Under detta arbete testades och utvärderades navigeringsverktyg mot varandra för att sedan se om de, tillsammans med kartsystemet OpenStreetMap, kunde fungera som substitut till programmet Google Maps och användas för att navigera vid en rutt. Navigeringssystemen som jämfördes hade alla öppen källkod och det gick att sätta upp och köra lokalt på en personlig dator med hjälp av stickprovsdata för att navigera i olika delar av världen.

There are many map providers on the market today. Anyone who wishes to use a licensed map-service in an application has to pay a license fee. This fee can become a big expense and affect the price that the end costumer has to pay.This thesis has investigated in how to set up and improve an open source geocoding service for it to measure against a licensed map-service. Geocoding is the technique of having an input address and returning a position which consists of a latitude and a longitude coordinate. The investigation has been done by implementing an open source solution as a proof of concept with the goal to answer the question to which extent is it feasible to develop an open source geocoding service to be as fast accurate and complete as a licensed map service.The open source solution has been developed in collaboration with TaxiCaller Nordic AB. In the implementation the Pelias project has been used as a geocoder together with map data from the datasets of OpenStreetMap and Who’s On First and Elasticsearch as the search engine. The work is based on functional, data and performance requirements set by TaxiCaller.The evaluation has shown that most of the requirements set for this work are achieved with the implemented open source geocoding service solution. Examples of these requirements are correctness of the search results and that the address, street, venue or intersection in the search results should be fully specified.The functional requirement to convert an intersection to coordinates is not achieved when the intersection can not be uniquely identified. The performance requirement to search for a venue is not. Also, the data requirement that the postal code in the search results should be fully specified is not achieved.Sometimes but not always a licensed map-service can provide better data. / 目前市场上有许多地图提供商。任何希望在应用程序中使用许可地图服务的人都必须支付许可费。这笔费用可能会成为一笔巨大的费用，并影响最终客户必须支付的价格。 本文研究了如何建立和改进开源地理编码服务，以便对许可的地图服务进行测量。地理编码是具有输入地址并返回由纬度和经度坐标组成的位置的技术。调查是通过实施开源解决方案作为概念证明来完成的，其目的是回答开发开源地理编码服务的可行程度，以及与许可地图服务一样快速准确和完整的问题。 开源解决方案是与TaxiCaller Nordic AB合作开发的。在实现中，Pelias项目已被用作地理编码器以及来自OpenStreetMap和Who's On First以及Elasticsearch数据集的地图数据作为搜索引擎。这项工作基于TaxiCaller设定的功能，数据和性能要求。 评估表明，通过实施的开源地理编码服务解决方案，可以实现为此项工作设置的大部分要求。这些要求的示例是搜索结果的正确性，并且应完全指定搜索结果中的地址，街道，地点或交叉点。 当无法唯一地识别交叉点时，不能实现将交叉点转换为坐标的功能要求。搜索场地的性能要求不是。此外，未实现搜索结果中的邮政编码应完全指定的数据要求。 有时但并非总是获得许可的地图服务可以提供更好的数据。

Utbudet av bra, täckande vägkartor som innehåller information om vägarnas lutningar är idag begränsat. Att skapa sådana kartor är också dyrt, då det kräver både arbetskraft och dyr utrustning. Tack vare en ny algoritm är det dock nu möjligt att skatta lutningen på en väg endast genom användandet av en enkel GPS-enhet och redan existerande sensorer i tunga lastbilar. Genom att kombinera flera sådana mätningar för samma väg är det möjligt att få en bra skattning av vägens lutning. I detta arbete har ett system för att skapa vägkartor med lutning både implementerats och utvärderats. Resultaten visar att det är möjligt att skapa vägprofiler med lutningsinformation genom att använda redan tillgängliga sensorer. Resultaten är baserade på både simulerad data och ett begränsat antal verkliga experiment. / There is currently a limited supply of good road maps with good coverage that includes data about the slope of the roads.Creating such maps is also expensive, and requires both labor and expensive equipment. Thanks to a new algorithm however, it is possible to estimate the slope of a road by using only a simple GPS device and already existing sensors in a heavy duty vehicle. By combining several measures along the same road, it is possible to get a good estimate of the slope of the road. In this work, a system for creating road maps with integrated slope data from such estimations is both implemented and evaluated. The results show that it is indeed possible to create road profiles with slope data using only already available sensors. The results are based on both simulated data and a limited set of data collected from real world experiments.

