No description available.

No description available.

Roadway crashes related to vision obstruction due to fog/smoke (FS) conditions constitute a challenge for traffic engineers. Previous research efforts mostly concentrated on the snow and rain related crashes. Statistics show that Florida is among the top three states in terms of crashes due to vision obstruction by FS. This research culminated in a comprehensive study of fog and smoke related crashes in the state of Florida. The analysis took into account the crashes that occurred between 2003 and 2007 on Florida state roads. Spatial analysis and injury severity analysis have been conducted and significant results have been identified. The spatial analysis by GIS examines the locations of high trends of FS related crashes on state roads in the State of Florida. Statistical features of the GIS tool, which is used efficiently in traffic safety research, has been used to find the crash clusters for the particular types of crashes that occur due to vision obstruction by FS. Several segmentation processes have been used, and the best segmentation for this study was found to be dividing the state roads into 1 mile segments, keeping the roadway characteristics uniform. Taking into account the entire state road network, ten distinct clusters were found that can be clearly associated with these types of crashes. However, no clear pattern in terms of area was observed, as it was seen that the percentage of FS related crashes in rural and urban areas are close. The general characteristics of FS related crashes have been investigated in detail. For the comparison to clear visibility conditions, simple odds ratios (in terms of crash frequencies) have been introduced. The morning hours in the months of December to February are found to be the prevalent time for fog related crashes, while for the smoke related crashes the dangerous time was found to be morning to midday in the month of May. Compared to crashes under clear-visibility conditions, the fog crashes tend to result in more severe injuries and involve more vehicles. Head-on and rear-end crashes are the two most common crash types in terms of crash frequency and severe crashes. For the injury severity analysis, a random effect ordered logistic model was used. The model in brief illustrates that the head-on and rear-end crash types are the two most prevalent crash types in FS conditions. Moreover, these severe crashes mainly occurred at higher speeds. Also they mostly took place on undivided roads, roadways without any sidewalk and two-lane rural roads. Increase of average daily traffic decrease the severity of FS related crashes. Overall, this study provides the Florida Department of Transportation (FDOT) with specific information on where improvements could be made to have better safety conditions in terms of vision obstruction due to FS in the state roads of Florida. Also it suggests the times and seasons that the safety precautions must be taken or the FS warning systems to be installed, and the controlling roadway geometries that can be improved or modified to reduce injury severity of a crash due to FS related vision obstruction.

Nighttime intersection crashes account for nearly half of all the intersection crashes, making them a major traffic safety concern. Although providing lighting at intersections has proven to be a successful countermeasure against these crashes, existing approaches to designing lighting at intersections are overly simplified. Current standards are based on recommending lighting levels, but do not account for the role of human vision or vehicle headlamps or the numerous pedestrian-vehicle conflict locations at intersections. For effective intersection lighting design, empirical evidence is required regarding the effects of lighting configuration (part of the intersection illuminated) and lighting levels on nighttime visibility. This research effort had three goals. The first was to identify an intersection lighting design that results in the best nighttime visibility. The second goal was to determine the effect of illuminance on visual performance at intersections. The third goal was to understand the relationships between object luminance, contrast, and visibility. To achieve these goals, three specific configurations were used, that illuminated the intersection approach (Approach), intersection box (Box), and both the intersection approach and box (Both). Each lighting configuration was evaluated under five levels of illumination. Visibility was assessed both objectively (visual performance) and subjectively (perceptions of visibility and glare). Illuminating the intersection box led to superior visual performance, higher perceived visibility, and lower perceived glare. For this same configuration, plateaus in visual performance and perceived visibility occurred between 8 and 12 lux illuminance levels. A photometric analysis revealed that the Box lighting configuration rendered targets in sufficient positive and negative contrasts to result in higher nighttime visibility. Negatively contrast targets aided visual performance, while for targets rendered in positive contrast visual performance was dependent on the magnitude of the contrast. The relationship between pedestrian contrast and perceived pedestrian visibility was more complex, as pedestrians were often rendered in multiple contrast polarities. These results indicate that Box illumination is an effective strategy to enhance nighttime visual performance and perceptions of visibility while reducing glare, and which may be an energy efficient solution as it requires fewer luminaires. / Ph. D.

The Global Positioning System (GPS) has recently become the significant mapping tool for millions of customers worldwide, providing its users with accurate terrestrial positions almost instantaneously. The functionality of a GPS receiver depends on the number of satellites to which it can establish an unobstructed line of sight. Current satellite availability prediction tools perform satellite visibility predictions without considering terrain or structures that block GPS signals, a major issue in mountainous and urban areas. This paper describes a new Geographic Information Systems (GIS) tool, a customization of ArcGIS named Satellite Viewsheds, which predicts satellite visibility for any place and time while considering line of sight obstructions. Satellite Viewsheds requires a raster surface model, the test date and time, and the orbital properties of the satellites. It produces grids depicting the number of visible satellites and optimal viewing time for every cell in the grid. Satellite Viewsheds allows users to avoid areas of signal loss and choose the best time to map using their GPS receivers. The field test of Satellite Viewsheds proved that the tool performs satellite visibility predictions consistently and accurately. The research outlined in this paper indicates that Satellite Viewsheds is the first tool of its kind. / Master of Science

