Produced by the Johnson City GIS Division on July 25, 1997, this map denotes the streets of Johnson City. The legend includes fire stations, neighborhoods, and schools. A city street index is also included. The map was designed by Gregory Plumb, GIS Coordinator and Ann Howland, GIS Database Manager. Physical copy resides with Johnson City, Geographic Information Systems Division. Scale - 1:24,000 1" = .4 mile / https://dc.etsu.edu/rare-maps/1063/thumbnail.jpg

Produced by the Johnson City GIS Division on April 23, 1998, this map denotes the streets of Johnson City. The legend includes fire stations, neighborhoods, and schools. A city street index is also included. The map was designed by Gregory Plumb, GIS Coordinator and Ann Howland, GIS Database Specialist. Physical copy resides with Johnson City, Geographic Information Systems Division. Scale - 1:24,000 - 1" = .4 mile / https://dc.etsu.edu/rare-maps/1064/thumbnail.jpg

Produced by the Johnson City GIS Division on December 17, 2014, this map denotes the streets of Johnson City. The legend includes fire stations, hospitals, city parks, and schools. A city street index is also included along the left side edge. Physical copy resides with Johnson City, Geographic Information Systems Division. Scale - 1" = 2000' / https://dc.etsu.edu/rare-maps/1065/thumbnail.jpg

This master’s thesis describes a sensorial subsystem of a mobile robot. The thesis mentions the structure and a basis of the satellite navigation. There are also described each systems and visualization techniques as e. g. WGS 84, including also other systems for specification of more accurate position on the Earth (EGNOS, WAAS and others). This thesis describes closely also a differential GPS and the corrections. For the purposes of the thesis there has been assembled GPS software for a fundamental and a remote station. There have been chosen and used modules for receiving a GPS signal and wireless modules for their communication. There are also used outcomes from the project of the Open Street Map in the thesis. Results of this project are described in details, decoded, adjusted and converted into RNDF file. At the end of this thesis there has been composed a function of the program for portable camera which works on principle time of flight. This portable camera is dedicated to look for immediate barrier and also for 3D space view in front of the robot. This thesis also including the process how the power source has been built up for this portable scanner.

Produced by the Johnson City GIS Division on September 9, 2003, this map denotes the streets of Johnson City. The legend includes fire stations, neighborhoods, and schools. A city street index is also included. The map was designed by Gregory Plumb, GIS Coordinator and Ann Howland, GIS Database Specialist. This map was donated by the Johnson City GIS Division and now resides in the map collection of Sherrod Library's Government Information, Law and Maps Department. Physical copy resides in the Government Information, Law and Maps Department of East Tennessee State University’s Sherrod Library. / https://dc.etsu.edu/rare-maps/1012/thumbnail.jpg

隨著GIS的發展，地圖定位成為空間查詢中極為普遍的行為。一般地圖定位大多透過地址來進行，但是在缺乏地址的情況之下，進行地圖上之定位變成極為困難之事。 本論文嘗試對手繪地圖在真實地圖上進行定位，我們提出了一套機制，使用者可以隨意地以手繪方式繪製街道圖與地標，透過我們提出的方法，即可自動地在真實的地圖上進行定位。 論文中，我們使用相鄰街廓中之地標配置與相鄰之交叉路口之地標配置等變數組成的表示法來描述地圖。我們將手繪地圖與真實地圖轉換成這些表示法，並透過字串編輯距離、圖同構等關係來比較手繪地圖與真實地圖之相似度，從而對手繪地圖進行定位。 實作中，我們挑選了幾處真實場景在台北市地圖中進行比對並觀察其結果。系統採用之地標包括政府機構(如派出所、消防隊、區公所等)、學校、醫院等資料。在實驗中，應用這套表示法可成功的定位出使用者所輸入之各場景所在位置。另外，透過控制相似度門檻值，我們可以調整辨識之精確度，不至於錯失可能之定位結果。 / As the widely spread of the GIS applications, map localization becomes one of the most important features in the spatial information retrieval. Normally, map localization is done through street addresses. Without this information, map localization becomes very difficult. In this research, we are trying to do map localization using hand drawing maps. We proposed a mechanism that can localize the user's drawing map in the reference map automatically. Our approaches use the landmark configurations of the adjacent street blocks as well as the landmark configurations of the adjacent street intersections as the descriptors in representing a map. The user's hand drawn maps and the reference maps are converted into these representations. The string editing distances and graph isomorphism are used in determining the similarities between the hand drawn map and the reference map. The map localization can be done by comparing these similarities. We used various real scenes in Taipei City to verify our systems. The landmarks we used including police offices, fire stations, county offices, schools and hospitals, etc. The experimental results shown that our system can localize the user's input successfully. Moreover, by controlling thresholds in similarity analysis, we can adjust the system's accuracy that reduces possibility of miss localizations.

In this work we present algorithms that are capable of calculating paths to destination for electric vehicles. These paths can be based on the simple metrics such as the distance, time or the paths can be based on more advanced metric such as the minimum energy demanding metric. This metric is parameterizable by the physical construction of the electrical vehicle. We also propose a new algorithm that computes energy optimal paths that are more acceptable by the driver, because it also takes into consideration the time metric while computing the path.