Ces dernières années, de nouvelles méthodes de collecte de données géospatiales basées sur la contribution du public se sont développées. L’information géographique volontaire ou «Volunteered Geographic Information (VGI)» en anglais, renvoie à des contextes dans lesquels les citoyens génèrent volontairement du contenu géospatial et le partage avec le reste de la communauté. OpenStreetMap est l'un des projets VGI les plus réussis. Il vise à créer une carte du monde modifiable et gratuite. Les citoyens peuvent participer à ce projet en créant de nouvelles fonctionnalités, en modifiant celles existantes ou en ajoutant des valeurs d'attribut aux objets cartographiés. Les valeurs d'attribut sont stockées dans la base de données OSM sous forme de paires «clé = valeur». Il existe trois façons de participer à OSM: numériser des images aériennes, importer des coordonnées GPS ou importer un ensemble de données. Aucune expertise en géomatique ou SIG n'est requise pour participer au projet. De plus, il n'y a pas de règle prédéfinie pour le balisage et les participants OSM peuvent ajouter n'importe quelle clé ou valeur aux fonctionnalités. Par conséquent, il existe de réelles préoccupations concernant la qualité des données OSM. Cette recherche évalue la qualité de la base de données OSM sur la base des éléments de qualité mentionnés dans la norme ISO (ISO 19157: 2013). En raison de l'accès limité aux ensembles de données de référence, seules l'exhaustivité, la précision de la position, la précision des attributs et la précision de la forme géométrique sont évaluées dans cette recherche. Dans un premier temps, toutes les mesures proposées pour évaluer la qualité des données spatiales sont passées en revue. Ensuite, la qualité des bases de données des routes et des bâtiments OSM est évaluée à l'aide de ces mesures. Enfin, une analyse statistique est effectuée pour mesurer la corrélation entre les mesures de qualité et les indicateurs de qualité potentiels tels que la densité de la population, le niveau de revenu et la distance au centre de la ville. Ces indicateurs peuvent fournir un aperçu de la qualité des données OSM lorsqu'aucune donnée de référence n'est disponible / In the recent years, a new method of spatial data collection based on the public participation has emerged which is called Volunteered Geographic Information (VGI). In VGI projects, citizens voluntarily generate spatial content and share it with the rest of the community. OpenStreetMap is one of the most successful VGI projects that aims to create an editable, free map of the world. Citizens can participate in this project by creating new features, editing the existing ones or adding attribute values to the features. Attribute values are stored in OSM database as “key=value” pairs. There are three ways of participating in OSM: digitizing aerial images, importing GPS coordinates and importing a data set. No expertise in geomatics or GIS is required for participating in the project. Furthermore, there is no pre-defined rule for tagging and OSM participants can add any key or value to the features. Consequently, there are real concerns regarding the quality of OSM data. This research, propose to assesse the quality of OSM database based on the quality elements that are mentioned in ISO standard (ISO 19157:2013). Due to the limited access to reference data sets, only completeness, positional accuracy, attribute accuracy and shape accuracy are evaluated in this research. In the first step, all the measure that are proposed for assessing the quality of spatial data are reviewed. Then, the quality of OSM roads and buildings databases are assessed using these measures. Finally, the statistical analysis is done to measure the correlation between quality measures and potential quality indicators such as population density, income level and the distance to the center of the city. These indicators can provide an insight into the quality of OSM data where no reference data is available.

