mud volcanoes as HMMV are considered as significant source locations for methane characterised by unique chemoautotrophic communities as Beggiatoa mats. For the detection and quantification of the spatial distribution of Beggiatoa mats an automated image analysis technique was developed, which applies watershed transformation and relaxation-based labelling of pre-segmented regions. Comparison of the data derived by visual inspection of 2840 video images with the automated image analysis revealed similarities with a precision better than 90%. We consider this as a step towards a time-efficient and accurate analysis of seafloor images for computation of geochemical budgets and identification of habitats at the seafloor.

Anomaly Detection for Next-Generation Space Launch Ground Operations

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Iverson, David L.; Hall, David R.; Taylor, William M.; Patterson-Hine, Ann; Brown, Barbara; Ferrell, Bob A.; Waterman, Robert D.

2010-01-01

NASA is developing new capabilities that will enable future human exploration missions while reducing mission risk and cost. The Fault Detection, Isolation, and Recovery (FDIR) project aims to demonstrate the utility of integrated vehicle health management (IVHM) tools in the domain of ground support equipment (GSE) to be used for the next generation launch vehicles. In addition to demonstrating the utility of IVHM tools for GSE, FDIR aims to mature promising tools for use on future missions and document the level of effort - and hence cost - required to implement an application with each selected tool. One of the FDIR capabilities is anomaly detection, i.e., detecting off-nominal behavior. The tool we selected for this task uses a data-driven approach. Unlike rule-based and model-based systems that require manual extraction of system knowledge, data-driven systems take a radically different approach to reasoning. At the basic level, they start with data that represent nominal functioning of the system and automatically learn expected system behavior. The behavior is encoded in a knowledge base that represents "in-family" system operations. During real-time system monitoring or during post-flight analysis, incoming data is compared to that nominal system operating behavior knowledge base; a distance representing deviation from nominal is computed, providing a measure of how far "out of family" current behavior is. We describe the selected tool for FDIR anomaly detection - Inductive Monitoring System (IMS), how it fits into the FDIR architecture, the operations concept for the GSE anomaly monitoring, and some preliminary results of applying IMS to a Space Shuttle GSE anomaly.

Crack detection in a wheel end spindle using wave propagation via modal impacts and piezo actuation

NASA Astrophysics Data System (ADS)

Ackers, Spencer; Evans, Ronald; Johnson, Timothy; Kess, Harold; White, Jonathan; Adams, Douglas E.; Brown, Pam

2006-03-01

This research demonstrates two methodologies for detecting cracks in a metal spindle housed deep within a vehicle wheel end assembly. First, modal impacts are imposed on the hub of the wheel in the longitudinal direction to produce broadband elastic wave excitation spectra out to 7000 Hz. The response data on the flange is collected using 3000 Hz bandwidth accelerometers. It is shown using frequency response analysis that the crack produces a filter, which amplifies the elastic response of the surrounding components of the wheel assembly. Experiments on wheel assemblies mounted on the vehicle with the vehicle lifted off the ground are performed to demonstrate that the modal impact method can be used to nondestructively evaluate cracks of varying depths despite sources of variability such as the half shaft angular position relative to the non-rotating spindle. Second, an automatic piezo-stack actuator is utilized to excite the wheel hub with a swept sine signal extending from 20 kHz. Accelerometers are then utilized to measure the response on the flange. It is demonstrated using frequency response analysis that the crack filters waves traveling from the hub to the flange. A simple finite element model is used to interpret the experimental results. Challenges discussed include variability from assembly to assembly, the variability in each assembly, and the high amount of damping present in each assembly due to the transmission gearing, lubricant, and other components in the wheel end. A two-channel measurement system with a graphical user interface for detecting cracks was also developed and a procedure was created to ensure that operators properly perform the test.

AUTOMOTIVE DIESEL MAINTENANCE 2. UNIT VII, AUTOMATIC TRANSMISSIONS--ALLISON, TORQUMATIC SERIES 5960 AND 6060 (PART I).

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 25-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE OPERATION AND MAINTENANCE OF SPECIFIC MODELS OF AUTOMATIC TRANSMISSIONS USED ON DIESEL POWERED VEHICLES. TOPICS ARE (1) GENERAL SPECIFICATION DATA, (2) OPTIONS FOR VARIOUS APPLICATIONS, (3) ROAD TEST INSTRUCTIONS, (4) IDENTIFICATION AND SPECIFICATION DATA, (5) ALLISON…

49 CFR 178.338-11 - Discharge control devices.

Code of Federal Regulations, 2011 CFR

2011-10-01

... water capacity, remote means of automatic closure must be installed at the ends of the cargo tank in at... control system. (ii) On a cargo tank motor vehicle of 3,500 gallons water capacity or less, at least one remote means of automatic closure must be installed on the end of the cargo tank farthest away from the...

AUTOMOTIVE DIESEL MAINTENANCE 2. UNIT X, AUTOMATIC TRANSMISSIONS--HYDRAULIC SYSTEMS (PART II).

ERIC Educational Resources Information Center

Human Engineering Inst., Cleveland, OH.

THIS MODULE OF A 25-MODULE COURSE IS DESIGNED TO PROVIDE A SUMMARY OF MAINTENANCE PROCEDURES FOR AUTOMATIC TRANSMISSIONS USED ON DIESEL POWERED VEHICLES. TOPICS ARE (1) CHECKING THE HYDRAULIC SYSTEM, (2) SERVICING THE HYDRAULIC SYSTEM, (3) EXAMINING THE RANGE CONTROL VALVE, (4) EXAMINING THE LOCK-UP AND FLOW VALVE, (5) EXAMINING THE MAIN REGULATOR…

Piezo-electric automatic vehicle classification system : Oregon Department of Transportation with Castle Rock Consultants for a SHRP Long Term Pavement Performance Site : final report.

DOT National Transportation Integrated Search

1991-07-01

Oregon has twelve pavement test sites that are part of the Strategic Highway Research Program (SHRP), Long Term Pavement Performance (LTPP) studies. Part of the data gathering on these sites involves vehicle weight and classification. This pilot proj...

Piezo-electric automatic vehicle classification system : Oregon Department of Transportation with Castle Rock Consultants for a SHRP Long Term Pavement Performance Site.

DOT National Transportation Integrated Search

1990-05-01

Oregon has twelve sites that are part of the Strategic Highway Research Program (SHRP), Long Term Pavement Performance (LTPP) studies. Part of the data gathering on these sites involves vehicle weight and classification. This pilot project was to hel...

76 FR 55829 - Federal Motor Vehicle Safety Standards; Electronic Stability Control Systems

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-09

.... Benefits of ESC Electronic stability control (ESC) systems use automatic computer- controlled braking of... demonstrated that these systems reduce fatal single-vehicle crashes of passenger cars by 55 percent and fatal... potential to prevent 56 percent of the fatal passenger car rollovers and 74 percent of the fatal LTV first...

44 CFR 60.3 - Flood plain management criteria for flood-prone areas.

Code of Federal Regulations, 2010 CFR

2010-10-01

... improvements, that fully enclosed areas below the lowest floor that are usable solely for parking of vehicles... that they permit the automatic entry and exit of floodwaters. (6) Require that manufactured homes that... building standards. Such enclosed space shall be useable solely for parking of vehicles, building access...

44 CFR 60.3 - Flood plain management criteria for flood-prone areas.

Code of Federal Regulations, 2011 CFR

2011-10-01

... improvements, that fully enclosed areas below the lowest floor that are usable solely for parking of vehicles... that they permit the automatic entry and exit of floodwaters. (6) Require that manufactured homes that... building standards. Such enclosed space shall be useable solely for parking of vehicles, building access...

Automatic detection of confusion in elderly users of a web-based health instruction video.

PubMed

Postma-Nilsenová, Marie; Postma, Eric; Tates, Kiek

2015-06-01

Because of cognitive limitations and lower health literacy, many elderly patients have difficulty understanding verbal medical instructions. Automatic detection of facial movements provides a nonintrusive basis for building technological tools supporting confusion detection in healthcare delivery applications on the Internet. Twenty-four elderly participants (70-90 years old) were recorded while watching Web-based health instruction videos involving easy and complex medical terminology. Relevant fragments of the participants' facial expressions were rated by 40 medical students for perceived level of confusion and analyzed with automatic software for facial movement recognition. A computer classification of the automatically detected facial features performed more accurately and with a higher sensitivity than the human observers (automatic detection and classification, 64% accuracy, 0.64 sensitivity; human observers, 41% accuracy, 0.43 sensitivity). A drill-down analysis of cues to confusion indicated the importance of the eye and eyebrow region. Confusion caused by misunderstanding of medical terminology is signaled by facial cues that can be automatically detected with currently available facial expression detection technology. The findings are relevant for the development of Web-based services for healthcare consumers.

Method of center localization for objects containing concentric arcs

NASA Astrophysics Data System (ADS)

Kuznetsova, Elena G.; Shvets, Evgeny A.; Nikolaev, Dmitry P.

2015-02-01

This paper proposes a method for automatic center location of objects containing concentric arcs. The method utilizes structure tensor analysis and voting scheme optimized with Fast Hough Transform. Two applications of the proposed method are considered: (i) wheel tracking in video-based system for automatic vehicle classification and (ii) tree growth rings analysis on a tree cross cut image.

Urban forest topographical mapping using UAV LIDAR

NASA Astrophysics Data System (ADS)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

Fault detection in heavy duty wheels by advanced vibration processing techniques and lumped parameter modeling

NASA Astrophysics Data System (ADS)

Malago`, M.; Mucchi, E.; Dalpiaz, G.

2016-03-01

Heavy duty wheels are used in applications such as automatic vehicles and are mainly composed of a polyurethane tread glued to a cast iron hub. In the manufacturing process, the adhesive application between tread and hub is a critical assembly phase, since it is completely made by an operator and a contamination of the bond area may happen. Furthermore, the presence of rust on the hub surface can contribute to worsen the adherence interface, reducing the operating life. In this scenario, a quality control procedure for fault detection to be used at the end of the manufacturing process has been developed. This procedure is based on vibration processing techniques and takes advantages of the results of a lumped parameter model. Indicators based on cyclostationarity can be considered as key parameters to be adopted in a monitoring test station at the end of the production line due to their not deterministic characteristics.

Detecting personnel around UGVs using stereo vision

NASA Astrophysics Data System (ADS)

Bajracharya, Max; Moghaddam, Baback; Howard, Andrew; Matthies, Larry H.

2008-04-01

Detecting people around unmanned ground vehicles (UGVs) to facilitate safe operation of UGVs is one of the highest priority issues in the development of perception technology for autonomous navigation. Research to date has not achieved the detection ranges or reliability needed in deployed systems to detect upright pedestrians in flat, relatively uncluttered terrain, let alone in more complex environments and with people in postures that are more difficult to detect. Range data is essential to solve this problem. Combining range data with high resolution imagery may enable higher performance than range data alone because image appearance can complement shape information in range data and because cameras may offer higher angular resolution than typical range sensors. This makes stereo vision a promising approach for several reasons: image resolution is high and will continue to increase, the physical size and power dissipation of the cameras and computers will continue to decrease, and stereo cameras provide range data and imagery that are automatically spatially and temporally registered. We describe a stereo vision-based pedestrian detection system, focusing on recent improvements to a shape-based classifier applied to the range data, and present frame-level performance results that show great promise for the overall approach.

A Clonal Selection Algorithm for Minimizing Distance Travel and Back Tracking of Automatic Guided Vehicles in Flexible Manufacturing System

NASA Astrophysics Data System (ADS)

Chawla, Viveak Kumar; Chanda, Arindam Kumar; Angra, Surjit

2018-03-01

The flexible manufacturing system (FMS) constitute of several programmable production work centers, material handling systems (MHSs), assembly stations and automatic storage and retrieval systems. In FMS, the automatic guided vehicles (AGVs) play a vital role in material handling operations and enhance the performance of the FMS in its overall operations. To achieve low makespan and high throughput yield in the FMS operations, it is highly imperative to integrate the production work centers schedules with the AGVs schedules. The Production schedule for work centers is generated by application of the Giffler and Thompson algorithm under four kind of priority hybrid dispatching rules. Then the clonal selection algorithm (CSA) is applied for the simultaneous scheduling to reduce backtracking as well as distance travel of AGVs within the FMS facility. The proposed procedure is computationally tested on the benchmark FMS configuration from the literature and findings from the investigations clearly indicates that the CSA yields best results in comparison of other applied methods from the literature.

Differences between automatically detected and steady-state fractional flow reserve.

PubMed

Härle, Tobias; Meyer, Sven; Vahldiek, Felix; Elsässer, Albrecht

2016-02-01

Measurement of fractional flow reserve (FFR) has become a standard diagnostic tool in the catheterization laboratory. FFR evaluation studies were based on pressure recordings during steady-state maximum hyperemia. Commercially available computer systems detect the lowest Pd/Pa ratio automatically, which might not always be measured during steady-state hyperemia. We sought to compare the automatically detected FFR and true steady-state FFR. Pressure measurement traces of 105 coronary lesions from 77 patients with intermediate coronary lesions or multivessel disease were reviewed. In all patients, hyperemia had been achieved by intravenous adenosine administration using a dosage of 140 µg/kg/min. In 42 lesions (40%) automatically detected FFR was lower than true steady-state FFR. Mean bias was 0.009 (standard deviation 0.015, limits of agreement -0.02, 0.037). In 4 lesions (3.8%) both methods lead to different treatment recommendations, in all 4 cases instantaneous wave-free ratio confirmed steady-state FFR. Automatically detected FFR was slightly lower than steady-state FFR in more than one-third of cases. Consequently, interpretation of automatically detected FFR values closely below the cutoff value requires special attention.

Restoration of Motion-Blurred Image Based on Border Deformation Detection: A Traffic Sign Restoration Model

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently. PMID:25849350

Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Non-Invasive Detection of Respiration and Heart Rate with a Vehicle Seat Sensor.

PubMed

Wusk, Grace; Gabler, Hampton

2018-05-08

This study demonstrates the feasibility of using a seat sensor designed for occupant classification from a production passenger vehicle to measure an occupant’s respiration rate (RR) and heart rate (HR) in a laboratory setting. Relaying occupant vital signs after a crash could improve emergency response by adding a direct measure of the occupant state to an Advanced Automatic Collision Notification (AACN) system. Data was collected from eleven participants with body weights ranging from 42 to 91 kg using a Ford Mustang passenger seat and seat sensor. Using a ballistocardiography (BCG) approach, the data was processed by time domain filtering and frequency domain analysis using the fast Fourier transform to yield RR and HR in a 1-min sliding window. Resting rates over the 30-min data collection and continuous RR and HR signals were compared to laboratory physiological instruments using the Bland-Altman approach. Differences between the seat sensor and reference sensor were within 5 breaths per minute for resting RR and within 15 beats per minute for resting HR. The time series comparisons for RR and HR were promising with the frequency analysis technique outperforming the peak detection technique. However, future work is necessary for more accurate and reliable real-time monitoring of RR and HR outside the laboratory setting.

Intelligent behaviors through vehicle-to-vehicle and vehicle-to-infrastructure communication

NASA Astrophysics Data System (ADS)

Garcia, Richard D.; Sturgeon, Purser; Brown, Mike

2012-06-01

The last decade has seen a significant increase in intelligent safety devices on private automobiles. These devices have both increased and augmented the situational awareness of the driver and in some cases provided automated vehicle responses. To date almost all intelligent safety devices have relied on data directly perceived by the vehicle. This constraint has a direct impact on the types of solutions available to the vehicle. In an effort to improve the safety options available to a vehicle, numerous research laboratories and government agencies are investing time and resources into connecting vehicles to each other and to infrastructure-based devices. This work details several efforts in both the commercial vehicle and the private auto industries to increase vehicle safety and driver situational awareness through vehicle-to-vehicle and vehicle-to-infrastructure communication. It will specifically discuss intelligent behaviors being designed to automatically disable non-compliant vehicles, warn tractor trailer vehicles of unsafe lane maneuvers such as lane changes, passing, and merging, and alert drivers to non-line-of-sight emergencies.

The design method and research status of vehicle detection system based on geomagnetic detection principle

NASA Astrophysics Data System (ADS)

Lin, Y. H.; Bai, R.; Qian, Z. H.

2018-03-01

Vehicle detection systems are applied to obtain real-time information of vehicles, realize traffic control and reduce traffic pressure. This paper reviews geomagnetic sensors as well as the research status of the vehicle detection system. Presented in the paper are also our work on the vehicle detection system, including detection algorithms and experimental results. It is found that the GMR based vehicle detection system has a detection accuracy up to 98% with a high potential for application in the road traffic control area.

A study on obstacle detection method of the frontal view using a camera on highway

NASA Astrophysics Data System (ADS)

Nguyen, Van-Quang; Park, Jeonghyeon; Seo, Changjun; Kim, Heungseob; Boo, Kwangsuck

2018-03-01

In this work, we introduce an approach to detect vehicles for driver assistance, or warning system. For driver assistance system, it must detect both lanes (left and right side lane), and discover vehicles ahead of the test vehicle. Therefore, in this study, we use a camera, it is installed on the windscreen of the test vehicle. Images from the camera are used to detect three lanes, and detect multiple vehicles. In lane detection, line detection and vanishing point estimation are used. For the vehicle detection, we combine the horizontal and vertical edge detection, the horizontal edge is used to detect the vehicle candidates, and then the vertical edge detection is used to verify the vehicle candidates. The proposed algorithm works with of 480 × 640 image frame resolution. The system was tested on the highway in Korea.

Co-Registration of DSMs Generated by Uav and Terrestrial Laser Scanning Systems

NASA Astrophysics Data System (ADS)

Ancil Persad, Ravi; Armenakis, Costas

2016-06-01

An approach for the co-registration of Digital Surface Models (DSMs) derived from Unmanned Aerial Vehicles (UAVs) and Terrestrial Laser Scanners (TLS) is proposed. Specifically, a wavelet-based feature descriptor for matching surface keypoints on the 2.5D DSMs is developed. DSMs are useful in wide-scope of various applications such as 3D building modelling and reconstruction, cultural heritage, urban and environmental planning, aircraft navigation/path routing, accident and crime scene reconstruction, mining as well as, topographic map revision and change detection. For these listed applications, it is not uncommon that there will be a need for automatically aligning multi-temporal DSMs which may have been acquired from multiple sensors, with different specifications over a period of time, and may have various overlaps. Terrestrial laser scanners usually capture urban facades in an accurate manner; however this is not the case for building roof structures. On the other hand, vertical photography from UAVs can capture the roofs. Therefore, the automatic fusion of UAV and laser-scanning based DSMs is addressed here as it serves various geospatial applications.

Orbital Spacecraft Consumables Resupply System (OSCRS). Volume 4: Extended study results Part 1: Executive Summary

NASA Technical Reports Server (NTRS)

1987-01-01

The objectives consisted of three major tasks. The first was to establish the definition of Space Station and Orbital Maneuvering Vehicle (OMV) user requirements and interfaces and to evaluate system requirements of a water tanker to be used at the station. The second task is to conduct trade studies of system requirements, hardware/software, and operations to evaluate the effect of automatic operation at the station or remote from the station in consonance with the OMV. The last task is to evaluate automatic refueling concepts and to evaluate the impact to Orbital Spacecraft Consumable Resupply System (OSCRS) concept/design to use expendable launch vehicles (ELV) to place the tank into orbit. Progress in each area is discussed.

Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer

DTIC Science & Technology

2016-06-01

TECHNICAL REPORT Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar...Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer Leon Vaizer, Jesse Angle, Neil...of Magnetic Dipole Targets Using LSG i June 2016 TABLE OF CONTENTS INTRODUCTION

Flight performance of the TCV B-737 airplane at Jorge Newberry Airport, Buenos Aires, Argentina using TRSB/MLS guidance

NASA Technical Reports Server (NTRS)

White, W. F.; Clark, L.

1980-01-01

The flight performance of the Terminal Configured Vehicle airplane is summarized. Demonstration automatic approaches and landings utilizing time reference scanning beam microwave landing system (TRSB/MLS) guidance are presented. The TRSB/MLS was shown to provide the terminal area guidance necessary for flying curved automatic approaches with final legs as short as 2 km.

AFETR Instrumentation Handbook

DTIC Science & Technology

1971-09-01

of time. From this, vehicle velocity and acceleration can be computed. LOCATION Three Askanias are mobile and may be located at selected universal...Being mobile , these cinetheodolites may be placed for optimum launch coverage. Preprogrammed focusing is provided for automatic focus from 2000 and 8000...console trailer. IR (lead sulfide sensor ) Automatic Tracking System with 1 to 20 miles range. Elevation range: -10 deg to +90 deg Azimuth range: 350

Automatic contact in DYNA3D for vehicle crashworthiness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whirley, R.G.; Engelmann, B.E.

1993-07-15

This paper presents a new formulation for the automatic definition and treatment of mechanical contact in explicit nonlinear finite element analysis. Automatic contact offers the benefits of significantly reduced model construction time and fewer opportunities for user error, but faces significant challenges in reliability and computational costs. This paper discusses in detail a new four-step automatic contact algorithm. Key aspects of the proposed method include automatic identification of adjacent and opposite surfaces in the global search phase, and the use of a smoothly varying surface normal which allows a consistent treatment of shell intersection and corner contact conditions without ad-hocmore » rules. The paper concludes with three examples which illustrate the performance of the newly proposed algorithm in the public DYNA3D code.« less

Semi-automatic mapping of cultural heritage from airborne laser scanning using deep learning

NASA Astrophysics Data System (ADS)

Due Trier, Øivind; Salberg, Arnt-Børre; Holger Pilø, Lars; Tonning, Christer; Marius Johansen, Hans; Aarsten, Dagrun

2016-04-01

This paper proposes to use deep learning to improve semi-automatic mapping of cultural heritage from airborne laser scanning (ALS) data. Automatic detection methods, based on traditional pattern recognition, have been applied in a number of cultural heritage mapping projects in Norway for the past five years. Automatic detection of pits and heaps have been combined with visual interpretation of the ALS data for the mapping of deer hunting systems, iron production sites, grave mounds and charcoal kilns. However, the performance of the automatic detection methods varies substantially between ALS datasets. For the mapping of deer hunting systems on flat gravel and sand sediment deposits, the automatic detection results were almost perfect. However, some false detections appeared in the terrain outside of the sediment deposits. These could be explained by other pit-like landscape features, like parts of river courses, spaces between boulders, and modern terrain modifications. However, these were easy to spot during visual interpretation, and the number of missed individual pitfall traps was still low. For the mapping of grave mounds, the automatic method produced a large number of false detections, reducing the usefulness of the semi-automatic approach. The mound structure is a very common natural terrain feature, and the grave mounds are less distinct in shape than the pitfall traps. Still, applying automatic mound detection on an entire municipality did lead to a new discovery of an Iron Age grave field with more than 15 individual mounds. Automatic mound detection also proved to be useful for a detailed re-mapping of Norway's largest Iron Age grave yard, which contains almost 1000 individual graves. Combined pit and mound detection has been applied to the mapping of more than 1000 charcoal kilns that were used by an iron work 350-200 years ago. The majority of charcoal kilns were indirectly detected as either pits on the circumference, a central mound, or both. However, kilns with a flat interior and a shallow ditch along the circumference were often missed by the automatic detection method. The successfulness of automatic detection seems to depend on two factors: (1) the density of ALS ground hits on the cultural heritage structures being sought, and (2) to what extent these structures stand out from natural terrain structures. The first factor may, to some extent, be improved by using a higher number of ALS pulses per square meter. The second factor is difficult to change, and also highlights another challenge: how to make a general automatic method that is applicable in all types of terrain within a country. The mixed experience with traditional pattern recognition for semi-automatic mapping of cultural heritage led us to consider deep learning as an alternative approach. The main principle is that a general feature detector has been trained on a large image database. The feature detector is then tailored to a specific task by using a modest number of images of true and false examples of the features being sought. Results of using deep learning are compared with previous results using traditional pattern recognition.

Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters

NASA Astrophysics Data System (ADS)

Chitsobhuk, Orachat; Kasemsiri, Watjanapong; Glomglome, Sorayut; Lapamonpinyo, Pipatphon

2018-04-01

In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.

Automated manual transmission clutch controller

DOEpatents

Lawrie, Robert E.; Reed, Jr., Richard G.; Rausen, David J.

1999-11-30

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission shift sequence controller

DOEpatents

Lawrie, Robert E.; Reed, Richard G.; Rausen, David J.

2000-02-01

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both, an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission mode selection controller

DOEpatents

Lawrie, Robert E.

1999-11-09

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission controller

DOEpatents

Lawrie, Robert E.; Reed, Jr., Richard G.; Bernier, David R.

1999-12-28

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

ROBIN: a platform for evaluating automatic target recognition algorithms: I. Overview of the project and presentation of the SAGEM DS competition

NASA Astrophysics Data System (ADS)

Duclos, D.; Lonnoy, J.; Guillerm, Q.; Jurie, F.; Herbin, S.; D'Angelo, E.

2008-04-01

The last five years have seen a renewal of Automatic Target Recognition applications, mainly because of the latest advances in machine learning techniques. In this context, large collections of image datasets are essential for training algorithms as well as for their evaluation. Indeed, the recent proliferation of recognition algorithms, generally applied to slightly different problems, make their comparisons through clean evaluation campaigns necessary. The ROBIN project tries to fulfil these two needs by putting unclassified datasets, ground truths, competitions and metrics for the evaluation of ATR algorithms at the disposition of the scientific community. The scope of this project includes single and multi-class generic target detection and generic target recognition, in military and security contexts. From our knowledge, it is the first time that a database of this importance (several hundred thousands of visible and infrared hand annotated images) has been publicly released. Funded by the French Ministry of Defence (DGA) and by the French Ministry of Research, ROBIN is one of the ten Techno-vision projects. Techno-vision is a large and ambitious government initiative for building evaluation means for computer vision technologies, for various application contexts. ROBIN's consortium includes major companies and research centres involved in Computer Vision R&D in the field of defence: Bertin Technologies, CNES, ECA, DGA, EADS, INRIA, ONERA, MBDA, SAGEM, THALES. This paper, which first gives an overview of the whole project, is focused on one of ROBIN's key competitions, the SAGEM Defence Security database. This dataset contains more than eight hundred ground and aerial infrared images of six different vehicles in cluttered scenes including distracters. Two different sets of data are available for each target. The first set includes different views of each vehicle at close range in a "simple" background, and can be used to train algorithms. The second set contains many views of the same vehicle in different contexts and situations simulating operational scenarios.

Unmanned Aerial Vehicles for Alien Plant Species Detection and Monitoring

NASA Astrophysics Data System (ADS)

Dvořák, P.; Müllerová, J.; Bartaloš, T.; Brůna, J.

2015-08-01

Invasive species spread rapidly and their eradication is difficult. New methods enabling fast and efficient monitoring are urgently needed for their successful control. Remote sensing can improve early detection of invading plants and make their management more efficient and less expensive. In an ongoing project in the Czech Republic, we aim at developing innovative methods of mapping invasive plant species (semi-automatic detection algorithms) by using purposely designed unmanned aircraft (UAV). We examine possibilities for detection of two tree and two herb invasive species. Our aim is to establish fast, repeatable and efficient computer-assisted method of timely monitoring, reducing the costs of extensive field campaigns. For finding the best detection algorithm we test various classification approaches (object-, pixel-based and hybrid). Thanks to its flexibility and low cost, UAV enables assessing the effect of phenological stage and spatial resolution, and is most suitable for monitoring the efficiency of eradication efforts. However, several challenges exist in UAV application, such as geometrical and radiometric distortions, high amount of data to be processed and legal constrains for the UAV flight missions over urban areas (often highly invaded). The newly proposed UAV approach shall serve invasive species researchers, management practitioners and policy makers.

Mobile Healthcare for Automatic Driving Sleep-Onset Detection Using Wavelet-Based EEG and Respiration Signals

PubMed Central

Lee, Boon-Giin; Lee, Boon-Leng; Chung, Wan-Young

2014-01-01

Driving drowsiness is a major cause of traffic accidents worldwide and has drawn the attention of researchers in recent decades. This paper presents an application for in-vehicle non-intrusive mobile-device-based automatic detection of driver sleep-onset in real time. The proposed application classifies the driving mental fatigue condition by analyzing the electroencephalogram (EEG) and respiration signals of a driver in the time and frequency domains. Our concept is heavily reliant on mobile technology, particularly remote physiological monitoring using Bluetooth. Respiratory events are gathered, and eight-channel EEG readings are captured from the frontal, central, and parietal (Fpz-Cz, Pz-Oz) regions. EEGs are preprocessed with a Butterworth bandpass filter, and features are subsequently extracted from the filtered EEG signals by employing the wavelet-packet-transform (WPT) method to categorize the signals into four frequency bands: α, β, θ, and δ. A mutual information (MI) technique selects the most descriptive features for further classification. The reduction in the number of prominent features improves the sleep-onset classification speed in the support vector machine (SVM) and results in a high sleep-onset recognition rate. Test results reveal that the combined use of the EEG and respiration signals results in 98.6% recognition accuracy. Our proposed application explores the possibility of processing long-term multi-channel signals. PMID:25264954

Automatic multimodal detection for long-term seizure documentation in epilepsy.

PubMed

Fürbass, F; Kampusch, S; Kaniusas, E; Koren, J; Pirker, S; Hopfengärtner, R; Stefan, H; Kluge, T; Baumgartner, C

2017-08-01

This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Smart Infrared Inspection System Field Operational Test Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siekmann, Adam; Capps, Gary J; Franzese, Oscar

2011-06-01

The Smart InfraRed Inspection System (SIRIS) is a tool designed to assist inspectors in determining which vehicles passing through the SIRIS system are in need of further inspection by measuring the thermal data from the wheel components. As a vehicle enters the system, infrared cameras on the road measure temperatures of the brakes, tires, and wheel bearings on both wheel ends of commercial motor vehicles (CMVs) in motion. This thermal data is then presented to enforcement personal inside of the inspection station on a user friendly interface. Vehicles that are suspected to have a violation are automatically alerted to themore » enforcement staff. The main goal of the SIRIS field operational test (FOT) was to collect data to evaluate the performance of the prototype system and determine the viability of such a system being used for commercial motor vehicle enforcement. From March 2010 to September 2010, ORNL facilitated the SIRIS FOT at the Greene County Inspection Station (IS) in Greeneville, Tennessee. During the course of the FOT, 413 CMVs were given a North American Standard (NAS) Level-1 inspection. Of those 413 CMVs, 384 were subjected to a SIRIS screening. A total of 36 (9.38%) of the vehicles were flagged by SIRIS as having one or more thermal issues; with brakes issues making up 33 (91.67%) of those. Of the 36 vehicles flagged as having thermal issues, 31 (86.11%) were found to have a violation and 30 (83.33%) of those vehicles were placed out-of-service (OOS). Overall the enforcement personnel who have used SIRIS for screening purposes have had positive feedback on the potential of SIRIS. With improvements in detection algorithms and stability, the system will be beneficial to the CMV enforcement community and increase overall trooper productivity by accurately identifying a higher percentage of CMVs to be placed OOS with minimal error. No future evaluation of SIRIS has been deemed necessary and specifications for a production system will soon be drafted.« less

Anomaly detection driven active learning for identifying suspicious tracks and events in WAMI video

NASA Astrophysics Data System (ADS)

Miller, David J.; Natraj, Aditya; Hockenbury, Ryler; Dunn, Katherine; Sheffler, Michael; Sullivan, Kevin

2012-06-01

We describe a comprehensive system for learning to identify suspicious vehicle tracks from wide-area motion (WAMI) video. First, since the road network for the scene of interest is assumed unknown, agglomerative hierarchical clustering is applied to all spatial vehicle measurements, resulting in spatial cells that largely capture individual road segments. Next, for each track, both at the cell (speed, acceleration, azimuth) and track (range, total distance, duration) levels, extreme value feature statistics are both computed and aggregated, to form summary (p-value based) anomaly statistics for each track. Here, to fairly evaluate tracks that travel across different numbers of spatial cells, for each cell-level feature type, a single (most extreme) statistic is chosen, over all cells traveled. Finally, a novel active learning paradigm, applied to a (logistic regression) track classifier, is invoked to learn to distinguish suspicious from merely anomalous tracks, starting from anomaly-ranked track prioritization, with ground-truth labeling by a human operator. This system has been applied to WAMI video data (ARGUS), with the tracks automatically extracted by a system developed in-house at Toyon Research Corporation. Our system gives promising preliminary results in highly ranking as suspicious aerial vehicles, dismounts, and traffic violators, and in learning which features are most indicative of suspicious tracks.

An Alternative for Emergency Preemption of Traffic Lights

NASA Technical Reports Server (NTRS)

Foster, Conrad; Bachelder, Aaron

2006-01-01

An electronic communication-and-control system has been developed as a prototype of advanced means of automatically modifying the switching of traffic lights to give priority to emergency vehicles. This system could be used alternatively or in addition to other emergency traffic-light-preemption systems, including a variety of systems now in use as well as two proposed systems described in "Systems Would Preempt Traffic Lights for Emergency Vehicles" (NPO-30573), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 36. Unlike those prior systems that depend on detection of sounds and/or lights emitted by emergency vehicles, this system is not subject to severe range limitations. This system can be retrofitted into any pre-existing traffic-light-control system, without need to modify that system other than to make a minimal number of wire connections between the two systems. This system comprises several subsystems, including a transponder and interface circuitry on each emergency vehicle, a monitoring and control unit at each intersection equipped with traffic lights, and a wide-area two-way radio communication network that connects the emergency vehicles and intersection units. Computers in the various intersections and vehicle units run special-purpose software that implements the traffic- light-preemption scheme. The operations of the intersection and vehicle units are synchronized by use of Global Positioning System (GPS) timing signals. The transponder in each vehicle estimates its own position and velocity by use of GPS signals, deductive ("dead") reckoning, data from the onboard diagnostic (OBD) computer of the vehicle, and/or triangulation of beacon signals. When the operator of an emergency vehicle turns on its flashing lights and sirens in response to a request for an emergency response, the transponder unit goes into action, reading the OBD data to determine speed and acceleration, and reading and gathering further navigational data as described above. The position, velocity, and acceleration data are combined with vehicle-identification data in a prescribed format, and the resulting set of data is transmitted to the intersections within communication range of the transponder.

Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morton, April M; Omitaomu, Olufemi A; Kotikot, Susan

A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.

Robust vehicle detection under various environments to realize road traffic flow surveillance using an infrared thermal camera.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized.

Robust Vehicle Detection under Various Environments to Realize Road Traffic Flow Surveillance Using an Infrared Thermal Camera

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2015-01-01

To realize road traffic flow surveillance under various environments which contain poor visibility conditions, we have already proposed two vehicle detection methods using thermal images taken with an infrared thermal camera. The first method uses pattern recognition for the windshields and their surroundings to detect vehicles. However, the first method decreases the vehicle detection accuracy in winter season. To maintain high vehicle detection accuracy in all seasons, we developed the second method. The second method uses tires' thermal energy reflection areas on a road as the detection targets. The second method did not achieve high detection accuracy for vehicles on left-hand and right-hand lanes except for two center-lanes. Therefore, we have developed a new method based on the second method to increase the vehicle detection accuracy. This paper proposes the new method and shows that the detection accuracy for vehicles on all lanes is 92.1%. Therefore, by combining the first method and the new method, high vehicle detection accuracies are maintained under various environments, and road traffic flow surveillance can be realized. PMID:25763384

COBRA ATD minefield detection results for the Joint Countermine ACTD Demonstrations

NASA Astrophysics Data System (ADS)

Stetson, Suzanne P.; Witherspoon, Ned H.; Holloway, John H., Jr.; Suiter, Harold R.; Crosby, Frank J.; Hilton, Russell J.; McCarley, Karen A.

2000-08-01

The Coastal Battlefield Reconnaissance and Analysis)COBRA) system described here was a Marine Corps Advanced Technology Demonstration (ATD) development consisting of an unmanned aerial vehicle (UAV) airborne multispectral video sensor system and ground station which processes the multispectral video data to automatically detect minefields along the flight path. After successful completion of the ATD, the residual COBRA ATD system participated in the Joint Countermine (JCM) Advanced Concept Technology Demonstration (ACTD) Demo I held at Camp Lejeune, North Carolina in conjunction with JTFX97 and Demo II held in Stephenville, Newfoundland in conjunction with MARCOT98. These exercises demonstrated the COBRA ATD system in an operational environment, detecting minefields that included several different mine types in widely varying backgrounds. The COBRA system performed superbly during these demonstrations, detecting mines under water, in the surf zone, on the beach, and inland, and has transitioned to an acquisition program. This paper describes the COBRA operation and performance results for these demonstrations, which represent the first demonstrated capability for remote tactical minefield detection from a UAV. The successful COBRA technologies and techniques demonstrated for tactical UAV minefield detection in the Joint Countermine Advanced Concept Technology Demonstrations have formed the technical foundation for future developments in Marine Corps, Navy, and Army tactical remote airborne mine detection systems.

Flight performance of the TCV B-737 airplane at Kennedy Airport using TRSB/MLS guidance

NASA Technical Reports Server (NTRS)

White, W. F.; Clark, L. V.

1979-01-01

The terminal configured vehicle (TCV) B 737 was flown in demonstration of the time reference scanning beam/microwave landing system (TRSB/MLS). The flight performance of the TCV airplane during the demonstration automatic approaches and landings while utilizing TRSB/MLS guidance is reported. The TRSB/MLS is shown to provide the terminal area guidance necessary for flying curved automatic approaches with short finals.

Review of automatic detection of pig behaviours by using image analysis

NASA Astrophysics Data System (ADS)

Han, Shuqing; Zhang, Jianhua; Zhu, Mengshuai; Wu, Jianzhai; Kong, Fantao

2017-06-01

Automatic detection of lying, moving, feeding, drinking, and aggressive behaviours of pigs by means of image analysis can save observation input by staff. It would help staff make early detection of diseases or injuries of pigs during breeding and improve management efficiency of swine industry. This study describes the progress of pig behaviour detection based on image analysis and advancement in image segmentation of pig body, segmentation of pig adhesion and extraction of pig behaviour characteristic parameters. Challenges for achieving automatic detection of pig behaviours were summarized.