<div>This dissertation addresses the problem of how to design a convolutional neural network (CNN) for giving semantic labels to the points on the ground given the satellite image coverage over the area and, for the ground truth, given the noisy labels in OpenStreetMap (OSM). This problem is made challenging by the fact that -- (1) Most of the images are likely to have been recorded from off-nadir viewpoints for the area of interest on the ground; (2) The user-supplied labels in OSM are frequently inaccurate and, not uncommonly, entirely missing; and (3) The size of the area covered on the ground must be large enough to possess any engineering utility. As this dissertation demonstrates, solving this problem requires that we first construct a DSM (Digital Surface Model) from a stereo fusion of the available images, and subsequently use the DSM to map the individual pixels in the satellite images to points on the ground. That creates an association between the pixels in the images and the noisy labels in OSM. The CNN-based solution we present yields a 4-8% improvement in the per-class segmentation IoU (Intersection over Union) scores compared to the traditional approaches that use the views independently of one another. The system we present is end-to-end automated, which facilitates comparing the classifiers trained directly on true orthophotos vis-`a-vis first training them on the off-nadir images and subsequently translating the predicted labels to geographical coordinates. This work also presents, for arguably the first time, an in-depth discussion of large-area image alignment and DSM construction using tens of true multi-date and multi-view WorldView-3 satellite images on a distributed OpenStack cloud computing platform.</div>