The analysis of visibility between two points on the earth's terrain is a common use of GIS software. Most commercial GIS software packages include the ability to generate a viewshed, or a map of terrain surrounding a particular location that would be visible to an observer. Viewsheds are often generated using "bare-earth" Digital Elevation Models (DEMs) derived from the process of photogrammetry. More detailed models, known as Digital Surface Models (DSMs), are often generated using Light Detection and Ranging (LIDAR) which uses an airborne laser to scan the terrain. In addition to having greater accuracy than photogrammetric DEMs, LIDAR DSMs include surface features such as buildings and trees. This project used a visibility algorithm to predict visibility between observer and target locations using both photogrammetric DEMs and LIDAR DSMs of varying resolution. A field survey of the locations was conducted to determine the accuracy of the visibility predictions and to gauge the extent to which the presence of surface features in the DSMs affected the accuracy. The use of different resolution terrain models allowed for the analysis of the relationship between accuracy and optimal grid size. Additionally, a series of visibility predictions were made using Monte Carlo methods to add random error to the terrain elevation to estimate the probability of a target's being visible. Finally, the LIDAR DSMs were used to determine the linear distance of terrain along the lines-of-sight between the observer and targets that were obscured by trees or bushes. A logistic regression was performed between that distance and the visibility of the target to determine the extent to which a greater amount of vegetation along the line-of-sight impacted the target's visibility. / Master of Science

The number of skyscrapers are increasing rapidly across the world. Interest is growing considerably in places such as Asia and Europe. Because of their height skyscrapers have a strong symbolic value and can help a city attract interest. In Sweden the number of skyscraper projects have also seen a significant increase, though relatively few of them have eventually been built. One of the most spectacular examples were the two Tellus Towers that were planned in southern Stockholm. The highest tower would have been the highest residential building in all of Scandinavia. The project was canceled by the municipality because of its visual impact over areas considered to be of national interest as well as concern over shadows. Instead a new project was suggested consisting of seven smaller high rise buildings. The aim of this thesis is to examine whether groups of smaller high rise buildings have benefits over major skyscrapers regarding visual impact and shadows, by comparing the Tellus Towers to the new project. The program ArcGIS Pro has been used to create 3D models of both projects, whereby analysis tools have been used to analyze their effects on the surrounding built area which was downloaded as 3D models from Stockholm municipality's data portal as well as OpenStreetMap based 3D models from Esri. The results reveal that the new project will cast significantly more shadows than its predecessor would have done, while having a smaller visual impact.

Indiana University-Purdue University Indianapolis (IUPUI) / Image is a dominant medium among video, 3D model, and other media for visualizing environment and creating virtual access on the Internet. The location of image capture is, however, subjective and has relied on the esthetic sense of photographers up until this point. In this paper, we will not only visualize areas with images, but also propose a general framework to determine where the most distinct viewpoints should be located. Starting from elevation data, we present spatial and content information in ground-based images such that (1) a given number of images can have maximum coverage on informative scenes; (2) a set of key views can be selected with certain continuity for representing the most distinct views. According to the scene visibility, continuity, and data redundancy, we evaluate viewpoints numerically with an object-emitting illumination model. Our key view exploration may eventually reduce the visual data to transmit, facilitate image acquisition, indexing and interaction, and enhance perception of spaces. Real sample images are captured based on planned positions to form a visual network to index the area.

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The Generic Planning Tool (GPT) is a new software package being developed by the Flight Dynamics team at DLR. In an era where laser communications are becoming more and more relevant to data transmission for space missions, the GPT’s purpose is to compute highly accurate visibility windows and provide a wide variety of support information for both satellite-to-ground and inter-satellite links. What sets the GPT apart from previous products, is its shift from mission-specific to multi-mission and being able to accept various orbit and attitude data formats, thus enabling the support of multiple missions from DLR and external clients with flight dynamics information for mission planning applications. Its two main components are the core libraries written in Fortran, which serve as the powerhouse for the orbital mechanic’s computations, and the microservice architecture, enabled by JSON input/output files and Python scripts, which implement an automatic request-response service accessible over the network. This thesis will present why, how, and which GPT software functionalities were developed and tested during the internship at the German Space Operation Center. / Det generiska planeringsverktyget, Generic planning tool (GPT), är ett nytt mjukvarupaket som utvecklas av den flygdynamiska avdelningen på DLR. I en tid när kommunikation med hjälp av laser blir alltmer relevant vid dataöverföringar för rymduppdrag, är syftet med GPT att beräkna mycket exakta öppningar för dataöverföringar, men också att bidra med en mängd olika sorters användbar information för både ”satellit-till-mark”- och ”satellit-tillsatellit”-länkar. Det som skiljer verktyget från tidigare produkter är dess omvandling från att vara uppdragsspecifik till att kunna hantera multipla uppdrag. I och med GPT:s förmåga att acceptera olika dataformat gällande omloppsbana och orientering, öppnar det upp för att kunna stödja multipla uppdrag från DLR och externa klienter med flygdynamisk information, för applikationer inom uppdragsplanering. GPT:s två huvudsakliga delar är, de centrala biblioteken skrivna i Fortran vilka verkar som ett kraftverk för de orbital-mekaniska beräkningarna, och mikroservice-arkitekturen skapad från JSON input/output-filer och Pythonskript, vilket implementerar en automatisk begär- och svarstjänst tillgänglig via nätverket. Detta examensarbete kommer presentera varför, hur och vilka av GPT:s mjukvarufunktioner som utvecklades och testades under praktikplatsen på German Space Operations Center (GSOC).