Neural network based automatic limit prediction and avoidance system and method

NASA Technical Reports Server (NTRS)

Calise, Anthony J. (Inventor); Prasad, Jonnalagadda V. R. (Inventor); Horn, Joseph F. (Inventor)

2001-01-01

A method for performance envelope boundary cueing for a vehicle control system comprises the steps of formulating a prediction system for a neural network and training the neural network to predict values of limited parameters as a function of current control positions and current vehicle operating conditions. The method further comprises the steps of applying the neural network to the control system of the vehicle, where the vehicle has capability for measuring current control positions and current vehicle operating conditions. The neural network generates a map of current control positions and vehicle operating conditions versus the limited parameters in a pre-determined vehicle operating condition. The method estimates critical control deflections from the current control positions required to drive the vehicle to a performance envelope boundary. Finally, the method comprises the steps of communicating the critical control deflection to the vehicle control system; and driving the vehicle control system to provide a tactile cue to an operator of the vehicle as the control positions approach the critical control deflections.

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares

PubMed Central

Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen

2017-01-01

Simple Summary Most prototypes of systems to automatically detect lameness in dairy cattle are still not available on the market. Estimating their potential adoption rate could support developers in defining development goals towards commercially viable and well-adopted systems. We simulated the potential market shares of such prototypes to assess the effect of altering the system cost and detection performance on the potential adoption rate. We found that system cost and lameness detection performance indeed substantially influence the potential adoption rate. In order for farmers to prefer automatic detection over current visual detection, the usefulness that farmers attach to a system with specific characteristics should be higher than that of visual detection. As such, we concluded that low system costs and high detection performances are required before automatic lameness detection systems become applicable in practice. Abstract Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system’s potential adoption rate. PMID:28991188

Statewide Cellular Coverage Map

DOT National Transportation Integrated Search

2002-02-01

The role of wireless communications in transportation is becoming increasingly important. Wireless communications are critical for many applications of Intelligent Transportation Systems (ITS) such as Automatic Vehicle Location (AVL) and Automated Co...

Experiments in teleoperator and autonomous control of space robotic vehicles

NASA Technical Reports Server (NTRS)

Alexander, Harold L.

1991-01-01

A program of research embracing teleoperator and automatic navigational control of freely flying satellite robots is presented. Current research goals include: (1) developing visual operator interfaces for improved vehicle teleoperation; (2) determining the effects of different visual interface system designs on operator performance; and (3) achieving autonomous vision-based vehicle navigation and control. This research program combines virtual-environment teleoperation studies and neutral-buoyancy experiments using a space-robot simulator vehicle currently under development. Visual-interface design options under investigation include monoscopic versus stereoscopic displays and cameras, helmet-mounted versus panel-mounted display monitors, head-tracking versus fixed or manually steerable remote cameras, and the provision of vehicle-fixed visual cues, or markers, in the remote scene for improved sensing of vehicle position, orientation, and motion.

Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations

NASA Technical Reports Server (NTRS)

Patrick, M. Clinton; Thaler, Stephen L.; Stevenson-Chavis, Katherine

2006-01-01

Neural Networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper summarizes efforts at NASA's Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.

Detection and 3d Modelling of Vehicles from Terrestrial Stereo Image Pairs

NASA Astrophysics Data System (ADS)

Coenen, M.; Rottensteiner, F.; Heipke, C.

2017-05-01

The detection and pose estimation of vehicles plays an important role for automated and autonomous moving objects e.g. in autonomous driving environments. We tackle that problem on the basis of street level stereo images, obtained from a moving vehicle. Processing every stereo pair individually, our approach is divided into two subsequent steps: the vehicle detection and the modelling step. For the detection, we make use of the 3D stereo information and incorporate geometric assumptions on vehicle inherent properties in a firstly applied generic 3D object detection. By combining our generic detection approach with a state of the art vehicle detector, we are able to achieve satisfying detection results with values for completeness and correctness up to more than 86%. By fitting an object specific vehicle model into the vehicle detections, we are able to reconstruct the vehicles in 3D and to derive pose estimations as well as shape parameters for each vehicle. To deal with the intra-class variability of vehicles, we make use of a deformable 3D active shape model learned from 3D CAD vehicle data in our model fitting approach. While we achieve encouraging values up to 67.2% for correct position estimations, we are facing larger problems concerning the orientation estimation. The evaluation is done by using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012).

Predicting severe injury using vehicle telemetry data.

PubMed

Ayoung-Chee, Patricia; Mack, Christopher D; Kaufman, Robert; Bulger, Eileen

2013-01-01

In 2010, the National Highway Traffic Safety Administration standardized collision data collected by event data recorders, which may help determine appropriate emergency medical service (EMS) response. Previous models (e.g., General Motors ) predict severe injury (Injury Severity Score [ISS] > 15) using occupant demographics and collision data. Occupant information is not automatically available, and 12% of calls from advanced automatic collision notification providers are unanswered. To better inform EMS triage, our goal was to create a predictive model only using vehicle collision data. Using the National Automotive Sampling System Crashworthiness Data System data set, we included front-seat occupants in late-model vehicles (2000 and later) in nonrollover and rollover crashes in years 2000 to 2010. Telematic (change in velocity, direction of force, seat belt use, vehicle type and curb weight, as well as multiple impact) and nontelematic variables (maximum intrusion, narrow impact, and passenger ejection) were included. Missing data were multiply imputed. The University of Washington model was tested to predict severe injury before application of guidelines (Step 0) and for occupants who did not meet Steps 1 and 2 criteria (Step 3) of the Centers for Disease Control and Prevention Field Triage Guidelines. A probability threshold of 20% was chosen in accordance with Centers for Disease Control and Prevention recommendations. There were 28,633 crashes, involving 33,956 vehicles and 52,033 occupants, of whom 9.9% had severe injury. At Step 0, the University of Washington model sensitivity was 40.0% and positive predictive value (PPV) was 20.7%. At Step 3, the sensitivity was 32.3 % and PPV was 10.1%. Model analysis excluding nontelematic variables decreased sensitivity and PPV. The sensitivity of the re-created General Motors model was 38.5% at Step 0 and 28.1% at Step 3. We designed a model using only vehicle collision data that was predictive of severe injury at collision notification and in the field and was comparable with an existing model. These models demonstrate the potential use of advanced automatic collision notification in planning EMS response. Prognostic study, level II.

Driving behaviour responses to a moose encounter, automatic speed camera, wildlife warning sign and radio message determined in a factorial simulator study.

PubMed

Jägerbrand, Annika K; Antonson, Hans

2016-01-01

In a driving simulator study, driving behaviour responses (speed and deceleration) to encountering a moose, automatic speed camera, wildlife warning sign and radio message, with or without a wildlife fence and in dense forest or open landscape, were analysed. The study consisted of a factorial experiment that examined responses to factors singly and in combination over 9-km road stretches driven eight times by 25 participants (10 men, 15 women). The aims were to: determine the most effective animal-vehicle collision (AVC) countermeasures in reducing vehicle speed and test whether these are more effective in combination for reducing vehicle speed; identify the most effective countermeasures on encountering moose; and determine whether the driving responses to AVC countermeasures are affected by the presence of wildlife fences and landscape characteristics. The AVC countermeasures that proved most effective in reducing vehicle speed were a wildlife warning sign and radio message, while automatic speed cameras had a speed-increasing effect. There were no statistically significant interactions between different countermeasures and moose encounters. However, there was a tendency for a stronger speed-reducing effect from the radio message warning and from a combination of a radio message and wildlife warning sign in velocity profiles covering longer driving distances than the statistical tests. Encountering a moose during the drive had the overall strongest speed-reducing effect and gave the strongest deceleration, indicating that moose decoys or moose artwork might be useful as speed-reducing countermeasures. Furthermore, drivers reduced speed earlier on encountering a moose in open landscape and had lower velocity when driving past it. The presence of a wildlife fence on encountering the moose resulted in smaller deceleration. Copyright © 2015 Elsevier Ltd. All rights reserved.

Clinical experience with a computer-aided diagnosis system for automatic detection of pulmonary nodules at spiral CT of the chest

NASA Astrophysics Data System (ADS)

Wormanns, Dag; Fiebich, Martin; Saidi, Mustafa; Diederich, Stefan; Heindel, Walter

2001-05-01

The purpose of the study was to evaluate a computer aided diagnosis (CAD) workstation with automatic detection of pulmonary nodules at low-dose spiral CT in a clinical setting for early detection of lung cancer. Two radiologists in consensus reported 88 consecutive spiral CT examinations. All examinations were reviewed using a UNIX-based CAD workstation with a self-developed algorithm for automatic detection of pulmonary nodules. The algorithm was designed to detect nodules with at least 5 mm diameter. The results of automatic nodule detection were compared to the consensus reporting of two radiologists as gold standard. Additional CAD findings were regarded as nodules initially missed by the radiologists or as false positive results. A total of 153 nodules were detected with all modalities (diameter: 85 nodules <5mm, 63 nodules 5-9 mm, 5 nodules >= 10 mm). Reasons for failure of automatic nodule detection were assessed. Sensitivity of radiologists for nodules >=5 mm was 85%, sensitivity of CAD was 38%. For nodules >=5 mm without pleural contact sensitivity was 84% for radiologists at 45% for CAD. CAD detected 15 (10%) nodules not mentioned in the radiologist's report but representing real nodules, among them 10 (15%) nodules with a diameter $GREW5 mm. Reasons for nodules missed by CAD include: exclusion because of morphological features during region analysis (33%), nodule density below the detection threshold (26%), pleural contact (33%), segmentation errors (5%) and other reasons (2%). CAD improves detection of pulmonary nodules at spiral CT significantly and is a valuable second opinion in a clinical setting for lung cancer screening. Optimization of region analysis and an appropriate density threshold have a potential for further improvement of automatic nodule detection.

Automatic spatiotemporal matching of detected pleural thickenings

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

40 CFR 1065.510 - Engine mapping.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... Configure any auxiliary work inputs and outputs such as hybrid, turbo-compounding, or thermoelectric systems... intended primarily for propulsion of a vehicle with an automatic transmission where that engine is subject...

On-road vehicle detection: a review.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-05-01

Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.

Study on road sign recognition in LabVIEW

NASA Astrophysics Data System (ADS)

Panoiu, M.; Rat, C. L.; Panoiu, C.

2016-02-01

Road and traffic sign identification is a field of study that can be used to aid the development of in-car advisory systems. It uses computer vision and artificial intelligence to extract the road signs from outdoor images acquired by a camera in uncontrolled lighting conditions where they may be occluded by other objects, or may suffer from problems such as color fading, disorientation, variations in shape and size, etc. An automatic means of identifying traffic signs, in these conditions, can make a significant contribution to develop an Intelligent Transport Systems (ITS) that continuously monitors the driver, the vehicle, and the road. Road and traffic signs are characterized by a number of features which make them recognizable from the environment. Road signs are located in standard positions and have standard shapes, standard colors, and known pictograms. These characteristics make them suitable for image identification. Traffic sign identification covers two problems: traffic sign detection and traffic sign recognition. Traffic sign detection is meant for the accurate localization of traffic signs in the image space, while traffic sign recognition handles the labeling of such detections into specific traffic sign types or subcategories [1].

Automatic Design of a Maglev Controller in State Space

DTIC Science & Technology

1991-12-01

Design of a Maglev Controller in State Space Feng Zhao Richard Thornton Abstract We describe the automatic synthesis of a global nonlinear controller for...the global switching points of the controller is presented. The synthesized control system can stabilize the maglev vehicle with large initial displace...NUMBERS Automation Desing of a Maglev Controller in State Space N00014-89-J-3202 MIP-9001651 6. AUTHOR(S) Feng Zhao and Richard Thornton 7. PERFORMING

Construction Management Activities of Governmental Agencies in the New England Area During the Construction Phase.

DTIC Science & Technology

1980-02-01

automatic data exchange ... 56 There are currently 12 Data Systems available: I. Integrated Disbursing and Accounting (IDA) 2. Integrated Program Management...construction project progress through the use of a CPM scheduling and progress reporting system . It automatically generates invoices for payment and payment...posted on the project. Water will be drained daily from tanks of vehicle air brake systems . Rtigging, hooks, pendants and slings will be examined

Transmit: An Advanced Traffic Management System

DOT National Transportation Integrated Search

1995-11-27

TRANSCOM'S SYSTEM FOR MANAGING INCIDENTS AND TRAFFIC, KNOWN AS TRANSMIT, WAS INITIATED TO ESTABLISH THE FEASIBILITY OF USING AUTOMATIC VEHICLE IDENTIFICATION (AVI) EQUIPMENT FOR TRAFFIC MANAGEMENT AND SURVEILLANCE APPLICATIONS. AVI TECHNOLOGY SYSTEMS...

Monocular precrash vehicle detection: features and classifiers.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-07-01

Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

The algorithm for automatic detection of the calibration object

NASA Astrophysics Data System (ADS)

Artem, Kruglov; Irina, Ugfeld

2017-06-01

The problem of the automatic image calibration is considered in this paper. The most challenging task of the automatic calibration is a proper detection of the calibration object. The solving of this problem required the appliance of the methods and algorithms of the digital image processing, such as morphology, filtering, edge detection, shape approximation. The step-by-step process of the development of the algorithm and its adopting to the specific conditions of the log cuts in the image's background is presented. Testing of the automatic calibration module was carrying out under the conditions of the production process of the logging enterprise. Through the tests the average possibility of the automatic isolating of the calibration object is 86.1% in the absence of the type 1 errors. The algorithm was implemented in the automatic calibration module within the mobile software for the log deck volume measurement.

Vehicle parts detection based on Faster - RCNN with location constraints of vehicle parts feature point

NASA Astrophysics Data System (ADS)

Yang, Liqin; Sang, Nong; Gao, Changxin

2018-03-01

Vehicle parts detection plays an important role in public transportation safety and mobility. The detection of vehicle parts is to detect the position of each vehicle part. We propose a new approach by combining Faster RCNN and three level cascaded convolutional neural network (DCNN). The output of Faster RCNN is a series of bounding boxes with coordinate information, from which we can locate vehicle parts. DCNN can precisely predict feature point position, which is the center of vehicle part. We design an output strategy by combining these two results. There are two advantages for this. The quality of the bounding boxes are greatly improved, which means vehicle parts feature point position can be located more precise. Meanwhile we preserve the position relationship between vehicle parts and effectively improve the validity and reliability of the result. By using our algorithm, the performance of the vehicle parts detection improve obviously compared with Faster RCNN.

Flow detection via sparse frame analysis for suspicious event recognition in infrared imagery

NASA Astrophysics Data System (ADS)

Fernandes, Henrique C.; Batista, Marcos A.; Barcelos, Celia A. Z.; Maldague, Xavier P. V.

2013-05-01

It is becoming increasingly evident that intelligent systems are very bene¯cial for society and that the further development of such systems is necessary to continue to improve society's quality of life. One area that has drawn the attention of recent research is the development of automatic surveillance systems. In our work we outline a system capable of monitoring an uncontrolled area (an outside parking lot) using infrared imagery and recognizing suspicious events in this area. The ¯rst step is to identify moving objects and segment them from the scene's background. Our approach is based on a dynamic background-subtraction technique which robustly adapts detection to illumination changes. It is analyzed only regions where movement is occurring, ignoring in°uence of pixels from regions where there is no movement, to segment moving objects. Regions where movement is occurring are identi¯ed using °ow detection via sparse frame analysis. During the tracking process the objects are classi¯ed into two categories: Persons and Vehicles, based on features such as size and velocity. The last step is to recognize suspicious events that may occur in the scene. Since the objects are correctly segmented and classi¯ed it is possible to identify those events using features such as velocity and time spent motionless in one spot. In this paper we recognize the suspicious event suspicion of object(s) theft from inside a parked vehicle at spot X by a person" and results show that the use of °ow detection increases the recognition of this suspicious event from 78:57% to 92:85%.

Framework for performance evaluation of face, text, and vehicle detection and tracking in video: data, metrics, and protocol.

PubMed

Kasturi, Rangachar; Goldgof, Dmitry; Soundararajan, Padmanabhan; Manohar, Vasant; Garofolo, John; Bowers, Rachel; Boonstra, Matthew; Korzhova, Valentina; Zhang, Jing

2009-02-01

Common benchmark data sets, standardized performance metrics, and baseline algorithms have demonstrated considerable impact on research and development in a variety of application domains. These resources provide both consumers and developers of technology with a common framework to objectively compare the performance of different algorithms and algorithmic improvements. In this paper, we present such a framework for evaluating object detection and tracking in video: specifically for face, text, and vehicle objects. This framework includes the source video data, ground-truth annotations (along with guidelines for annotation), performance metrics, evaluation protocols, and tools including scoring software and baseline algorithms. For each detection and tracking task and supported domain, we developed a 50-clip training set and a 50-clip test set. Each data clip is approximately 2.5 minutes long and has been completely spatially/temporally annotated at the I-frame level. Each task/domain, therefore, has an associated annotated corpus of approximately 450,000 frames. The scope of such annotation is unprecedented and was designed to begin to support the necessary quantities of data for robust machine learning approaches, as well as a statistically significant comparison of the performance of algorithms. The goal of this work was to systematically address the challenges of object detection and tracking through a common evaluation framework that permits a meaningful objective comparison of techniques, provides the research community with sufficient data for the exploration of automatic modeling techniques, encourages the incorporation of objective evaluation into the development process, and contributes useful lasting resources of a scale and magnitude that will prove to be extremely useful to the computer vision research community for years to come.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

PubMed Central

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

PubMed

Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Electrophysiological Correlates of Automatic Visual Change Detection in School-Age Children

ERIC Educational Resources Information Center

Clery, Helen; Roux, Sylvie; Besle, Julien; Giard, Marie-Helene; Bruneau, Nicole; Gomot, Marie

2012-01-01

Automatic stimulus-change detection is usually investigated in the auditory modality by studying Mismatch Negativity (MMN). Although the change-detection process occurs in all sensory modalities, little is known about visual deviance detection, particularly regarding the development of this brain function throughout childhood. The aim of the…

Automatic event recognition and anomaly detection with attribute grammar by learning scene semantics

NASA Astrophysics Data System (ADS)

Qi, Lin; Yao, Zhenyu; Li, Li; Dong, Junyu

2007-11-01

In this paper we present a novel framework for automatic event recognition and abnormal behavior detection with attribute grammar by learning scene semantics. This framework combines learning scene semantics by trajectory analysis and constructing attribute grammar-based event representation. The scene and event information is learned automatically. Abnormal behaviors that disobey scene semantics or event grammars rules are detected. By this method, an approach to understanding video scenes is achieved. Further more, with this prior knowledge, the accuracy of abnormal event detection is increased.

Intervertebral disc detection in X-ray images using faster R-CNN.

PubMed

Ruhan Sa; Owens, William; Wiegand, Raymond; Studin, Mark; Capoferri, Donald; Barooha, Kenneth; Greaux, Alexander; Rattray, Robert; Hutton, Adam; Cintineo, John; Chaudhary, Vipin

2017-07-01

Automatic identification of specific osseous landmarks on the spinal radiograph can be used to automate calculations for correcting ligament instability and injury, which affect 75% of patients injured in motor vehicle accidents. In this work, we propose to use deep learning based object detection method as the first step towards identifying landmark points in lateral lumbar X-ray images. The significant breakthrough of deep learning technology has made it a prevailing choice for perception based applications, however, the lack of large annotated training dataset has brought challenges to utilizing the technology in medical image processing field. In this work, we propose to fine tune a deep network, Faster-RCNN, a state-of-the-art deep detection network in natural image domain, using small annotated clinical datasets. In the experiment we show that, by using only 81 lateral lumbar X-Ray training images, one can achieve much better performance compared to traditional sliding window detection method on hand crafted features. Furthermore, we fine-tuned the network using 974 training images and tested on 108 images, which achieved average precision of 0.905 with average computation time of 3 second per image, which greatly outperformed traditional methods in terms of accuracy and efficiency.

