35,803 research outputs found
Saliency difference based objective evaluation method for a superimposed screen of the HUD with various background
The head-up display (HUD) is an emerging device which can project information
on a transparent screen. The HUD has been used in airplanes and vehicles, and
it is usually placed in front of the operator's view. In the case of the
vehicle, the driver can see not only various information on the HUD but also
the backgrounds (driving environment) through the HUD. However, the projected
information on the HUD may interfere with the colors in the background because
the HUD is transparent. For example, a red message on the HUD will be less
noticeable when there is an overlap between it and the red brake light from the
front vehicle. As the first step to solve this issue, how to evaluate the
mutual interference between the information on the HUD and backgrounds is
important. Therefore, this paper proposes a method to evaluate the mutual
interference based on saliency. It can be evaluated by comparing the HUD part
cut from a saliency map of a measured image with the HUD image.Comment: 10 pages, 5 fighres, 1 table, accepted by IFAC-HMS 201
Unmanned Aerial Systems for Wildland and Forest Fires
Wildfires represent an important natural risk causing economic losses, human
death and important environmental damage. In recent years, we witness an
increase in fire intensity and frequency. Research has been conducted towards
the development of dedicated solutions for wildland and forest fire assistance
and fighting. Systems were proposed for the remote detection and tracking of
fires. These systems have shown improvements in the area of efficient data
collection and fire characterization within small scale environments. However,
wildfires cover large areas making some of the proposed ground-based systems
unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial
Systems (UAS) were proposed. UAS have proven to be useful due to their
maneuverability, allowing for the implementation of remote sensing, allocation
strategies and task planning. They can provide a low-cost alternative for the
prevention, detection and real-time support of firefighting. In this paper we
review previous work related to the use of UAS in wildfires. Onboard sensor
instruments, fire perception algorithms and coordination strategies are
considered. In addition, we present some of the recent frameworks proposing the
use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more
efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at:
https://doi.org/10.3390/drones501001
End-to-end Learning of Driving Models from Large-scale Video Datasets
Robust perception-action models should be learned from training data with
diverse visual appearances and realistic behaviors, yet current approaches to
deep visuomotor policy learning have been generally limited to in-situ models
learned from a single vehicle or a simulation environment. We advocate learning
a generic vehicle motion model from large scale crowd-sourced video data, and
develop an end-to-end trainable architecture for learning to predict a
distribution over future vehicle egomotion from instantaneous monocular camera
observations and previous vehicle state. Our model incorporates a novel
FCN-LSTM architecture, which can be learned from large-scale crowd-sourced
vehicle action data, and leverages available scene segmentation side tasks to
improve performance under a privileged learning paradigm.Comment: camera ready for CVPR201
Helicopter human factors research
Helicopter flight is among the most demanding of all human-machine integrations. The inherent manual control complexities of rotorcraft are made even more challenging by the small margin for error created in certain operations, such as nap-of-the-Earth (NOE) flight, by the proximity of the terrain. Accident data recount numerous examples of unintended conflict between helicopters and terrain and attest to the perceptual and control difficulties associated with low altitude flight tasks. Ames Research Center, in cooperation with the U.S. Army Aeroflightdynamics Directorate, has initiated an ambitious research program aimed at increasing safety margins for both civilian and military rotorcraft operations. The program is broad, fundamental, and focused on the development of scientific understandings and technological countermeasures. Research being conducted in several areas is reviewed: workload assessment, prediction, and measure validation; development of advanced displays and effective pilot/automation interfaces; identification of visual cues necessary for low-level, low-visibility flight and modeling of visual flight-path control; and pilot training
Intergrated leachate treatment by sequencing batch reactor (SBR) and micro-zeolite (MZ)
Biological treatment has a lot of potential in leachate treatment with the ability of the biodegradable substrates and this method can reduce the cost of treatment residues with respect to ecological and economical requirements.The aims of this study are to investigate the effect of biological treatment by using sequencing batch reactor (SBR) system in different condition consisting anaerobic (An), anoxic (Ax), and oxic (Ox) with different reaction time. An integration in combining phases consisting An/Ax/Ox is used in order to achieve maximum removal. Then, followed by the performance of combination phases consisting An/Ax/Ox in SBR system with addition of adsorption adsorbent micro-zeolite (MZ) (size range 75-150 μm) at different dosages. The raw leachate and sludge were collected from sanitary landfill from Tanjung Langsat, Pasir Gudang. An condition has better performance in an SBR system at optimum reaction time 11 hr promoting the percentage removal efficiency of chemical oxygen demand (COD), ammonia nitrogen (AN), total nitrogen (TN), total phosphorus (TP) and suspended solid (SS) and turbidity which were 77%, 74.65%, 75.07%, 76.05%, 63.91%, and 62.67% respectively. The result indicated that the combined condition consisting An/Ax/Ox at the optimum time reaction of each condition gives the removal efficiency COD, AN, TN, TP, SS, and turbidity which were 85.78%, 88.65%, 87.07%, 86.9%, 81.92% and 81.15% respectively. The application addition of adsorption adsorbent gives optimum dosage at 5 g/L. The addition of MZ shows good removal efficiency which were more than 90% at overall parameter
Helicopter flights with night-vision goggles: Human factors aspects
Night-vision goggles (NVGs) and, in particular, the advanced, helmet-mounted Aviators Night-Vision-Imaging System (ANVIS) allows helicopter pilots to perform low-level flight at night. It consists of light intensifier tubes which amplify low-intensity ambient illumination (star and moon light) and an optical system which together produce a bright image of the scene. However, these NVGs do not turn night into day, and, while they may often provide significant advantages over unaided night flight, they may also result in visual fatigue, high workload, and safety hazards. These problems reflect both system limitations and human-factors issues. A brief description of the technical characteristics of NVGs and of human night-vision capabilities is followed by a description and analysis of specific perceptual problems which occur with the use of NVGs in flight. Some of the issues addressed include: limitations imposed by a restricted field of view; problems related to binocular rivalry; the consequences of inappropriate focusing of the eye; the effects of ambient illumination levels and of various types of terrain on image quality; difficulties in distance and slope estimation; effects of dazzling; and visual fatigue and superimposed symbology. These issues are described and analyzed in terms of their possible consequences on helicopter pilot performance. The additional influence of individual differences among pilots is emphasized. Thermal imaging systems (forward looking infrared (FLIR)) are described briefly and compared to light intensifier systems (NVGs). Many of the phenomena which are described are not readily understood. More research is required to better understand the human-factors problems created by the use of NVGs and other night-vision aids, to enhance system design, and to improve training methods and simulation techniques
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