[ES] En la actualidad, uno de los principales desafíos a los que se enfrentan las grandes áreas metropolitanas es la congestión provocada por el tráfico, la cual se ha convertido en un problema importante al que se enfrentan las autoridades de cada ciudad. Para abordar este problema es necesario implementar una solución eficiente para controlar el tráfico que genere beneficios para los ciudadanos, como reducir los tiempos de viaje de los vehículos y, en consecuencia, el consumo de combustible, el ruido, y la contaminación ambiental. De hecho, al analizar adecuadamente la demanda de tráfico, es posible predecir las condiciones futuras del tráfico, y utilizar esa información para la optimización de las rutas tomadas por los vehículos. Este enfoque puede ser especialmente efectivo si se aplica en el contexto de los vehículos autónomos, que tienen un comportamiento más predecible, lo cual permite a los administradores de la ciudad mitigar los efectos de la congestión, como es la contaminación, al mejorar el flujo de tráfico de manera totalmente centralizada. La validación de este enfoque generalmente requiere el uso de simulaciones que deberían ser lo más realistas posible. Sin embargo, lograr altos grados de realismo puede ser complejo cuando los patrones de tráfico reales, definidos a través de una matriz de Origen/Destino (O-D) para los vehículos en una ciudad, son desconocidos, como ocurre la mayoría de las veces. Por lo tanto, la primera contribución de esta tesis es desarrollar una heurística iterativa para mejorar el modelado de la congestión de tráfico; a partir de las mediciones de bucle de inducción reales hechas por el Ayuntamiento de Valencia (España), pudimos generar una matriz O-D para la simulación de tráfico que se asemeja a la distribución de tráfico real. Si fuera posible caracterizar el estado del tráfico prediciendo las condiciones futuras del tráfico para optimizar la ruta de los vehículos automatizados, y si se pudieran tomar estas medidas para mitigar de manera preventiva los efectos de la congestión con sus problemas relacionados, se podría mejorar el flujo de tráfico en general. Por lo tanto, la segunda contribución de esta tesis es desarrollar una Ecuación de Predicción de Tráfico para caracterizar el comportamiento en las diferentes calles de la ciudad en términos de tiempo de viaje con respecto al volumen de tráfico, y aplicar una regresión logística a esos datos para predecir las condiciones futuras del tráfico. La tercera y última contribución de esta tesis apunta directamente al nuevo paradigma de gestión de tráfico previsto, tratándose de un servidor de rutas capaz de manejar todo el tráfico en una ciudad, y equilibrar los flujos de tráfico teniendo en cuenta las condiciones de congestión del tráfico presentes y futuras. Por lo tanto, realizamos un estudio de simulación con datos reales de congestión de tráfico en la ciudad de Valencia (España), para demostrar cómo se puede mejorar el flujo de tráfico en un día típico mediante la solución propuesta. Los resultados experimentales muestran que nuestra solución, combinada con una actualización frecuente de las condiciones del tráfico en el servidor de rutas, es capaz de lograr mejoras sustanciales en términos de velocidad promedio y tiempo de trayecto, ambos indicadores de un menor grado de congestión y de una mejor fluidez del tráfico. / [CA] En l'actualitat, un dels principals desafiaments als quals s'enfronten les grans àrees metropolitanes és la congestió provocada pel trànsit, que s'ha convertit en un problema important al qual s'enfronten les autoritats de cada ciutat. Per a abordar aquest problema és necessari implementar una solució eficient per a controlar el trànsit que genere beneficis per als ciutadans, com reduir els temps de viatge dels vehicles i, en conseqüència, el consum de combustible, el soroll, i la contaminació ambiental. De fet, en analitzar adequadament la demanda de trànsit, és possible predir les condicions futures del trànsit, i utilitzar aqueixa informació per a l'optimització de les rutes preses pels vehicles. Aquest enfocament pot ser especialment efectiu si s'aplica en el context dels vehicles autònoms, que tenen un comportament més predictible, i això permet als administradors de la ciutat mitigar els efectes de la congestió, com és la contaminació, en millorar el flux de trànsit de manera totalment centralitzada. La validació d'aquest enfocament generalment requereix l'ús de simulacions que haurien de ser el més realistes possible. No obstant això, aconseguir alts graus de realisme pot ser complex quan els patrons de trànsit reals, definits a través d'una matriu d'Origen/Destinació (O-D) per als vehicles en una ciutat, són desconeguts, com ocorre la majoria de les vegades. Per tant, la primera contribució d'aquesta tesi és desenvolupar una heurística iterativa per a millorar el modelatge de la congestió de trànsit; a partir dels mesuraments de bucle d'inducció reals fetes per l'Ajuntament de València (Espanya), vam poder generar una matriu O-D per a la simulació de trànsit que s'assembla a la distribució de trànsit real. Si fóra possible caracteritzar l'estat del trànsit predient les condicions futures del trànsit per a optimitzar la ruta dels vehicles automatitzats, i si es pogueren prendre aquestes mesures per a mitigar de manera preventiva els efectes de la congestió amb els seus problemes relacionats, es podria millorar el flux de trànsit en general. Per tant, la segona contribució d'aquesta tesi és desenvolupar una Equació de Predicció de Trànsit per a caracteritzar el comportament en els diferents carrers de la ciutat en termes de temps de viatge respecte al volum de trànsit, i aplicar una regressió logística a aqueixes dades per a predir les condicions futures del trànsit. La tercera i última contribució d'aquesta tesi apunta directament al nou paradigma de gestió de trànsit previst. Es tracta d'un servidor de rutes capaç de manejar tot el trànsit en una ciutat, i equilibrar els fluxos de trànsit tenint en compte les condicions de congestió del trànsit presents i futures. Per tant, realitzem un estudi de simulació amb dades reals de congestió de trànsit a la ciutat de València (Espanya), per a demostrar com es pot millorar el flux de trànsit en un dia típic mitjançant la solució proposada. Els resultats experimentals mostren que la nostra solució, combinada amb una actualització freqüent de les condicions del trànsit en el servidor de rutes, és capaç d'aconseguir millores substancials en termes de velocitat faig una mitjana i de temps de trajecte, tots dos indicadors d'un grau menor de congestió i d'una fluïdesa millor del trànsit. / [EN] Currently, one of the main challenges that large metropolitan areas have to face is traffic congestion, which has become an important problem faced by city authorities. To address this problem, it becomes necessary to implement an efficient solution to control traffic that generates benefits for citizens, such as reducing vehicle journey times and, consequently, use of fuel, noise and environmental pollution. In fact, by properly analyzing traffic demand, it becomes possible to predict future traffic conditions, and to use that information for the optimization of the routes taken by vehicles. Such an approach becomes especially effective if applied in the context of autonomous vehicles, which have a more predictable behavior, thus enabling city management entities to mitigate the effects of traffic congestion and pollution by improving the traffic flow in a city in a fully centralized manner. Validating this approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, are unknown, as occurs most of the times. Thus, the first contribution of this thesis is to develop an iterative heuristic for improving traffic congestion modeling; starting from real induction loop measurements made available by the City Hall of Valencia, Spain, we were able to generate an O-D matrix for traffic simulation that resembles the real traffic distribution. If it were possible to characterize the state of traffic by predicting future traffic conditions for optimizing the route of automated vehicles, and if these measures could be taken to preventively mitigate the effects of congestion with its related problems, the overall traffic flow could be improved. Thereby, the second contribution of this thesis was to develop a Traffic Prediction Equation to characterize the different streets of a city in terms of travel time with respect to the vehicle load, and applying logistic regression to those data to predict future traffic conditions. The third and last contribution of this thesis towards our envisioned traffic management paradigm was a route server capable of handling all the traffic in a city, and balancing traffic flows by accounting for present and future traffic congestion conditions. Thus, we perform a simulation study using real data of traffic congestion in the city of Valencia, Spain, to demonstrate how the traffic flow in a typical day can be improved using our proposed solution. Experimental results show that our proposed solution, combined with frequent updating of traffic conditions on the route server, is able to achieve substantial improvements in terms of average travel speeds and travel times, both indicators of lower degrees of congestion and improved traffic fluidity. / Finally, I want to thank the Ecuatorian Republic through the "Secretaría de Educación Superior, Ciencia, Tecnología e Innovación" (SENESCYT), for granting me the scholarship to finance my studies. / Zambrano Martínez, JL. (2019). Efficient Traffic Management in Urban Environments [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/129865