Automated low-thrust guidance for the orbital maneuvering vehicle

NASA Technical Reports Server (NTRS)

Rose, Richard E.; Schmeichel, Harry; Shortwell, Charles P.; Werner, Ronald A.

1988-01-01

This paper describes the highly autonomous OMV Guidance Navigation and Control system. Emphasis is placed on a key feature of the design, the low thrust guidance algorithm. The two guidance modes, orbit change guidance and rendezvous guidance, are discussed in detail. It is shown how OMV will automatically transfer from its initial orbit to an arbitrary target orbit and reach a specified rendezvous position relative to the target vehicle.

Preceding Vehicle Detection and Tracking Adaptive to Illumination Variation in Night Traffic Scenes Based on Relevance Analysis

PubMed Central

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-01-01

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation. PMID:25195855

Preceding vehicle detection and tracking adaptive to illumination variation in night traffic scenes based on relevance analysis.

PubMed

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-08-19

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation.

Characterization of the occult nature of injury for frequently occurring motor vehicle crash injuries.

PubMed

Schoell, Samantha L; Doud, Andrea N; Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Winslow, James E; Stitzel, Joel D

2017-01-01

Occult injuries are not easily detected and can be potentially life-threatening. The purpose of this study was to quantify the perceived occultness of the most frequent motor vehicle crash injuries according to emergency medical services (EMS) professionals. An electronic survey was distributed to 1,125 EMS professionals who were asked to quantify the likelihood that first responders would miss symptoms related to a particular injury on a 5-point Likert scale. The Occult Score for each injury was computed from the average of all the survey responses and normalized to be a continuous metric ranging from 0 to 1 where 0 is a non-occult (highly apparent on initial presentation) injury and 1 is an occult (unapparent on initial presentation) injury. Overall, 110,671 survey responses were collected. The Occult Score ranged from 0 to 1 with a mean, median, and standard deviation of 0.443, 0.450, and 0.233, respectively. When comparing the Occult Score of an injury to its corresponding AIS severity, there was no relationship between the metrics. When stratifying by body region, injury type, and AIS severity, it was evident that AIS 2-4 abdominal injuries with lacerations, hemorrhage, or contusions were perceived as the most occult injuries. Timely triage is key to reduce the morbidity and mortality associated with occult injuries. The Occult Score developed in this study to describe the predictability of an injury in a motor vehicle crash will be used as part of a larger effort, including incorporation into an advanced automatic crash notification (AACN) algorithm to detect crash conditions associated with a patient's need for prompt treatment at a trauma center. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Research and education from a smart campus transit laboratory.

DOT National Transportation Integrated Search

2009-10-15

For approximately a decade, members of the project team monitored Ohio State University (OSU) : campus buses serving four million passengers annually with a homemade GPSbased automatic : vehicle location (AVL), communications, and informatio...

Rural ITS user needs

DOT National Transportation Integrated Search

1999-07-01

The Truck Characteristics Study seeks to develop a better understanding of the physical characteristics of the national truck fleet. With automatic vehicle classifiers (AVC) and weigh-in-motion devices (WIM), only axle spacing and weight information ...

Vibration Tests on Transit Buses

DOT National Transportation Integrated Search

1979-03-01

The objective of this vibration measurement program was to quantify the vibration environment which would be experienced by Automatic Vehicle Monitoring (AVM) equipment when installed on buses during typical city route service operations. Two buses w...

Better service, greater efficiency : transit management for demand response systems

DOT National Transportation Integrated Search

1999-01-01

This brochure briefly describes different technologies which can enhance demand response transit systems. It covers automated scheduling and dispatching, mobile data terminals, electronic identification cards, automatic vehicle location, and geograph...

Automatic Parking of Self-Driving CAR Based on LIDAR

NASA Astrophysics Data System (ADS)

Lee, B.; Wei, Y.; Guo, I. Y.

2017-09-01

To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle's dynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realize the stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automatic parking system is feasible and effective.

Automatic polymerase chain reaction product detection system for food safety monitoring using zinc finger protein fused to luciferase.

PubMed

Yoshida, Wataru; Kezuka, Aki; Murakami, Yoshiyuki; Lee, Jinhee; Abe, Koichi; Motoki, Hiroaki; Matsuo, Takafumi; Shimura, Nobuaki; Noda, Mamoru; Igimi, Shizunobu; Ikebukuro, Kazunori

2013-11-01

An automatic polymerase chain reaction (PCR) product detection system for food safety monitoring using zinc finger (ZF) protein fused to luciferase was developed. ZF protein fused to luciferase specifically binds to target double stranded DNA sequence and has luciferase enzymatic activity. Therefore, PCR products that comprise ZF protein recognition sequence can be detected by measuring the luciferase activity of the fusion protein. We previously reported that PCR products from Legionella pneumophila and Escherichia coli (E. coli) O157 genomic DNA were detected by Zif268, a natural ZF protein, fused to luciferase. In this study, Zif268-luciferase was applied to detect the presence of Salmonella and coliforms. Moreover, an artificial zinc finger protein (B2) fused to luciferase was constructed for a Norovirus detection system. In the luciferase activity detection assay, several bound/free separation process is required. Therefore, an analyzer that automatically performed the bound/free separation process was developed to detect PCR products using the ZF-luciferase fusion protein. By means of the automatic analyzer with ZF-luciferase fusion protein, target pathogenic genomes were specifically detected in the presence of other pathogenic genomes. Moreover, we succeeded in the detection of 10 copies of E. coli BL21 without extraction of genomic DNA by the automatic analyzer and E. coli was detected with a logarithmic dependency in the range of 1.0×10 to 1.0×10(6) copies. Copyright © 2013 Elsevier B.V. All rights reserved.

[Application of automatic photography in Schistosoma japonicum miracidium hatching experiments].

PubMed

Ming-Li, Zhou; Ai-Ling, Cai; Xue-Feng, Wang

2016-05-20

To explore the value of automatic photography in the observation of results of Schistosoma japonicum miracidium hatching experiments. Some fresh S. japonicum eggs were added into cow feces, and the samples of feces were divided into a low infested experimental group and a high infested group (40 samples each group). In addition, there was a negative control group with 40 samples of cow feces without S. japonicum eggs. The conventional nylon bag S. japonicum miracidium hatching experiments were performed. The process was observed with the method of flashlight and magnifying glass combined with automatic video (automatic photography method), and, at the same time, with the naked eye observation method. The results were compared. In the low infested group, the miracidium positive detection rates were 57.5% and 85.0% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 11.723, P < 0.05). In the high infested group, the positive detection rates were 97.5% and 100% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 1.253, P > 0.05). In the two infested groups, the average positive detection rates were 77.5% and 92.5% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 6.894, P < 0.05). The automatic photography can effectively improve the positive detection rate in the S. japonicum miracidium hatching experiments.

Acquisition and use of Orlando, Florida and Continental Airbus radar flight test data

NASA Technical Reports Server (NTRS)

Eide, Michael C.; Mathews, Bruce

1992-01-01

Westinghouse is developing a lookdown pulse Doppler radar for production as the sensor and processor of a forward looking hazardous windshear detection and avoidance system. A data collection prototype of that product was ready for flight testing in Orlando to encounter low level windshear in corroboration with the FAA-Terminal Doppler Weather Radar (TDWR). Airborne real-time processing and display of the hazard factor were demonstrated with TDWR facilitated intercepts and penetrations of over 80 microbursts in a three day period, including microbursts with hazard factors in excess of .16 (with 500 ft. PIREP altitude loss) and the hazard factor display at 6 n.mi. of a visually transparent ('dry') microburst with TDWR corroborated outflow reflectivities of +5 dBz. Range gated Doppler spectrum data was recorded for subsequent development and refinement of hazard factor detection and urban clutter rejection algorithms. Following Orlando, the data collection radar was supplemental type certified for in revenue service on a Continental Airlines Airbus in an automatic and non-interferring basis with its ARINC 708 radar to allow Westinghouse to confirm its understanding of commercial aircraft installation, interface realities, and urban airport clutter. A number of software upgrades, all of which were verified at the Receiver-Transmitter-Processor (RTP) hardware bench with Orlando microburst data to produce desired advanced warning hazard factor detection, included some preliminary loads with automatic (sliding window average hazard factor) detection and annunciation recording. The current (14-APR-92) configured software is free from false and/or nuisance alerts (CAUTIONS, WARNINGS, etc.) for all take-off and landing approaches, under 2500 ft. altitude to weight-on-wheels, into all encountered airports, including Newark (NJ), LAX, Denver, Houston, Cleveland, etc. Using the Orlando data collected on hazardous microbursts, Westinghouse has developed a lookdown pulse Doppler radar product with signal and data processing algorithms which detect realistic microburst hazards and has demonstrated those algorithms produce no false alerts (or nuisance alerts) in urban airport ground moving vehicle (GMTI) and/or clutter environments.

Fusion of pixel and object-based features for weed mapping using unmanned aerial vehicle imagery

NASA Astrophysics Data System (ADS)

Gao, Junfeng; Liao, Wenzhi; Nuyttens, David; Lootens, Peter; Vangeyte, Jürgen; Pižurica, Aleksandra; He, Yong; Pieters, Jan G.

2018-05-01

The developments in the use of unmanned aerial vehicles (UAVs) and advanced imaging sensors provide new opportunities for ultra-high resolution (e.g., less than a 10 cm ground sampling distance (GSD)) crop field monitoring and mapping in precision agriculture applications. In this study, we developed a strategy for inter- and intra-row weed detection in early season maize fields from aerial visual imagery. More specifically, the Hough transform algorithm (HT) was applied to the orthomosaicked images for inter-row weed detection. A semi-automatic Object-Based Image Analysis (OBIA) procedure was developed with Random Forests (RF) combined with feature selection techniques to classify soil, weeds and maize. Furthermore, the two binary weed masks generated from HT and OBIA were fused for accurate binary weed image. The developed RF classifier was evaluated by 5-fold cross validation, and it obtained an overall accuracy of 0.945, and Kappa value of 0.912. Finally, the relationship of detected weeds and their ground truth densities was quantified by a fitted linear model with a coefficient of determination of 0.895 and a root mean square error of 0.026. Besides, the importance of input features was evaluated, and it was found that the ratio of vegetation length and width was the most significant feature for the classification model. Overall, our approach can yield a satisfactory weed map, and we expect that the obtained accurate and timely weed map from UAV imagery will be applicable to realize site-specific weed management (SSWM) in early season crop fields for reducing spraying non-selective herbicides and costs.

Automatic thermographic image defect detection of composites

NASA Astrophysics Data System (ADS)

Luo, Bin; Liebenberg, Bjorn; Raymont, Jeff; Santospirito, SP

2011-05-01

Detecting defects, and especially reliably measuring defect sizes, are critical objectives in automatic NDT defect detection applications. In this work, the Sentence software is proposed for the analysis of pulsed thermography and near IR images of composite materials. Furthermore, the Sentence software delivers an end-to-end, user friendly platform for engineers to perform complete manual inspections, as well as tools that allow senior engineers to develop inspection templates and profiles, reducing the requisite thermographic skill level of the operating engineer. Finally, the Sentence software can also offer complete independence of operator decisions by the fully automated "Beep on Defect" detection functionality. The end-to-end automatic inspection system includes sub-systems for defining a panel profile, generating an inspection plan, controlling a robot-arm and capturing thermographic images to detect defects. A statistical model has been built to analyze the entire image, evaluate grey-scale ranges, import sentencing criteria and automatically detect impact damage defects. A full width half maximum algorithm has been used to quantify the flaw sizes. The identified defects are imported into the sentencing engine which then sentences (automatically compares analysis results against acceptance criteria) the inspection by comparing the most significant defect or group of defects against the inspection standards.

A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

PubMed Central

Wang, Jianqiang; Sun, Xiaoyan; Guo, Junbin

2013-01-01

The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS). This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR) of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

PubMed

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-08-19

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Automatic detection of typical dust devils from Mars landscape images

NASA Astrophysics Data System (ADS)

Ogohara, Kazunori; Watanabe, Takeru; Okumura, Susumu; Hatanaka, Yuji

2018-02-01

This paper presents an improved algorithm for automatic detection of Martian dust devils that successfully extracts tiny bright dust devils and obscured large dust devils from two subtracted landscape images. These dust devils are frequently observed using visible cameras onboard landers or rovers. Nevertheless, previous research on automated detection of dust devils has not focused on these common types of dust devils, but on dust devils that appear on images to be irregularly bright and large. In this study, we detect these common dust devils automatically using two kinds of parameter sets for thresholding when binarizing subtracted images. We automatically extract dust devils from 266 images taken by the Spirit rover to evaluate our algorithm. Taking dust devils detected by visual inspection to be ground truth, the precision, recall and F-measure values are 0.77, 0.86, and 0.81, respectively.

Automatic detection of articulation disorders in children with cleft lip and palate.

PubMed

Maier, Andreas; Hönig, Florian; Bocklet, Tobias; Nöth, Elmar; Stelzle, Florian; Nkenke, Emeka; Schuster, Maria

2009-11-01

Speech of children with cleft lip and palate (CLP) is sometimes still disordered even after adequate surgical and nonsurgical therapies. Such speech shows complex articulation disorders, which are usually assessed perceptually, consuming time and manpower. Hence, there is a need for an easy to apply and reliable automatic method. To create a reference for an automatic system, speech data of 58 children with CLP were assessed perceptually by experienced speech therapists for characteristic phonetic disorders at the phoneme level. The first part of the article aims to detect such characteristics by a semiautomatic procedure and the second to evaluate a fully automatic, thus simple, procedure. The methods are based on a combination of speech processing algorithms. The semiautomatic method achieves moderate to good agreement (kappa approximately 0.6) for the detection of all phonetic disorders. On a speaker level, significant correlations between the perceptual evaluation and the automatic system of 0.89 are obtained. The fully automatic system yields a correlation on the speaker level of 0.81 to the perceptual evaluation. This correlation is in the range of the inter-rater correlation of the listeners. The automatic speech evaluation is able to detect phonetic disorders at an experts'level without any additional human postprocessing.

Solar electric propulsion thrust subsystem development

NASA Technical Reports Server (NTRS)

Masek, T. D.

1973-01-01

The Solar Electric Propulsion System developed under this program was designed to demonstrate all the thrust subsystem functions needed on an unmanned planetary vehicle. The demonstration included operation of the basic elements, power matching input and output voltage regulation, three-axis thrust vector control, subsystem automatic control including failure detection and correction capability (using a PDP-11 computer), operation of critical elements in thermal-vacuum-, zero-gravity-type propellant storage, and data outputs from all subsystem elements. The subsystem elements, functions, unique features, and test setup are described. General features and capabilities of the test-support data system are also presented. The test program culminated in a 1500-h computer-controlled, system-functional demonstration. This included simultaneous operation of two thruster/power conditioner sets. The results of this testing phase satisfied all the program goals.

Slip control for LIM propelled transit vehicles

NASA Astrophysics Data System (ADS)

Wallace, A. K.; Parker, J. H.; Dawson, G. E.

1980-09-01

Short stator linear induction motors, with an iron-backed aluminum sheet reaction rail and powered by a controlled inverter, have been selected as the propulsion system for transit vehicles in an intermediate capacity system (12-20,000 pphpd). The linear induction motor is capable of adhesion independent braking and acceleration levels which permit safe, close headways. In addition, simple control is possible allowing moving block automatic train control. This paper presents a slip frequency control scheme for the LIM. Experimental results for motoring and braking obtained from a test vehicle are also presented. These values are compared with theoretical predictions.

Vehicle fault diagnostics and management system

NASA Astrophysics Data System (ADS)

Gopal, Jagadeesh; Gowthamsachin

2017-11-01

This project is a kind of advanced automatic identification technology, and is more and more widely used in the fields of transportation and logistics. It looks over the main functions with like Vehicle management, Vehicle Speed limit and Control. This system starts with authentication process to keep itself secure. Here we connect sensors to the STM32 board which in turn is connected to the car through Ethernet cable, as Ethernet in capable of sending large amounts of data at high speeds. This technology involved clearly shows how a careful combination of software and hardware can produce an extremely cost-effective solution to a problem.

Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection

PubMed Central

Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe

2012-01-01

This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461

Automatic identification of artifacts in electrodermal activity data.

PubMed

Taylor, Sara; Jaques, Natasha; Chen, Weixuan; Fedor, Szymon; Sano, Akane; Picard, Rosalind

2015-01-01

Recently, wearable devices have allowed for long term, ambulatory measurement of electrodermal activity (EDA). Despite the fact that ambulatory recording can be noisy, and recording artifacts can easily be mistaken for a physiological response during analysis, to date there is no automatic method for detecting artifacts. This paper describes the development of a machine learning algorithm for automatically detecting EDA artifacts, and provides an empirical evaluation of classification performance. We have encoded our results into a freely available web-based tool for artifact and peak detection.

Communication Systems for Dual Mode Transportation

DOT National Transportation Integrated Search

1974-02-01

A program is underway to develop and demonstrate transportation systems based on vehicles which are capable of automatic operation on special guideways and manual operation on conventional roads. Adequate and reliable communications to and from vehic...

Cost/benefit analysis of electronic license plates

DOT National Transportation Integrated Search

2008-06-01

The objective of this report is to determine whether electronic vehicle recognition systems (EVR) or automatic license plate recognition systems (ALPR) would be beneficial to the Arizona Department of Transportation (AZDOT). EVR uses radio frequency ...

Better service, safer service : transit management for fixed-route systems

DOT National Transportation Integrated Search

1999-01-01

This brochure gives a brief overview of the different technologies available through advanced public transportation systems to aid public transit systems. It includes automatic vehicle location, mobile data terminals, and on-board surveillance.

Automatic Dependent Surveillance Broadcast ADS-B Sense-and-Avoid System

NASA Technical Reports Server (NTRS)

Arteaga, Ricardo

2016-01-01

This presentation provides valuable results, benefits and compliance to the FAA mandate in order to have clear guidelines to show aircraft designers how to integrate ADS-B technology into future UAS vehicles.

23 CFR 950.3 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION INTELLIGENT TRANSPORTATION SYSTEMS ELECTRONIC TOLL... Express Lanes Demonstration Program, and the Interstate System Construction Toll Pilot Program. Electronic toll collection means the ability for vehicle operators to pay tolls automatically without slowing down...

40 CFR 51.362 - Motorist compliance enforcement program oversight.

Code of Federal Regulations, 2010 CFR

2010-07-01

... collection through the use of automatic data capture systems such as bar-code scanners or optical character... determination of compliance through parking lot surveys, road-side pull-overs, or other in-use vehicle...

40 CFR 51.362 - Motorist compliance enforcement program oversight.

Code of Federal Regulations, 2011 CFR

2011-07-01

... collection through the use of automatic data capture systems such as bar-code scanners or optical character... determination of compliance through parking lot surveys, road-side pull-overs, or other in-use vehicle...

Cognitive Radio will revolutionize American transportation

ScienceCinema

None

2018-02-07

Cognitive Radio will revolutionize American transportation. Through smart technology, it will anticipate user needs; detect available bandwidths and frequencies then seamlessly connect vehicles, infrastructures, and consumer devices; and it will support the Department of Transportation IntelliDrive Program, helping researchers, auto manufacturers, and Federal and State officials advance the connectivity of US transportation systems for improved safety, mobility, and environmental conditions. Using cognitive radio, a commercial vehicle will know its driver, onboard freight and destination route. Drivers will save time and resources communicating with automatic toll booths and know ahead of time whether to stop at a weigh station or keep rolling. At accident scenes, cognitive radio sensors on freight and transportation modes can alert emergency personnel and measure on-site, real-time conditions such as a chemical leak. The sensors will connect freight to industry, relaying shipment conditions and new delivery schedules. For industry or military purposes, cognitive radio will enable real-time freight tracking around the globe and its sensory technology can help prevent cargo theft or tampering by alerting shipper and receiver if freight is tampered with while en route. For the average consumer, a vehicle will tailor the transportation experience to the passenger such as delivering age-appropriate movies via satellite. Cognitive radio will enhance transportation safety by continually sensing what is important to the user adapting to its environment and incoming information, and proposing solutions that improve mobility and quality of life.

Innovation as Road Safety Felicitator

NASA Astrophysics Data System (ADS)

Sahoo, S.; Mitra, A.; Kumar, J.; Sahoo, B.

2018-03-01

Transportation via Roads should only be used for safely commuting from one place to another. In 2015, when 1.5 Million people, across the Globe started out on a journey, it was meant to be their last. The Global Status Report on Road Safety, 2015, reflected this data from 180 countries as road traffic deaths, worldwide. In India, more than 1.37 Lakh[4] people were victims of road accidents in 2013 alone. That number is more than the number of Indians killed in all the wars put together. With these disturbing facts in mind, we found out some key ambiguities in the Indian Road Traffic Management systems like the non-adaptive nature to fluctuating traffic, pedestrians and motor vehicles not adhering to the traffic norms strictly, to name a few. Introduction of simple systems would greatly erase the effects of this silent epidemic and our Project aims to achieve the same. It would introduce a pair of Barricade systems to cautiously separate the pedestrians and motor vehicles to minimise road mishaps to the extent possible. Exceptional situations like that of an Ambulance or any emergency vehicles will be taken care off by the use of RFID tags to monitor the movement of the Barricades. The varied traffic scenario can be guided properly by using the ADS-B (Automatic Detection System-Broadcast) for monitoring traffic density according to the time and place.

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1986-01-01

The topics of research in this program include pilot/vehicle analysis techniques, identification of pilot dynamics, and control and display synthesis techniques for optimizing aircraft handling qualities. The project activities are discussed. The current technical activity is directed at extending and validating the active display synthesis procedure, and the pilot/vehicle analysis of the NLR rate-command flight configurations in the landing task. Two papers published by the researchers are attached as appendices.

Tasking and sharing sensing assets using controlled natural language

NASA Astrophysics Data System (ADS)

Preece, Alun; Pizzocaro, Diego; Braines, David; Mott, David

2012-06-01

We introduce an approach to representing intelligence, surveillance, and reconnaissance (ISR) tasks at a relatively high level in controlled natural language. We demonstrate that this facilitates both human interpretation and machine processing of tasks. More specically, it allows the automatic assignment of sensing assets to tasks, and the informed sharing of tasks between collaborating users in a coalition environment. To enable automatic matching of sensor types to tasks, we created a machine-processable knowledge representation based on the Military Missions and Means Framework (MMF), and implemented a semantic reasoner to match task types to sensor types. We combined this mechanism with a sensor-task assignment procedure based on a well-known distributed protocol for resource allocation. In this paper, we re-formulate the MMF ontology in Controlled English (CE), a type of controlled natural language designed to be readable by a native English speaker whilst representing information in a structured, unambiguous form to facilitate machine processing. We show how CE can be used to describe both ISR tasks (for example, detection, localization, or identication of particular kinds of object) and sensing assets (for example, acoustic, visual, or seismic sensors, mounted on motes or unmanned vehicles). We show how these representations enable an automatic sensor-task assignment process. Where a group of users are cooperating in a coalition, we show how CE task summaries give users in the eld a high-level picture of ISR coverage of an area of interest. This allows them to make ecient use of sensing resources by sharing tasks.

Multitask assessment of roads and vehicles network (MARVN)

NASA Astrophysics Data System (ADS)

Yang, Fang; Yi, Meng; Cai, Yiran; Blasch, Erik; Sullivan, Nichole; Sheaff, Carolyn; Chen, Genshe; Ling, Haibin

2018-05-01

Vehicle detection in wide area motion imagery (WAMI) has drawn increasing attention from the computer vision research community in recent decades. In this paper, we present a new architecture for vehicle detection on road using multi-task network, which is able to detect and segment vehicles, estimate their pose, and meanwhile yield road isolation for a given region. The multi-task network consists of three components: 1) vehicle detection, 2) vehicle and road segmentation, and 3) detection screening. Segmentation and detection components share the same backbone network and are trained jointly in an end-to-end way. Unlike background subtraction or frame differencing based methods, the proposed Multitask Assessment of Roads and Vehicles Network (MARVN) method can detect vehicles which are slowing down, stopped, and/or partially occluded in a single image. In addition, the method can eliminate the detections which are located at outside road using yielded road segmentation so as to decrease the false positive rate. As few WAMI datasets have road mask and vehicles bounding box anotations, we extract 512 frames from WPAFB 2009 dataset and carefully refine the original annotations. The resulting dataset is thus named as WAMI512. We extensively compare the proposed method with state-of-the-art methods on WAMI512 dataset, and demonstrate superior performance in terms of efficiency and accuracy.

Novel vehicle detection system based on stacked DoG kernel and AdaBoost

PubMed Central

Kang, Hyun Ho; Lee, Seo Won; You, Sung Hyun

2018-01-01

This paper proposes a novel vehicle detection system that can overcome some limitations of typical vehicle detection systems using AdaBoost-based methods. The performance of the AdaBoost-based vehicle detection system is dependent on its training data. Thus, its performance decreases when the shape of a target differs from its training data, or the pattern of a preceding vehicle is not visible in the image due to the light conditions. A stacked Difference of Gaussian (DoG)–based feature extraction algorithm is proposed to address this issue by recognizing common characteristics, such as the shadow and rear wheels beneath vehicles—of vehicles under various conditions. The common characteristics of vehicles are extracted by applying the stacked DoG shaped kernel obtained from the 3D plot of an image through a convolution method and investigating only certain regions that have a similar patterns. A new vehicle detection system is constructed by combining the novel stacked DoG feature extraction algorithm with the AdaBoost method. Experiments are provided to demonstrate the effectiveness of the proposed vehicle detection system under different conditions. PMID:29513727

Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection.

PubMed

Nguyen, Thanh; Bui, Vy; Lam, Van; Raub, Christopher B; Chang, Lin-Ching; Nehmetallah, George

2017-06-26

We propose a fully automatic technique to obtain aberration free quantitative phase imaging in digital holographic microscopy (DHM) based on deep learning. The traditional DHM solves the phase aberration compensation problem by manually detecting the background for quantitative measurement. This would be a drawback in real time implementation and for dynamic processes such as cell migration phenomena. A recent automatic aberration compensation approach using principle component analysis (PCA) in DHM avoids human intervention regardless of the cells' motion. However, it corrects spherical/elliptical aberration only and disregards the higher order aberrations. Traditional image segmentation techniques can be employed to spatially detect cell locations. Ideally, automatic image segmentation techniques make real time measurement possible. However, existing automatic unsupervised segmentation techniques have poor performance when applied to DHM phase images because of aberrations and speckle noise. In this paper, we propose a novel method that combines a supervised deep learning technique with convolutional neural network (CNN) and Zernike polynomial fitting (ZPF). The deep learning CNN is implemented to perform automatic background region detection that allows for ZPF to compute the self-conjugated phase to compensate for most aberrations.

Vehicle Classification Using an Imbalanced Dataset Based on a Single Magnetic Sensor.

PubMed

Xu, Chang; Wang, Yingguan; Bao, Xinghe; Li, Fengrong

2018-05-24

This paper aims to improve the accuracy of automatic vehicle classifiers for imbalanced datasets. Classification is made through utilizing a single anisotropic magnetoresistive sensor, with the models of vehicles involved being classified into hatchbacks, sedans, buses, and multi-purpose vehicles (MPVs). Using time domain and frequency domain features in combination with three common classification algorithms in pattern recognition, we develop a novel feature extraction method for vehicle classification. These three common classification algorithms are the k-nearest neighbor, the support vector machine, and the back-propagation neural network. Nevertheless, a problem remains with the original vehicle magnetic dataset collected being imbalanced, and may lead to inaccurate classification results. With this in mind, we propose an approach called SMOTE, which can further boost the performance of classifiers. Experimental results show that the k-nearest neighbor (KNN) classifier with the SMOTE algorithm can reach a classification accuracy of 95.46%, thus minimizing the effect of the imbalance.

Navy Omni-Directional Vehicle (ODV) development program

NASA Technical Reports Server (NTRS)

Mcgowen, Hillery

1994-01-01

The Omni-Directional Vehicle (ODV) development program sponsored by the Office of Naval Research at the Coastal Systems Station has investigated the application of ODV technology for use in the Navy shipboard environment. ODV technology as originally received by the Navy in the form of the Cadillac-Gage Side Mover Vehicle was applicable to the shipboard environment with the potential to overcome conditions of reduced traction, ship motion, decks heeled at high angles, obstacles, and confined spaces. Under the Navy program, ODV technology was investigated and a series of experimental vehicles were built and successfully tested under extremely demanding conditions. The ODV drive system has been found to be applicable to autonomous, remotely, or manually operated vehicles. Potential commercial applications include multi-directional forklift trucks, automatic guided vehicles employed in manufacturing environments, and remotely controlled platforms used in nuclear facilities or for hazardous waste clean up tasks.

Navy Omni-Directional Vehicle (ODV) development program

NASA Astrophysics Data System (ADS)

McGowen, Hillery

1994-02-01

The Omni-Directional Vehicle (ODV) development program sponsored by the Office of Naval Research at the Coastal Systems Station has investigated the application of ODV technology for use in the Navy shipboard environment. ODV technology as originally received by the Navy in the form of the Cadillac-Gage Side Mover Vehicle was applicable to the shipboard environment with the potential to overcome conditions of reduced traction, ship motion, decks heeled at high angles, obstacles, and confined spaces. Under the Navy program, ODV technology was investigated and a series of experimental vehicles were built and successfully tested under extremely demanding conditions. The ODV drive system has been found to be applicable to autonomous, remotely, or manually operated vehicles. Potential commercial applications include multi-directional forklift trucks, automatic guided vehicles employed in manufacturing environments, and remotely controlled platforms used in nuclear facilities or for hazardous waste clean up tasks.

Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

PubMed

Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

2018-01-01

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Benchmark of Vehicle Maintenance Training Between the U.S. Air Force and a Civilian Industry Leader

DTIC Science & Technology

1992-09-01

Aas :nosen to 113entlfy tasKs oerformed Dv reczcnizeo :omoe:ent automotive serv’ce Personnel :intry level o"ersonnei 4ere iot , ,ic udec i n tie sirve...Diagnose the cause of poor, intermittent, or no electric door and hatch/trunk lock operation. 10. Repair or replace switches, relays, actuators ...Semi-4utomative Temoerature Controls i. Cnecx ooeration of automatic ana semi-automatic neating, HP ventalation ana air-conaitioning ( HVAC ) control

Flight performance of the TCV B-737 airplane at Montreal/Dorval International Airport, Montreal, Canada, using TRSB/MLS guidance

NASA Technical Reports Server (NTRS)

White, W. F.; Clark, L. V.

1980-01-01

The NASA terminal configured vehicle B-737 was flown in support of the world wide FAA demonstration of the time reference scanning beam microwave landing system. A summary of the flight performance of the TCV airplane during demonstration automatic approaches and landings while utilizing TRSB/MLS guidance is presented. The TRSB/MLS provided the terminal area guidance necessary for automatically flying curved, noise abatement type approaches and landings with short finals.

Automatic Processing of Changes in Facial Emotions in Dysphoria: A Magnetoencephalography Study.

PubMed

Xu, Qianru; Ruohonen, Elisa M; Ye, Chaoxiong; Li, Xueqiao; Kreegipuu, Kairi; Stefanics, Gabor; Luo, Wenbo; Astikainen, Piia

2018-01-01

It is not known to what extent the automatic encoding and change detection of peripherally presented facial emotion is altered in dysphoria. The negative bias in automatic face processing in particular has rarely been studied. We used magnetoencephalography (MEG) to record automatic brain responses to happy and sad faces in dysphoric (Beck's Depression Inventory ≥ 13) and control participants. Stimuli were presented in a passive oddball condition, which allowed potential negative bias in dysphoria at different stages of face processing (M100, M170, and M300) and alterations of change detection (visual mismatch negativity, vMMN) to be investigated. The magnetic counterpart of the vMMN was elicited at all stages of face processing, indexing automatic deviance detection in facial emotions. The M170 amplitude was modulated by emotion, response amplitudes being larger for sad faces than happy faces. Group differences were found for the M300, and they were indexed by two different interaction effects. At the left occipital region of interest, the dysphoric group had larger amplitudes for sad than happy deviant faces, reflecting negative bias in deviance detection, which was not found in the control group. On the other hand, the dysphoric group showed no vMMN to changes in facial emotions, while the vMMN was observed in the control group at the right occipital region of interest. Our results indicate that there is a negative bias in automatic visual deviance detection, but also a general change detection deficit in dysphoria.

Designing and Implementing a Retrospective Earthquake Detection Framework at the U.S. Geological Survey National Earthquake Information Center

NASA Astrophysics Data System (ADS)

Patton, J.; Yeck, W.; Benz, H.

2017-12-01

The U.S. Geological Survey National Earthquake Information Center (USGS NEIC) is implementing and integrating new signal detection methods such as subspace correlation, continuous beamforming, multi-band picking and automatic phase identification into near-real-time monitoring operations. Leveraging the additional information from these techniques help the NEIC utilize a large and varied network on local to global scales. The NEIC is developing an ordered, rapid, robust, and decentralized framework for distributing seismic detection data as well as a set of formalized formatting standards. These frameworks and standards enable the NEIC to implement a seismic event detection framework that supports basic tasks, including automatic arrival time picking, social media based event detections, and automatic association of different seismic detection data into seismic earthquake events. In addition, this framework enables retrospective detection processing such as automated S-wave arrival time picking given a detected event, discrimination and classification of detected events by type, back-azimuth and slowness calculations, and ensuring aftershock and induced sequence detection completeness. These processes and infrastructure improve the NEIC's capabilities, accuracy, and speed of response. In addition, this same infrastructure provides an improved and convenient structure to support access to automatic detection data for both research and algorithmic development.

Design of synchromesh mechanism to optimization manual transmission's electric vehicle

NASA Astrophysics Data System (ADS)

Zainuri, Fuad; Sumarsono, Danardono A.; Adhitya, Muhammad; Siregar, Rolan

2017-03-01

Significant research has been attempted on a vehicle that lead to the development of transmission that can reduce energy consumption and improve vehicle efficiency. Consumers also expect safety, convenience, and competitive prices. Automatic transmission (AT), continuously variable transmission (CVT), and dual clutch transmission (DCT) is the latest transmission developed for road vehicle. From literature reviews that have been done that this transmission is less effective on electric cars which use batteries as a power source compared to type manual transmission, this is due to the large power losses when making gear changes. Zeroshift system is the transmission can do shift gears with no time (zero time). It was developed for the automatic manual transmission, and this transmission has been used on racing vehicles to eliminate deceleration when gear shift. Zeroshift transmission still use the clutch to change gear in which electromechanical be used to replace the clutch pedal. Therefore, the transmission is too complex for the transmission of electric vehicles, but its mechanism is considered very suitable to increase the transmission efficiency. From this idea, a new innovation design transmission will be created to electric car. The combination synchromesh with zeroshift mechanism for the manual transmission is a transmission that is ideal for improving the transmission efficiency. Installation synchromesh on zeroshift mechanism is expected to replace the function of the clutch MT, and assisted with the motor torque setting when to change gear. Additionally to consider is the weight of the transmission, ease of manufacturing, ease of installation with an electric motor, as well as ease of use by drivers is a matter that must be done to obtain a new transmission system that is suitable for electric cars.

Study of Terrestrial Radio Determination : Applications and Technology

DOT National Transportation Integrated Search

1979-02-01

The report describes the results of a study of terrestrial radio determination (TRD) applications and technology. Considerable emphasis has been placed on automatic automotive vehicle location or monitoring (AVL or AVM) systems because almost all of ...

Adaptive driving beam headlights : visibility, glare and measurement considerations.

DOT National Transportation Integrated Search

2016-06-01

Recent developments in solid-state lighting, sensor and control technologies are making new : configurations for vehicle forward lighting feasible. Building on systems that automatically switch from : high- to low-beam headlights in the presence of o...

78 FR 8101 - Codex Alimentarius Commission: Meeting of the Codex Committee on Food Additives

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-05

... the building and its parking area. If you require parking, please include the vehicle make and tag... offers an electronic mail subscription service which provides automatic and customized access to selected...

The NavTrax fleet management system

NASA Astrophysics Data System (ADS)

McLellan, James F.; Krakiwsky, Edward J.; Schleppe, John B.; Knapp, Paul L.

The NavTrax System, a dispatch-type automatic vehicle location and navigation system, is discussed. Attention is given to its positioning, communication, digital mapping, and dispatch center components. The positioning module is a robust GPS (Global Positioning System)-based system integrated with dead reckoning devices by a decentralized-federated filter, making the module fault tolerant. The error behavior and characteristics of GPS, rate gyro, compass, and odometer sensors are discussed. The communications module, as presently configured, utilizes UHF radio technology, and plans are being made to employ a digital cellular telephone system. Polling and automatic smart vehicle reporting are also discussed. The digital mapping component is an intelligent digital single line road network database stored in vector form with full connectivity and address ranges. A limited form of map matching is performed for the purposes of positioning, but its main purpose is to define location once position is determined.

Kickdown control for a motor vehicle automatic transmission with two stage kickdown

DOE Office of Scientific and Technical Information (OSTI.GOV)

Higashi, H.; Waki, K.; Fukuiri, M.

This patent describes a vehicle automatic transmission. This transmission consists of a hydraulic torque converter, a transmission gear mechanism connected with the torque converter and has at least three gear stages of different gear ratios for foward drive, friction for selecting one of the gear stages. A kick down control which consists of a first shift down circuit for controlling the friction so that the transmission gear mechanism is shifted down from a high gear stage to a lower gear stage. A kick down solenoid is provided in the first shift down circuit for controlling the first shift down circuitmore » and a kick down switch is adapted to be actuated by an engine control member. When the engine control member is moved substantially to a full power position to thereby control the kick down solenoid effects a shift down from a high gear stage to a lower gear stage.« less

Multi Sensor Data Integration for AN Accurate 3d Model Generation

NASA Astrophysics Data System (ADS)

Chhatkuli, S.; Satoh, T.; Tachibana, K.

2015-05-01

The aim of this paper is to introduce a novel technique of data integration between two different data sets, i.e. laser scanned RGB point cloud and oblique imageries derived 3D model, to create a 3D model with more details and better accuracy. In general, aerial imageries are used to create a 3D city model. Aerial imageries produce an overall decent 3D city models and generally suit to generate 3D model of building roof and some non-complex terrain. However, the automatically generated 3D model, from aerial imageries, generally suffers from the lack of accuracy in deriving the 3D model of road under the bridges, details under tree canopy, isolated trees, etc. Moreover, the automatically generated 3D model from aerial imageries also suffers from undulated road surfaces, non-conforming building shapes, loss of minute details like street furniture, etc. in many cases. On the other hand, laser scanned data and images taken from mobile vehicle platform can produce more detailed 3D road model, street furniture model, 3D model of details under bridge, etc. However, laser scanned data and images from mobile vehicle are not suitable to acquire detailed 3D model of tall buildings, roof tops, and so forth. Our proposed approach to integrate multi sensor data compensated each other's weakness and helped to create a very detailed 3D model with better accuracy. Moreover, the additional details like isolated trees, street furniture, etc. which were missing in the original 3D model derived from aerial imageries could also be integrated in the final model automatically. During the process, the noise in the laser scanned data for example people, vehicles etc. on the road were also automatically removed. Hence, even though the two dataset were acquired in different time period the integrated data set or the final 3D model was generally noise free and without unnecessary details.

Automatic patient respiration failure detection system with wireless transmission

NASA Technical Reports Server (NTRS)

Dimeff, J.; Pope, J. M.

1968-01-01

Automatic respiration failure detection system detects respiration failure in patients with a surgically implanted tracheostomy tube, and actuates an audible and/or visual alarm. The system incorporates a miniature radio transmitter so that the patient is unencumbered by wires yet can be monitored from a remote location.

[Micron]ADS-B Detect and Avoid Flight Tests on Phantom 4 Unmanned Aircraft System

NASA Technical Reports Server (NTRS)

Arteaga, Ricardo; Dandachy, Mike; Truong, Hong; Aruljothi, Arun; Vedantam, Mihir; Epperson, Kraettli; McCartney, Reed

2018-01-01

Researchers at the National Aeronautics and Space Administration Armstrong Flight Research Center in Edwards, California and Vigilant Aerospace Systems collaborated for the flight-test demonstration of an Automatic Dependent Surveillance-Broadcast based collision avoidance technology on a small unmanned aircraft system equipped with the uAvionix Automatic Dependent Surveillance-Broadcast transponder. The purpose of the testing was to demonstrate that National Aeronautics and Space Administration / Vigilant software and algorithms, commercialized as the FlightHorizon UAS"TM", are compatible with uAvionix hardware systems and the DJI Phantom 4 small unmanned aircraft system. The testing and demonstrations were necessary for both parties to further develop and certify the technology in three key areas: flights beyond visual line of sight, collision avoidance, and autonomous operations. The National Aeronautics and Space Administration and Vigilant Aerospace Systems have developed and successfully flight-tested an Automatic Dependent Surveillance-Broadcast Detect and Avoid system on the Phantom 4 small unmanned aircraft system. The Automatic Dependent Surveillance-Broadcast Detect and Avoid system architecture is especially suited for small unmanned aircraft systems because it integrates: 1) miniaturized Automatic Dependent Surveillance-Broadcast hardware; 2) radio data-link communications; 3) software algorithms for real-time Automatic Dependent Surveillance-Broadcast data integration, conflict detection, and alerting; and 4) a synthetic vision display using a fully-integrated National Aeronautics and Space Administration geobrowser for three dimensional graphical representations for ownship and air traffic situational awareness. The flight-test objectives were to evaluate the performance of Automatic Dependent Surveillance-Broadcast Detect and Avoid collision avoidance technology as installed on two small unmanned aircraft systems. In December 2016, four flight tests were conducted at Edwards Air Force Base. Researchers in the ground control station looking at displays were able to verify the Automatic Dependent Surveillance-Broadcast target detection and collision avoidance resolutions.

Design Description of the X-33 Avionics Architecture

NASA Technical Reports Server (NTRS)

Reichenfeld, Curtis J.; Jones, Paul G.

1999-01-01

In this paper, we provide a design description of the X-33 avionics architecture. The X-33 is an autonomous Single Stage to Orbit (SSTO) launch vehicle currently being developed by Lockheed Martin for NASA as a technology demonstrator for the VentureStar Reusable Launch Vehicle (RLV). The X-33 avionics provides autonomous control of die vehicle throughout takeoff, ascent, descent, approach, landing, rollout, and vehicle safing. During flight the avionics provides communication to the range through uplinked commands and downlinked telemetry. During pre-launch and post-safing activities, the avionics provides interfaces to ground support consoles that perform vehicle flight preparations and maintenance. The X-33 Avionics is a hybrid of centralized and distributed processing elements connected by three dual redundant Mil-Std 1553 data buses. These data buses are controlled by a central processing suite located in the avionics bay and composed of triplex redundant Vehicle Mission Computers (VMCs). The VMCs integrate mission management, guidance, navigation, flight control, subsystem control and redundancy management functions. The vehicle sensors, effectors and subsystems are interfaced directly to the centralized VMCs as remote terminals or through dual redundant Data Interface Units (DIUs). The DIUs are located forward and aft of the avionics bay and provide signal conditioning, health monitoring, low level subsystem control and data interface functions. Each VMC is connected to all three redundant 1553 data buses for monitoring and provides a complete identical data set to the processing algorithms. This enables bus faults to be detected and reconfigured through a voted bus control configuration. Data is also shared between VMCs though a cross channel data link that is implemented in hardware and controlled by AlliedSignal's Fault Tolerant Executive (FTE). The FTE synchronizes processors within the VMC and synchronizes redundant VMCs to each other. The FTE provides an output-voting plane to detect, isolate and contain faults due to internal hardware or software faults and reconfigures the VMCs to accommodate these faults. Critical data in the 1553 messages are scheduled and synchronized to specific processing frames in order to minimize data latency. In order to achieve an open architecture, military and commercial off-the-shelf equipment is incorporated using common processors, standard VME backplanes and chassis, the VxWorks operating system, and MartixX for automatic code generation. The use of off-the-shelf tools and equipment helps reduce development time and enables software reuse. The open architecture allows for technology insertion, while the distributed modular elements allow for expansion to increased redundancy levels to meet the higher reliability goals of future RLVs.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

PubMed Central

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-01-01

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

License Plate Recognition System for Indian Vehicles

NASA Astrophysics Data System (ADS)

Sanap, P. R.; Narote, S. P.

2010-11-01

We consider the task of recognition of Indian vehicle number plates (also called license plates or registration plates in other countries). A system for Indian number plate recognition must cope with wide variations in the appearance of the plates. Each state uses its own range of designs with font variations between the designs. Also, vehicle owners may place the plates inside glass covered frames or use plates made of nonstandard materials. These issues compound the complexity of automatic number plate recognition, making existing approaches inadequate. We have developed a system that incorporates a novel combination of image processing and artificial neural network technologies to successfully locate and read Indian vehicle number plates in digital images. Commercial application of the system is envisaged.

Convolution neural-network-based detection of lung structures

NASA Astrophysics Data System (ADS)

Hasegawa, Akira; Lo, Shih-Chung B.; Freedman, Matthew T.; Mun, Seong K.

1994-05-01

Chest radiography is one of the most primary and widely used techniques in diagnostic imaging. Nowadays with the advent of digital radiology, the digital medical image processing techniques for digital chest radiographs have attracted considerable attention, and several studies on the computer-aided diagnosis (CADx) as well as on the conventional image processing techniques for chest radiographs have been reported. In the automatic diagnostic process for chest radiographs, it is important to outline the areas of the lungs, the heart, and the diaphragm. This is because the original chest radiograph is composed of important anatomic structures and, without knowing exact positions of the organs, the automatic diagnosis may result in unexpected detections. The automatic extraction of an anatomical structure from digital chest radiographs can be a useful tool for (1) the evaluation of heart size, (2) automatic detection of interstitial lung diseases, (3) automatic detection of lung nodules, and (4) data compression, etc. Based on the clearly defined boundaries of heart area, rib spaces, rib positions, and rib cage extracted, one should be able to use this information to facilitate the tasks of the CADx on chest radiographs. In this paper, we present an automatic scheme for the detection of lung field from chest radiographs by using a shift-invariant convolution neural network. A novel algorithm for smoothing boundaries of lungs is also presented.

Neural network model for automatic traffic incident detection : executive summary.

DOT National Transportation Integrated Search

2001-04-01

Automatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. In this research, a multi-paradigm intelli...

Improved Real-Time Scan Matching Using Corner Features

NASA Astrophysics Data System (ADS)

Mohamed, H. A.; Moussa, A. M.; Elhabiby, M. M.; El-Sheimy, N.; Sesay, Abu B.

2016-06-01

The automation of unmanned vehicle operation has gained a lot of research attention, in the last few years, because of its numerous applications. The vehicle localization is more challenging in indoor environments where absolute positioning measurements (e.g. GPS) are typically unavailable. Laser range finders are among the most widely used sensors that help the unmanned vehicles to localize themselves in indoor environments. Typically, automatic real-time matching of the successive scans is performed either explicitly or implicitly by any localization approach that utilizes laser range finders. Many accustomed approaches such as Iterative Closest Point (ICP), Iterative Matching Range Point (IMRP), Iterative Dual Correspondence (IDC), and Polar Scan Matching (PSM) handles the scan matching problem in an iterative fashion which significantly affects the time consumption. Furthermore, the solution convergence is not guaranteed especially in cases of sharp maneuvers or fast movement. This paper proposes an automated real-time scan matching algorithm where the matching process is initialized using the detected corners. This initialization step aims to increase the convergence probability and to limit the number of iterations needed to reach convergence. The corner detection is preceded by line extraction from the laser scans. To evaluate the probability of line availability in indoor environments, various data sets, offered by different research groups, have been tested and the mean numbers of extracted lines per scan for these data sets are ranging from 4.10 to 8.86 lines of more than 7 points. The set of all intersections between extracted lines are detected as corners regardless of the physical intersection of these line segments in the scan. To account for the uncertainties of the detected corners, the covariance of the corners is estimated using the extracted lines variances. The detected corners are used to estimate the transformation parameters between the successive scan using least squares. These estimated transformation parameters are used to calculate an adjusted initialization for scan matching process. The presented method can be employed solely to match the successive scans and also can be used to aid other accustomed iterative methods to achieve more effective and faster converge. The performance and time consumption of the proposed approach is compared with ICP algorithm alone without initialization in different scenarios such as static period, fast straight movement, and sharp manoeuvers.

Electronic System for Preventing Airport Runway Incursions

NASA Technical Reports Server (NTRS)

Dabney, Richard; Elrod, Susan

2009-01-01

A proposed system of portable illuminated signs, electronic monitoring equipment, and radio-communication equipment for preventing (or taking corrective action in response to) improper entry of aircraft, pedestrians, or ground vehicles onto active airport runways is described. The main overall functions of the proposed system would be to automatically monitor aircraft ground traffic on or approaching runways and to generate visible and/or audible warnings to affected pilots, ground-vehicle drivers, and control-tower personnel when runway incursions take place.

Progress 28 supply vehicle approach

NASA Image and Video Library

2008-02-07

ISS016-E-027761 (7 Feb. 2008) --- Backdropped by a colorful Earth, an unpiloted Progress supply vehicle approaches the International Space Station. Progress 28 resupply craft launched at 7:03 a.m. (CST) on Feb. 5, 2008 from the Baikonur Cosmodrome in Kazakhstan to deliver more than 2.5 tons of food, fuel, oxygen and other supplies to the Expedition 16 crewmembers onboard the station. Progress automatically docked to the Pirs Docking Compartment at 8:30 a.m. (CST) on Feb. 7.

Progress 28 supply vehicle approach

NASA Image and Video Library

2008-02-07

ISS016-E-027815 (7 Feb. 2008) --- Backdropped by a colorful Earth, an unpiloted Progress supply vehicle approaches the International Space Station. Progress 28 resupply craft launched at 7:03 a.m. (CST) on Feb. 5, 2008 from the Baikonur Cosmodrome in Kazakhstan to deliver more than 2.5 tons of food, fuel, oxygen and other supplies to the Expedition 16 crewmembers onboard the station. Progress automatically docked to the Pirs Docking Compartment at 8:30 a.m. (CST) on Feb. 7.

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares.

PubMed

Van De Gucht, Tim; Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen; Saeys, Wouter

2017-10-08

Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system's potential adoption rate.

Intelligence Level Performance Standards Research for Autonomous Vehicles

PubMed Central

Bostelman, Roger B.; Hong, Tsai H.; Messina, Elena

2017-01-01

United States and European safety standards have evolved to protect workers near Automatic Guided Vehicles (AGV’s). However, performance standards for AGV’s and mobile robots have only recently begun development. Lessons can be learned from research and standards efforts for mobile robots applied to emergency response and military applications. Research challenges, tests and evaluations, and programs to develop higher intelligence levels for vehicles can also used to guide industrial AGV developments towards more adaptable and intelligent systems. These other efforts also provide useful standards development criteria for AGV performance test methods. Current standards areas being considered for AGVs are for docking, navigation, obstacle avoidance, and the ground truth systems that measure performance. This paper provides a look to the future with standards developments in both the performance of vehicles and the dynamic perception systems that measure intelligent vehicle performance. PMID:28649189

Intelligence Level Performance Standards Research for Autonomous Vehicles.

PubMed

Bostelman, Roger B; Hong, Tsai H; Messina, Elena

2015-01-01

United States and European safety standards have evolved to protect workers near Automatic Guided Vehicles (AGV's). However, performance standards for AGV's and mobile robots have only recently begun development. Lessons can be learned from research and standards efforts for mobile robots applied to emergency response and military applications. Research challenges, tests and evaluations, and programs to develop higher intelligence levels for vehicles can also used to guide industrial AGV developments towards more adaptable and intelligent systems. These other efforts also provide useful standards development criteria for AGV performance test methods. Current standards areas being considered for AGVs are for docking, navigation, obstacle avoidance, and the ground truth systems that measure performance. This paper provides a look to the future with standards developments in both the performance of vehicles and the dynamic perception systems that measure intelligent vehicle performance.

Improvement in vehicle agility and stability by G-Vectoring control

NASA Astrophysics Data System (ADS)

Yamakado, Makoto; Takahashi, Jyunya; Saito, Shinjiro; Yokoyama, Atsushi; Abe, Masato

2010-12-01

We extracted a trade-off strategy between longitudinal traction/braking force and cornering force by using jerk information through observing an expert driver's voluntary braking and turning action. Using the expert driver's strategy, we developed a new control concept, called 'G-Vectoring control', which is an automatic longitudinal acceleration control (No DYC) in accordance with the vehicle's lateral jerk caused by the driver's steering manoeuvres. With the control, the direction of synthetic acceleration (G) changes seamlessly (i.e. vectoring). The improvements in vehicle agility and stability were evaluated by theoretical analysis and through computer simulation. We then introduced a 'G-Vectoring' equipped test vehicle realised by brake-by-wire technology and executed a detailed examination on a test track. We have confirmed that the vehicle motion in view of both handling and ride quality has improved dramatically.

Automatic zebrafish heartbeat detection and analysis for zebrafish embryos.

PubMed

Pylatiuk, Christian; Sanchez, Daniela; Mikut, Ralf; Alshut, Rüdiger; Reischl, Markus; Hirth, Sofia; Rottbauer, Wolfgang; Just, Steffen

2014-08-01

A fully automatic detection and analysis method of heartbeats in videos of nonfixed and nonanesthetized zebrafish embryos is presented. This method reduces the manual workload and time needed for preparation and imaging of the zebrafish embryos, as well as for evaluating heartbeat parameters such as frequency, beat-to-beat intervals, and arrhythmicity. The method is validated by a comparison of the results from automatic and manual detection of the heart rates of wild-type zebrafish embryos 36-120 h postfertilization and of embryonic hearts with bradycardia and pauses in the cardiac contraction.

Automatic detection of larynx cancer from contrast-enhanced magnetic resonance images

NASA Astrophysics Data System (ADS)

Doshi, Trushali; Soraghan, John; Grose, Derek; MacKenzie, Kenneth; Petropoulakis, Lykourgos

2015-03-01

Detection of larynx cancer from medical imaging is important for the quantification and for the definition of target volumes in radiotherapy treatment planning (RTP). Magnetic resonance imaging (MRI) is being increasingly used in RTP due to its high resolution and excellent soft tissue contrast. Manually detecting larynx cancer from sequential MRI is time consuming and subjective. The large diversity of cancer in terms of geometry, non-distinct boundaries combined with the presence of normal anatomical regions close to the cancer regions necessitates the development of automatic and robust algorithms for this task. A new automatic algorithm for the detection of larynx cancer from 2D gadoliniumenhanced T1-weighted (T1+Gd) MRI to assist clinicians in RTP is presented. The algorithm employs edge detection using spatial neighborhood information of pixels and incorporates this information in a fuzzy c-means clustering process to robustly separate different tissues types. Furthermore, it utilizes the information of the expected cancerous location for cancer regions labeling. Comparison of this automatic detection system with manual clinical detection on real T1+Gd axial MRI slices of 2 patients (24 MRI slices) with visible larynx cancer yields an average dice similarity coefficient of 0.78+/-0.04 and average root mean square error of 1.82+/-0.28 mm. Preliminary results show that this fully automatic system can assist clinicians in RTP by obtaining quantifiable and non-subjective repeatable detection results in a particular time-efficient and unbiased fashion.

EVA Metro Sedan electric-propulsion system: test and evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reimers, E.

1979-09-01

The procedure and results of the performance evaluation of the EVA Metro Sedan (car No. 1) variable speed dc chopper motor drive and its three speed automatic transmission are presented. The propulsion system for a battery powered vehicle manufactured by Electric Vehicle Associates, Valley View, Ohio, was removed from the vehicle, mounted on the programmable electric dynamometer test facility and evaluated with the aid of a hp 3052A Data Acquisition System. Performance data for the automatic transmission, the solid state dc motor speed controller, and the dc motor in the continuous and pulsating dc power mode, as derived on themore » dynamometer test facility, as well as the entire propulsion system are given. This concept and the system's components were evaluated in terms of commercial applicability, maintainability, and energy utility to establish a design base for the further development of this system or similar propulsion drives. The propulsion system of the EVA Metro Sedan is powered by sixteen 6-volt traction batteries, Type EV 106 (Exide Battery Mfg. Co.). A thyristor controlled cable form Pulsomatic Mark 10 controller, actuated by a foot throttle, controls the voltage applied to a dc series field motor, rated at 10 hp at 3800 rpm (Baldor Electric Co.). Gear speed reduction to the wheel is accomplished by the original equipment three speed automatic transmission with torque converter (Renault 12 Sedan). The brake consists of a power-assisted, hydraulic braking system with front wheel disk and rear drum. An ability to recuperate electric energy with subsequent storage in the battery power supply is not provided.« less

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PubMed

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

Reducing impaired-driving recidivism using advanced vehicle-based alcohol detection systems : a report to Congress

DOT National Transportation Integrated Search

2007-12-01

Vehicle-based alcohol detection systems use technologies designed to detect the presence of alcohol in a driver. Technology suitable for use in all vehicles that will detect an impaired driver faces many challenges including public acceptability, pas...

A stereo vision-based obstacle detection system in vehicles

NASA Astrophysics Data System (ADS)

Huh, Kunsoo; Park, Jaehak; Hwang, Junyeon; Hong, Daegun

2008-02-01

Obstacle detection is a crucial issue for driver assistance systems as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision with the front vehicle. The vision-based obstacle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an obstacle detection system using stereo vision sensors is developed. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the obstacles. The proposed system can detect a front obstacle, a leading vehicle and a vehicle cutting into the lane. Then, the position parameters of the obstacles and leading vehicles can be obtained. The proposed obstacle detection system is implemented on a passenger car and its performance is verified experimentally.

Automatically Detecting Likely Edits in Clinical Notes Created Using Automatic Speech Recognition

PubMed Central

Lybarger, Kevin; Ostendorf, Mari; Yetisgen, Meliha

2017-01-01

The use of automatic speech recognition (ASR) to create clinical notes has the potential to reduce costs associated with note creation for electronic medical records, but at current system accuracy levels, post-editing by practitioners is needed to ensure note quality. Aiming to reduce the time required to edit ASR transcripts, this paper investigates novel methods for automatic detection of edit regions within the transcripts, including both putative ASR errors but also regions that are targets for cleanup or rephrasing. We create detection models using logistic regression and conditional random field models, exploring a variety of text-based features that consider the structure of clinical notes and exploit the medical context. Different medical text resources are used to improve feature extraction. Experimental results on a large corpus of practitioner-edited clinical notes show that 67% of sentence-level edits and 45% of word-level edits can be detected with a false detection rate of 15%. PMID:29854187

Detecting targets hidden in random forests

NASA Astrophysics Data System (ADS)

Kouritzin, Michael A.; Luo, Dandan; Newton, Fraser; Wu, Biao

2009-05-01

Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.

Differential Visual Processing of Animal Images, with and without Conscious Awareness

PubMed Central

Zhu, Weina; Drewes, Jan; Peatfield, Nicholas A.; Melcher, David

2016-01-01

The human visual system can quickly and efficiently extract categorical information from a complex natural scene. The rapid detection of animals in a scene is one compelling example of this phenomenon, and it suggests the automatic processing of at least some types of categories with little or no attentional requirements (Li et al., 2002, 2005). The aim of this study is to investigate whether the remarkable capability to categorize complex natural scenes exist in the absence of awareness, based on recent reports that “invisible” stimuli, which do not reach conscious awareness, can still be processed by the human visual system (Pasley et al., 2004; Williams et al., 2004; Fang and He, 2005; Jiang et al., 2006, 2007; Kaunitz et al., 2011a). In two experiments, we recorded event-related potentials (ERPs) in response to animal and non-animal/vehicle stimuli in both aware and unaware conditions in a continuous flash suppression (CFS) paradigm. Our results indicate that even in the “unseen” condition, the brain responds differently to animal and non-animal/vehicle images, consistent with rapid activation of animal-selective feature detectors prior to, or outside of, suppression by the CFS mask. PMID:27790106

Differential Visual Processing of Animal Images, with and without Conscious Awareness.

PubMed

Zhu, Weina; Drewes, Jan; Peatfield, Nicholas A; Melcher, David

2016-01-01

The human visual system can quickly and efficiently extract categorical information from a complex natural scene. The rapid detection of animals in a scene is one compelling example of this phenomenon, and it suggests the automatic processing of at least some types of categories with little or no attentional requirements (Li et al., 2002, 2005). The aim of this study is to investigate whether the remarkable capability to categorize complex natural scenes exist in the absence of awareness, based on recent reports that "invisible" stimuli, which do not reach conscious awareness, can still be processed by the human visual system (Pasley et al., 2004; Williams et al., 2004; Fang and He, 2005; Jiang et al., 2006, 2007; Kaunitz et al., 2011a). In two experiments, we recorded event-related potentials (ERPs) in response to animal and non-animal/vehicle stimuli in both aware and unaware conditions in a continuous flash suppression (CFS) paradigm. Our results indicate that even in the "unseen" condition, the brain responds differently to animal and non-animal/vehicle images, consistent with rapid activation of animal-selective feature detectors prior to, or outside of, suppression by the CFS mask.

Measurement of signal use and vehicle turns as indication of driver cognition.

PubMed

Wallace, Bruce; Goubran, Rafik; Knoefel, Frank

2014-01-01

This paper uses data analytics to provide a method for the measurement of a key driving task, turn signal usage as a measure of an automatic over-learned cognitive function drivers. The paper augments previously reported more complex executive function cognition measures by proposing an algorithm that analyzes dashboard video to detect turn indicator use with 100% accuracy without any false positives. The paper proposes two algorithms that determine the actual turns made on a trip. The first through analysis of GPS location traces for the vehicle, locating 73% of the turns made with a very low false positive rate of 3%. A second algorithm uses GIS tools to retroactively create turn by turn directions. Fusion of GIS and GPS information raises performance to 77%. The paper presents the algorithm required to measure signal use for actual turns by realigning the 0.2Hz GPS data, 30fps video and GIS turn events. The result is a measure that can be tracked over time and changes in the driver's performance can result in alerts to the driver, caregivers or clinicians as indication of cognitive change. A lack of decline can also be shared as reassurance.

Neural network model for automatic traffic incident detection : final report, August 2001.

DOT National Transportation Integrated Search

2001-08-01

Automatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. In this research, a multi-paradigm intelli...

Detecting cheaters without thinking: testing the automaticity of the cheater detection module.

PubMed

Van Lier, Jens; Revlin, Russell; De Neys, Wim

2013-01-01

Evolutionary psychologists have suggested that our brain is composed of evolved mechanisms. One extensively studied mechanism is the cheater detection module. This module would make people very good at detecting cheaters in a social exchange. A vast amount of research has illustrated performance facilitation on social contract selection tasks. This facilitation is attributed to the alleged automatic and isolated operation of the module (i.e., independent of general cognitive capacity). This study, using the selection task, tested the critical automaticity assumption in three experiments. Experiments 1 and 2 established that performance on social contract versions did not depend on cognitive capacity or age. Experiment 3 showed that experimentally burdening cognitive resources with a secondary task had no impact on performance on the social contract version. However, in all experiments, performance on a non-social contract version did depend on available cognitive capacity. Overall, findings validate the automatic and effortless nature of social exchange reasoning.

Developing an Active Traffic Management System for I-70 in Colorado

DOT National Transportation Integrated Search

2012-09-01

The Colorado DOT is at the forefront of developing an Active Traffic Management (ATM) system that not only : considers operation aspects, but also integrates safety measures. In this research, data collected from Automatic : Vehicle Identification (A...

Synthesis on GPS/AVL equipment used for winter maintenance : final report.

DOT National Transportation Integrated Search

2016-07-01

This project gathered information about available Global Positioning Systems/Automatic Vehicle Location (GPS/AVL) equipment and vendors to gain an understanding of their use by state and local agencies for winter maintenance activities. Depending on ...

23 CFR 771.117 - Categorical exclusions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... management systems, electronic payment equipment, automatic vehicle locaters, automated passenger counters..., reconstruction, adding shoulders, or adding auxiliary lanes (e.g., parking, weaving, turning, climbing). (2... fringe parking facilities. (5) Construction of new truck weigh stations or rest areas. (6) Approvals for...

77 FR 5483 - Codex Alimentarius Commission: Meeting of the Codex Committee on Food Additives

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-03

... building and its parking area. If you require parking, please include the vehicle make and tag number when..., FSIS offers an electronic mail subscription service which provides automatic and customized access to...

Automatic Detection of Student Mental Models during Prior Knowledge Activation in MetaTutor

ERIC Educational Resources Information Center

Rus, Vasile; Lintean, Mihai; Azevedo, Roger

2009-01-01

This paper presents several methods to automatically detecting students' mental models in MetaTutor, an intelligent tutoring system that teaches students self-regulatory processes during learning of complex science topics. In particular, we focus on detecting students' mental models based on student-generated paragraphs during prior knowledge…

AVID - A design system for technology studies of advanced transportation concepts. [Aerospace Vehicle Interactive Design

NASA Technical Reports Server (NTRS)

Wilhite, A. W.; Rehder, J. J.

1979-01-01

The basic AVID (Aerospace Vehicle Interactive Design) is a general system for conceptual and preliminary design currently being applied to a broad range of future space transportation and spacecraft vehicle concepts. AVID hardware includes a minicomputer allowing rapid designer interaction. AVID software includes (1) an executive program and communication data base which provide the automated capability to couple individual programs, either individually in an interactive mode or chained together in an automatic sequence mode; and (2) the individual technology and utility programs which provide analysis capability in areas such as graphics, aerodynamics, propulsion, flight performance, weights, sizing, and costs.

Real-Time Charging Strategies for an Electric Vehicle Aggregator to Provide Ancillary Services

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenzel, George; Negrete-Pincetic, Matias; Olivares, Daniel E.

Real-time charging strategies, in the context of vehicle to grid (V2G) technology, are needed to enable the use of electric vehicle (EV) fleets batteries to provide ancillary services (AS). Here, we develop tools to manage charging and discharging in a fleet to track an Automatic Generation Control (AGC) signal when aggregated. We also propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing Model Predictive Control (MPC). Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.

Automatic Aircraft Structural Topology Generation for Multidisciplinary Optimization and Weight Estimation

NASA Technical Reports Server (NTRS)

Sensmeier, Mark D.; Samareh, Jamshid A.

2005-01-01

An approach is proposed for the application of rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process. This should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. A demonstration of this process is shown for two sample aircraft wing designs.

Real-Time Charging Strategies for an Electric Vehicle Aggregator to Provide Ancillary Services

DOE PAGES

Wenzel, George; Negrete-Pincetic, Matias; Olivares, Daniel E.; ...

2017-03-13

Real-time charging strategies, in the context of vehicle to grid (V2G) technology, are needed to enable the use of electric vehicle (EV) fleets batteries to provide ancillary services (AS). Here, we develop tools to manage charging and discharging in a fleet to track an Automatic Generation Control (AGC) signal when aggregated. We also propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing Model Predictive Control (MPC). Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.

Noise abatement and traffic safety: The trade-off of quieter engines and pavements on vehicle detection.

PubMed

Mendonça, C; Freitas, E; Ferreira, J P; Raimundo, I D; Santos, J A

2013-03-01

Road traffic sounds are a major source of noise pollution in urban areas. But recent developments such as low noise pavements and hybrid/electric engine vehicles cast an optimistic outlook over such an environmental problem. However, it can be argued that engine, tire, and road noise could be relevant sources of information to avoid road traffic conflicts and accidents. In this paper, we analyze the potential trade-offs of traffic-noise abatement approaches in an experimental study, focusing for the first time on the impact and interaction of relevant factors such as pavement type, vehicle type, listener's age, and background noise, on vehicle detection levels. Results reveal that vehicle and pavement type significantly affect vehicle detection. Age is a significant factor, as both younger and older people exhibit lower detection levels of incoming vehicles. Low noise pavements combined with all-electric and hybrid vehicles might pose a severe threat to the safety of vulnerable road users. All factors interact simultaneously, and vehicle detection is best predicted by the loudness signal-to-noise ratio. Copyright © 2012 Elsevier Ltd. All rights reserved.

Determining Geometric Parameters of Agricultural Trees from Laser Scanning Data Obtained with Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Hadas, E.; Jozkow, G.; Walicka, A.; Borkowski, A.

2018-05-01

The estimation of dendrometric parameters has become an important issue for agriculture planning and for the efficient management of orchards. Airborne Laser Scanning (ALS) data is widely used in forestry and many algorithms for automatic estimation of dendrometric parameters of individual forest trees were developed. Unfortunately, due to significant differences between forest and fruit trees, some contradictions exist against adopting the achievements of forestry science to agricultural studies indiscriminately. In this study we present the methodology to identify individual trees in apple orchard and estimate heights of individual trees, using high-density LiDAR data (3200 points/m2) obtained with Unmanned Aerial Vehicle (UAV) equipped with Velodyne HDL32-E sensor. The processing strategy combines the alpha-shape algorithm, principal component analysis (PCA) and detection of local minima. The alpha-shape algorithm is used to separate tree rows. In order to separate trees in a single row, we detect local minima on the canopy profile and slice polygons from alpha-shape results. We successfully separated 92 % of trees in the test area. 6 % of trees in orchard were not separated from each other and 2 % were sliced into two polygons. The RMSE of tree heights determined from the point clouds compared to field measurements was equal to 0.09 m, and the correlation coefficient was equal to 0.96. The results confirm the usefulness of LiDAR data from UAV platform in orchard inventory.

Automatic detection of blurred images in UAV image sets

NASA Astrophysics Data System (ADS)

Sieberth, Till; Wackrow, Rene; Chandler, Jim H.

2016-12-01

Unmanned aerial vehicles (UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by an UAV, which have a high ground resolution and good spectral and radiometrical resolution, due to the low flight altitudes combined with a high resolution camera. UAV image flights are also cost effective and have become attractive for many applications including, change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs. This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms. The detection and removal of these images is currently achieved manually, which is both time consuming and prone to error, particularly for large image-sets. To increase the quality of data processing an automated process is necessary, which must be both reliable and quick. This paper describes the development of an automatic filtering process, which is based upon the quantification of blur in an image. Images with known blur are processed digitally to determine a quantifiable measure of image blur. The algorithm is required to process UAV images fast and reliably to relieve the operator from detecting blurred images manually. The newly developed method makes it possible to detect blur caused by linear camera displacement and is based on human detection of blur. Humans detect blurred images best by comparing it to other images in order to establish whether an image is blurred or not. The developed algorithm simulates this procedure by creating an image for comparison using image processing. Creating internally a comparable image makes the method independent of additional images. However, the calculated blur value named SIEDS (saturation image edge difference standard-deviation) on its own does not provide an absolute number to judge if an image is blurred or not. To achieve a reliable judgement of image sharpness the SIEDS value has to be compared to other SIEDS values from the same dataset. The speed and reliability of the method was tested using a range of different UAV datasets. Two datasets will be presented in this paper to demonstrate the effectiveness of the algorithm. The algorithm proves to be fast and the returned values are optically correct, making the algorithm applicable for UAV datasets. Additionally, a close range dataset was processed to determine whether the method is also useful for close range applications. The results show that the method is also reliable for close range images, which significantly extends the field of application for the algorithm.

DALMATIAN: An Algorithm for Automatic Cell Detection and Counting in 3D.

PubMed

Shuvaev, Sergey A; Lazutkin, Alexander A; Kedrov, Alexander V; Anokhin, Konstantin V; Enikolopov, Grigori N; Koulakov, Alexei A

2017-01-01

Current 3D imaging methods, including optical projection tomography, light-sheet microscopy, block-face imaging, and serial two photon tomography enable visualization of large samples of biological tissue. Large volumes of data obtained at high resolution require development of automatic image processing techniques, such as algorithms for automatic cell detection or, more generally, point-like object detection. Current approaches to automated cell detection suffer from difficulties originating from detection of particular cell types, cell populations of different brightness, non-uniformly stained, and overlapping cells. In this study, we present a set of algorithms for robust automatic cell detection in 3D. Our algorithms are suitable for, but not limited to, whole brain regions and individual brain sections. We used watershed procedure to split regional maxima representing overlapping cells. We developed a bootstrap Gaussian fit procedure to evaluate the statistical significance of detected cells. We compared cell detection quality of our algorithm and other software using 42 samples, representing 6 staining and imaging techniques. The results provided by our algorithm matched manual expert quantification with signal-to-noise dependent confidence, including samples with cells of different brightness, non-uniformly stained, and overlapping cells for whole brain regions and individual tissue sections. Our algorithm provided the best cell detection quality among tested free and commercial software.

The Advanced Linked Extended Reconnaissance & Targeting Technology Demonstration project

NASA Astrophysics Data System (ADS)

Edwards, Mark

2008-04-01

The Advanced Linked Extended Reconnaissance & Targeting (ALERT) Technology Demonstration (TD) project is addressing many operational needs of the future Canadian Army's Surveillance and Reconnaissance forces. Using the surveillance system of the Coyote reconnaissance vehicle as an experimental platform, the ALERT TD project aims to significantly enhance situational awareness by fusing multi-sensor and tactical data, developing automated processes, and integrating beyond line-of-sight sensing. The project is exploiting important advances made in computer processing capability, displays technology, digital communications, and sensor technology since the design of the original surveillance system. As the major research area within the project, concepts are discussed for displaying and fusing multi-sensor and tactical data within an Enhanced Operator Control Station (EOCS). The sensor data can originate from the Coyote's own visible-band and IR cameras, laser rangefinder, and ground-surveillance radar, as well as from beyond line-of-sight systems such as mini-UAVs and unattended ground sensors. Video-rate image processing has been developed to assist the operator to detect poorly visible targets. As a second major area of research, automatic target cueing capabilities have been added to the system. These include scene change detection, automatic target detection and aided target recognition algorithms processing both IR and visible-band images to draw the operator's attention to possible targets. The merits of incorporating scene change detection algorithms are also discussed. In the area of multi-sensor data fusion, up to Joint Defence Labs level 2 has been demonstrated. The human factors engineering aspects of the user interface in this complex environment are presented, drawing upon multiple user group sessions with military surveillance system operators. The paper concludes with Lessons Learned from the project. The ALERT system has been used in a number of C4ISR field trials, most recently at Exercise Empire Challenge in China Lake CA, and at Trial Quest in Norway. Those exercises provided further opportunities to investigate operator interactions. The paper concludes with recommendations for future work in operator interface design.

OKCARS : Oklahoma Collision Analysis and Response System.

DOT National Transportation Integrated Search

2012-10-01

By continuously monitoring traffic intersections to automatically detect that a collision or nearcollision : has occurred, automatically call for assistance, and automatically forewarn oncoming traffic, : our OKCARS has the capability to effectively ...

Testing & Evaluation of Close-Range SAR for Monitoring & Automatically Detecting Pavement Conditions

DOT National Transportation Integrated Search

2012-01-01

This report summarizes activities in support of the DOT contract on Testing & Evaluating Close-Range SAR for Monitoring & Automatically Detecting Pavement Conditions & Improve Visual Inspection Procedures. The work of this project was performed by Dr...

Feature-aided multiple target tracking in the image plane

NASA Astrophysics Data System (ADS)

Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

2006-05-01

Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

Low ground clearance vehicle detection and warning.

DOT National Transportation Integrated Search

2015-06-01

A Low Ground Clearance Vehicle Detection : System (LGCVDS) determines if a commercial : motor vehicle can successfully clear a highwayrail : grade crossing and notifies the driver when : his or her vehicle cannot safely traverse the : crossing. That ...

Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images.

PubMed

Kim, Young Jae; Kim, Kwang Gi

2018-01-01

Existing drusen measurement is difficult to use in clinic because it requires a lot of time and effort for visual inspection. In order to resolve this problem, we propose an automatic drusen detection method to help clinical diagnosis of age-related macular degeneration. First, we changed the fundus image to a green channel and extracted the ROI of the macular area based on the optic disk. Next, we detected the candidate group using the difference image of the median filter within the ROI. We also segmented vessels and removed them from the image. Finally, we detected the drusen through Renyi's entropy threshold algorithm. We performed comparisons and statistical analysis between the manual detection results and automatic detection results for 30 cases in order to verify validity. As a result, the average sensitivity was 93.37% (80.95%~100%) and the average DSC was 0.73 (0.3~0.98). In addition, the value of the ICC was 0.984 (CI: 0.967~0.993, p < 0.01), showing the high reliability of the proposed automatic method. We expect that the automatic drusen detection helps clinicians to improve the diagnostic performance in the detection of drusen on fundus image.

A fast automatic target detection method for detecting ships in infrared scenes

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

Research on detection method of UAV obstruction based on binocular vision

NASA Astrophysics Data System (ADS)

Zhu, Xiongwei; Lei, Xusheng; Sui, Zhehao

2018-04-01

For the autonomous obstacle positioning and ranging in the process of UAV (unmanned aerial vehicle) flight, a system based on binocular vision is constructed. A three-stage image preprocessing method is proposed to solve the problem of the noise and brightness difference in the actual captured image. The distance of the nearest obstacle is calculated by using the disparity map that generated by binocular vision. Then the contour of the obstacle is extracted by post-processing of the disparity map, and a color-based adaptive parameter adjustment algorithm is designed to extract contours of obstacle automatically. Finally, the safety distance measurement and obstacle positioning during the UAV flight process are achieved. Based on a series of tests, the error of distance measurement can keep within 2.24% of the measuring range from 5 m to 20 m.

Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

NASA Astrophysics Data System (ADS)

Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

2016-10-01

With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

Shadow detection and removal in RGB VHR images for land use unsupervised classification

NASA Astrophysics Data System (ADS)

Movia, A.; Beinat, A.; Crosilla, F.

2016-09-01

Nowadays, high resolution aerial images are widely available thanks to the diffusion of advanced technologies such as UAVs (Unmanned Aerial Vehicles) and new satellite missions. Although these developments offer new opportunities for accurate land use analysis and change detection, cloud and terrain shadows actually limit benefits and possibilities of modern sensors. Focusing on the problem of shadow detection and removal in VHR color images, the paper proposes new solutions and analyses how they can enhance common unsupervised classification procedures for identifying land use classes related to the CO2 absorption. To this aim, an improved fully automatic procedure has been developed for detecting image shadows using exclusively RGB color information, and avoiding user interaction. Results show a significant accuracy enhancement with respect to similar methods using RGB based indexes. Furthermore, novel solutions derived from Procrustes analysis have been applied to remove shadows and restore brightness in the images. In particular, two methods implementing the so called "anisotropic Procrustes" and the "not-centered oblique Procrustes" algorithms have been developed and compared with the linear correlation correction method based on the Cholesky decomposition. To assess how shadow removal can enhance unsupervised classifications, results obtained with classical methods such as k-means, maximum likelihood, and self-organizing maps, have been compared to each other and with a supervised clustering procedure.

Motor vehicle technology:Mobility for prosperity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1985-01-01

This book presents the papers given at a conference on internal combustion engines for vehicles. Topics considered at the conference included combustion chambers, the lubrication of turbocharged engines, oil filters, fuel consumption, traffic control, crashworthiness, brakes, acceleration, unleaded gasoline, methanol fuels, pressure drop, safety regulations, tire vibration, detergents, fuel economy, ceramics in engines, steels, catalytic converters, fuel additives, heat exchangers, pump systems, emissions control, fuel injection systems, noise pollution control, natural gas fuels, assembly plant productivity, aerodynamics, torsion, electronics, and automatic transmissions.

Expert system applications for army vehicle diagnostics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halle, R.F.

1987-01-01

Bulky manuals, limited training procedures, and complex Automatic Test Equipment are but a few of the problems a mechanic must face when trying to repair many of the military's new and highly complex vehicle systems. Recent technological advances in Expert Systms has given the mechanic the potential to solve many of these problems and to actually enhance his maintenance proficiency. This paper describes both the history of and the future potential of the Expert System and how it could impact on the present military maintenance system.

Solving the AI Planning Plus Scheduling Problem Using Model Checking via Automatic Translation from the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL)

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Munoz, Cesar A.; Siminiceanu, Radu I.

2007-01-01

This paper describes a translator from a new planning language named the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL) model checker. This translator has been developed in support of the Spacecraft Autonomy for Vehicles and Habitats (SAVH) project sponsored by the Exploration Technology Development Program, which is seeking to mature autonomy technology for the vehicles and operations centers of Project Constellation.

Flair-fleet location and information reporting

NASA Technical Reports Server (NTRS)

Norman, E. R.; Dunlap, M. E.

1974-01-01

The FLAIR system, as now produced, automatically updates each vehicle's location and corresponding officer's status once each two seconds and presents this information to police dispatchers in the command and control center. The position of all vehicles available for assignment is displayed on a color video map at each dispatcher's console to an accuracy of 50 feet. This gives the dispatcher a continuous picture of the deployment of the total available force and thus complete command and control of all police under his responsibility.

Systems and Methods for Collaboratively Controlling at Least One Aircraft

NASA Technical Reports Server (NTRS)

Estkowski, Regina I. (Inventor)

2016-01-01

An unmanned vehicle management system includes an unmanned aircraft system (UAS) control station controlling one or more unmanned vehicles (UV), a collaborative routing system, and a communication network connecting the UAS and the collaborative routing system. The collaborative routing system being configured to receive flight parameters from an operator of the UAS control station and, based on the received flight parameters, automatically present the UAS control station with flight plan options to enable the operator to operate the UV in a defined airspace.

Evaluation of skid test automatic digital recording system.

DOT National Transportation Integrated Search

1974-01-01

The Virginia skid vehicle has been equipped with a digital data recording system to provide rapid reduction of skid measurement data. It was found that five to ten minutes are required to evaluate a single measurement using the original analog strip ...

Electronic Toll And Traffic Management Systems, National Cooperative Highway Research Program Synthesis

DOT National Transportation Integrated Search

1993-01-01

ELECTRONIC TOLL COLLECTION OR ETC AND TRAFFIC MANAGEMENT OR ETTM, AUTOMATIC VEHICLE IDENTIFICATION OR AVI : ELECTRONIC TOLL COLLECTION AND TRAFFIC MANAGEMENT (ETTM) SYSTEMS ARE NOT A FUTURISTIC DREAM, THEY ARE OPERATING OR ARE BEING TESTED TODAY I...

Automatic vehicle identification technology applications to toll collection services

DOT National Transportation Integrated Search

1997-01-01

Intelligent transportation systems technologies are being developed and applied through transportation systems in the United States. An example of this type of innovation can be seen on toll roads where a driver is required to deposit a toll in order...

Sources of error in estimating truck traffic from automatic vehicle classification data

DOT National Transportation Integrated Search

1998-10-01

Truck annual average daily traffic estimation errors resulting from sample classification counts are computed in this paper under two scenarios. One scenario investigates an improper factoring procedure that may be used by highway agencies. The study...

Officials nationwide give a green light to automated traffic enforcement

DOT National Transportation Integrated Search

2000-03-11

There has been resistance to using cameras to automatically identify vehicles driven by motorists who run red lights and drive faster than the posted speed limits. Fairness, privacy, and "big brother" have been cited as reasons. The article examines ...

Automatic Detection of Storm Damages Using High-Altitude Photogrammetric Imaging

NASA Astrophysics Data System (ADS)

Litkey, P.; Nurminen, K.; Honkavaara, E.

2013-05-01

The risks of storms that cause damage in forests are increasing due to climate change. Quickly detecting fallen trees, assessing the amount of fallen trees and efficiently collecting them are of great importance for economic and environmental reasons. Visually detecting and delineating storm damage is a laborious and error-prone process; thus, it is important to develop cost-efficient and highly automated methods. Objective of our research project is to investigate and develop a reliable and efficient method for automatic storm damage detection, which is based on airborne imagery that is collected after a storm. The requirements for the method are the before-storm and after-storm surface models. A difference surface is calculated using two DSMs and the locations where significant changes have appeared are automatically detected. In our previous research we used four-year old airborne laser scanning surface model as the before-storm surface. The after-storm DSM was provided from the photogrammetric images using the Next Generation Automatic Terrain Extraction (NGATE) algorithm of Socet Set software. We obtained 100% accuracy in detection of major storm damages. In this investigation we will further evaluate the sensitivity of the storm-damage detection process. We will investigate the potential of national airborne photography, that is collected at no-leaf season, to automatically produce a before-storm DSM using image matching. We will also compare impact of the terrain extraction algorithm to the results. Our results will also promote the potential of national open source data sets in the management of natural disasters.

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system

PubMed Central

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness. PMID:28296902

A real-time digital computer program for the simulation of automatic spacecraft reentries

NASA Technical Reports Server (NTRS)

Kaylor, J. T.; Powell, L. F.; Powell, R. W.

1977-01-01

The automatic reentry flight dynamics simulator, a nonlinear, six-degree-of-freedom simulation, digital computer program, has been developed. The program includes a rotating, oblate earth model for accurate navigation calculations and contains adjustable gains on the aerodynamic stability and control parameters. This program uses a real-time simulation system and is designed to examine entries of vehicles which have constant mass properties whose attitudes are controlled by both aerodynamic surfaces and reaction control thrusters, and which have automatic guidance and control systems. The program has been used to study the space shuttle orbiter entry. This report includes descriptions of the equations of motion used, the control and guidance schemes that were implemented, the program flow and operation, and the hardware involved.

Piloted Simulation of a Model-Predictive Automated Recovery System

NASA Technical Reports Server (NTRS)

Liu, James (Yuan); Litt, Jonathan; Sowers, T. Shane; Owens, A. Karl; Guo, Ten-Huei

2014-01-01

This presentation describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.

Research on vehicle detection based on background feature analysis in SAR images

NASA Astrophysics Data System (ADS)

Zhang, Bochuan; Tang, Bo; Zhang, Cong; Hu, Ruiguang; Yun, Hongquan; Xiao, Liping

2017-10-01

Aiming at vehicle detection on the ground through low resolution SAR images, a method is proposed for determining the region of the vehicles first and then detecting the target in the specific region. The experimental results show that this method not only reduces the target detection area, but also reduces the influence of terrain clutter on the detection, which greatly improves the reliability of the target detection.

The near-term hybrid vehicle program, phase 1

NASA Technical Reports Server (NTRS)

1979-01-01

Performance specifications were determined for a hybrid vehicle designed to achieve the greatest reduction in fuel consumption. Based on the results of systems level studies, a baseline vehicle was constructed with the following basic paramaters: a heat engine power peak of 53 kW (VW gasoline engine); a traction motor power peak of 30 kW (Siemens 1GV1, separately excited); a heat engine fraction of 0.64; a vehicle curb weight of 2080 kg; a lead acid battery (35 kg weight); and a battery weight fraction of 0.17. The heat engine and the traction motor are coupled together with their combined output driving a 3 speed automatic transmission with lockup torque converter. The heat engine is equipped withe a clutch which allows it to be decoupled from the system.

Progress on advanced dc and ac induction drives for electric vehicles

NASA Technical Reports Server (NTRS)

Schwartz, H. J.

1982-01-01

Progress is reported in the development of complete electric vehicle propulsion systems, and the results of tests on the Road Load Simulator of two such systems representative of advanced dc and ac drive technology are presented. One is the system used in the DOE's ETV-1 integrated test vehicle which consists of a shunt wound dc traction motor under microprocessor control using a transistorized controller. The motor drives the vehicle through a fixed ratio transmission. The second system uses an ac induction motor controlled by transistorized pulse width modulated inverter which drives through a two speed automatically shifted transmission. The inverter and transmission both operate under the control of a microprocessor. The characteristics of these systems are also compared with the propulsion system technology available in vehicles being manufactured at the inception of the DOE program and with an advanced, highly integrated propulsion system upon which technology development was recently initiated.

Design of the liquefied natural gas (LNG) vehicle gas cylinder filling semi-physical simulation training and assessment system

NASA Astrophysics Data System (ADS)

Gao, Jie; Zheng, Jianrong; Zhao, Yinghui

2017-08-01

With the rapid development of LNG vehicle in China, the operator's training and assessment of the operating skills cannot operate on material objects, because of Vehicle Gas Cylinder's high pressure, flammable and explosive characteristics. LNG Vehicle Gas Cylinder's filling simulation system with semi-physical simulation technology presents the overall design and procedures of the simulation system, and elaborates the realization of the practical analog machine, data acquisition and control system and the computer software, and introduces the design process of equipment simulation model in detail. According to the designed assessment system of the Vehicle Gas Cylinder, it can obtain the operation on the actual cylinder filling and visual effects for the operator, and automatically record operation, the results of real operation with its software, and achieve the operators' training and assessment of operating skills on mobile special equipment.

Modeling of electromagnetic brakes for enhanced braking capabilities

NASA Astrophysics Data System (ADS)

Kachroo, Pushkin; Ming, Qian

1998-01-01

In automatic highway systems, automatic brake actuation is a very important part of the overall control of the vehicle. Hence, a faster response and a robust braking system are crucial. This paper describes electromagnetic brakes as a supplementary system for regular friction brakes. This system provides better response time for emergency situations, and in general keeps the friction brake working longer and safer. A new mathematical model for electromagnetic brakes is proposed to describe their static characteristics. The performance of the new mathematical model is better than the other three models available in the literature.

Self-propelled automatic chassis of Lunokhod-1: History of creation in episodes

NASA Astrophysics Data System (ADS)

Malenkov, Mikhail

2016-03-01

This report reviews the most important episodes in the history of designing the self-propelled automatic chassis of the first mobile extraterrestrial vehicle in the world, Lunokhod-1. The review considers the issues in designing moon rovers, their essential features, and the particular construction properties of their systems, mechanisms, units, and assemblies. It presents the results of exploiting the chassis of Lunokhod-1 and Lunokhod-2. Analysis of the approaches utilized and engineering solutions reveals their value as well as the consequences of certain defects.

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, J; Yang, D

2015-06-15

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets,more » and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from Varian Medical System.« less

An improvement in rollover detection of articulated vehicles using the grey system theory

NASA Astrophysics Data System (ADS)

Chou, Tao; Chu, Tzyy-Wen

2014-05-01

A Rollover Index combined with the grey system theory, called a Grey Rollover Index (GRI), is proposed to assess the rollover threat for articulated vehicles with a tractor-semitrailer combination. This index can predict future trends of vehicle dynamics based on current vehicle motion; thus, it is suitable for vehicle-rollover detection. Two difficulties are encountered when applying the GRI for rollover detection. The first difficulty is effectively predicting the rollover threat of the vehicles, and the second difficulty is achieving a definite definition of the real rollover timing of a vehicle. The following methods are used to resolve these problems. First, a nonlinear mathematical model is constructed to accurately describe the vehicle dynamics of articulated vehicles. This model is combined with the GRI to predict rollover propensity. Finally, TruckSim™ software is used to determine the real rollover timing and facilitate the accurate supply of information to the rollover detection system through the GRI. This index is used to verify the simulation based on the common manoeuvres that cause rollover accidents to reduce the occurrence of false signals and effectively increase the efficiency of the rollover detection system.

Shadow-Based Vehicle Detection in Urban Traffic

PubMed Central

Ibarra-Arenado, Manuel; Tjahjadi, Tardi; Pérez-Oria, Juan; Robla-Gómez, Sandra; Jiménez-Avello, Agustín

2017-01-01

Vehicle detection is a fundamental task in Forward Collision Avoiding Systems (FACS). Generally, vision-based vehicle detection methods consist of two stages: hypotheses generation and hypotheses verification. In this paper, we focus on the former, presenting a feature-based method for on-road vehicle detection in urban traffic. Hypotheses for vehicle candidates are generated according to the shadow under the vehicles by comparing pixel properties across the vertical intensity gradients caused by shadows on the road, and followed by intensity thresholding and morphological discrimination. Unlike methods that identify the shadow under a vehicle as a road region with intensity smaller than a coarse lower bound of the intensity for road, the thresholding strategy we propose determines a coarse upper bound of the intensity for shadow which reduces false positives rates. The experimental results are promising in terms of detection performance and robustness in day time under different weather conditions and cluttered scenarios to enable validation for the first stage of a complete FACS. PMID:28448465

Slip Ratio Estimation and Regenerative Brake Control for Decelerating Electric Vehicles without Detection of Vehicle Velocity and Acceleration

NASA Astrophysics Data System (ADS)

Suzuki, Toru; Fujimoto, Hiroshi

In slip ratio control systems, it is necessary to detect the vehicle velocity in order to obtain the slip ratio. However, it is very difficult to measure this velocity directly. We have proposed slip ratio estimation and control methods that do not require the vehicle velocity with acceleration. In this paper, the slip ratio estimation and control methods are proposed without detecting the vehicle velocity and acceleration when it is decelerating. We carried out simulations and experiments by using an electric vehicle to verify the effectiveness of the proposed method.

Navy/Marine Corps innovative science and technology developments for future enhanced mine detection capabilities

NASA Astrophysics Data System (ADS)

Holloway, John H., Jr.; Witherspoon, Ned H.; Miller, Richard E.; Davis, Kenn S.; Suiter, Harold R.; Hilton, Russell J.

2000-08-01

JMDT is a Navy/Marine Corps 6.2 Exploratory Development program that is closely coordinated with the 6.4 COBRA acquisition program. The objective of the program is to develop innovative science and technology to enhance future mine detection capabilities. The objective of the program is to develop innovative science and technology to enhance future mine detection capabilities. Prior to transition to acquisition, the COBRA ATD was extremely successful in demonstrating a passive airborne multispectral video sensor system operating in the tactical Pioneer unmanned aerial vehicle (UAV), combined with an integrated ground station subsystem to detect and locate minefields from surf zone to inland areas. JMDT is investigating advanced technology solutions for future enhancements in mine field detection capability beyond the current COBRA ATD demonstrated capabilities. JMDT has recently been delivered next- generation, innovative hardware which was specified by the Coastal System Station and developed under contract. This hardware includes an agile-tuning multispectral, polarimetric, digital video camera and advanced multi wavelength laser illumination technologies to extend the same sorts of multispectral detections from a UAV into the night and over shallow water and other difficult littoral regions. One of these illumination devices is an ultra- compact, highly-efficient near-IR laser diode array. The other is a multi-wavelength range-gateable laser. Additionally, in conjunction with this new technology, algorithm enhancements are being developed in JMDT for future naval capabilities which will outperform the already impressive record of automatic detection of minefields demonstrated by the COBAR ATD.

Cognitive Radio will revolutionize American transportation

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

Cognitive Radio will revolutionize American transportation. Through smart technology, it will anticipate user needs; detect available bandwidths and frequencies then seamlessly connect vehicles, infrastructures, and consumer devices; and it will support the Department of Transportation IntelliDrive Program, helping researchers, auto manufacturers, and Federal and State officials advance the connectivity of US transportation systems for improved safety, mobility, and environmental conditions. Using cognitive radio, a commercial vehicle will know its driver, onboard freight and destination route. Drivers will save time and resources communicating with automatic toll booths and know ahead of time whether to stop at a weigh station or keepmore » rolling. At accident scenes, cognitive radio sensors on freight and transportation modes can alert emergency personnel and measure on-site, real-time conditions such as a chemical leak. The sensors will connect freight to industry, relaying shipment conditions and new delivery schedules. For industry or military purposes, cognitive radio will enable real-time freight tracking around the globe and its sensory technology can help prevent cargo theft or tampering by alerting shipper and receiver if freight is tampered with while en route. For the average consumer, a vehicle will tailor the transportation experience to the passenger such as delivering age-appropriate movies via satellite. Cognitive radio will enhance transportation safety by continually sensing what is important to the user adapting to its environment and incoming information, and proposing solutions that improve mobility and quality of life.« less

Vehicle automation: a remedy for driver stress?

PubMed

Funke, G; Matthews, G; Warm, J S; Emo, A K

2007-08-01

The present study addressed the effects of stress, vehicle automation and subjective state on driver performance and mood in a simulated driving task. A total of 168 college students participated. Participants in the stress-induction condition completed a 'winter' drive, which included periodic loss of control episodes. Participants in the no-stress-induction condition were not exposed to loss of control. An additional, independent manipulation of vehicle speed was also conducted, consisting of two control conditions requiring manual speed regulation and a third in which vehicle speed was automatically regulated by the simulation. Stress and automation both influenced subjective distress, but the two factors did not interact. Driver performance data indicated that vehicle automation impacted performance similarly in the stress and no-stress conditions. Individual differences in subjective stress response and performance were also investigated. Resource theory provides a framework that partially but not completely explains the relationship between vehicle automation and driver stress. Implications for driver workload, safety and training are discussed.