Navigation systems are one of the most commonly found electronic gadgets in modern vehicles nowadays. Alongside navigation units this technology is made readily available to individuals in everyday devices such as a mobile phone. Digital maps which come preloaded on these devices accommodate within them an extensive dataset of spatial information from around the globe which aids the driver in achieving a well guided driving experience. Apart from being essential for navigation this sensor information backs up other vehicular applications in making intelligent decisions. The quality of this information delivered is in direct relation to the underlying dataset used to produce these maps. Since we live in a highly dynamic environment with constantly changing geography, an effort is necessary to keep these maps updated with the most up to date information as frequently as possible. The digital map of interest in this study is OpenStreetMap, the underlying data of which is a combination of donated as well as crowdsourced information from the last 10 years. This extensive dataset helps in building of a detailed digital map of the world using well defined cartographic techniques. The information within OpenStreetMap is currently enhanced by a large group of volunteers who willing use donated satellite imagery, uploaded GPS tracks, field surveys etc. to correct and collect necessary data for a region of interest. Though this method helps in improving and increasing the quality and quantity of the OpenStreetMap dataset, it is very time consuming and requires a great deal of human effort. Through this thesis an effort is made to automatically enrich this dataset by preprocessing crowdsourced sensor data collected from the navigation system and driver assistance systems (Traffic Sign Recognition system and a Lane Detection System) of a driving vehicle. The kind of data that is algorithmically derived includes the calculation of the curvature of the underlying road, correction of speed limit values for individual road segments being driven and the identification of change in the geometry of existing roads due to closure of old ones or addition of new ones in the Nuremberg region of Bavaria, Germany. Except for a small percentage of speed limit information on roads segments, other information is currently not available in the OpenStreetMap database for use in safety and comfort related applications. The navigation system has the ability to deliver geographical data in form of GPS coordinates at a certain frequency. This set of GPS coordinates can grouped together to form a GPS track visualizing the actual path traversed by a driving vehicle. A large number of such GPS tracks repeatedly collected from different vehicles driving in a region of interest gives all GPS points which lie on a particular road. These points, after outlier elimination methods are used as a dataset to scientifically determine the underlying curvature of the road with the aid of curve fitting techniques. Additional information received from the lane detection system helps identify curves on a road for which the curvature must be calculated. The fusion of information from these sources helps to achieve curvature results with high accuracy. Traffic sign recognition system helps detect traffic signs while driving, the fusion of this data with geographical information from the navigation system at the instance of detection helps determine road segments for which the recognized speed limit values are valid. This thesis successfully demonstrates a method to automatically enrich OpenStreetMap data by crowdsourcing raw sensor data from multiple vehicles equipped with driver assistance systems. All OpenStreetMap attributes were 100% updated into the database and the results have proven the effectiveness our system architecture. The positive results obtained in combination with minimal errors promise a better future for assisted driving.

Depuis les années 2000, les technologies du Web permettent aux utilisateurs de prendre part à la production de données : les internautes du Web 2.0 sont les nouveaux capteurs de l’information. Du côté de l’Information Géographique affluent de nombreux jeux de données en provenance de plates-formes de cartographie participative telles qu’OpenStreetMap (OSM) qui a largement impulsé le phénomène de la Géographique Participative (VGI). La communauté OSM représente aujourd’hui plus de deux millions de contributeurs qui alimentent une base de données géospatiales ouverte dont l’objet est de capturer une représentation du territoire mondial. Les éléments cartographiques qui découlent de ce déluge de VGI sont caractérisés par des tags. Les tags permettent une catégorisation simple et rapide du contenu des plates-formes de crowdsourcing qui inondent la toile. Cette approche est cependant un obstacle majeur pour le partage et la réutilisation de ces grands volumes d’information. En effet, ces ensembles de tags, ou folksonomies, sont des modèles de données beaucoup moins expressifs que les ontologies. Nous proposons un méta-modèle pour rapprocher la folksonomie et l’ontologie OSM afin de mieux exploiter la sémantique des données qui en sont issues, tout en préservant la flexibilité intrinsèque à l’utilisation de tags. / Post-2000s web technologies have enabled users to engage in the information production process: Web 2.0 surfers are the new data sensors. Regarding Geographic Information (GI), large crowdsourced datasets emerge from the Volunteered Geographic Information (VGI) phenomenon through platforms such as OpenStreetMap (OSM). The latter involves more than two millions contributors who aim at mapping the world into an open geospatial database. This deluge of VGI consists of spatial features associated with tags describing their attributes which is typical of crowdsourced content categorization. However, this approach is also a major impediment to interoperability with other systems that could benefit from this huge amount of bottom-up data. Indeed, folksonomies are much less expressive data models than ontologies. We address the issue of loose OSM metadata by proposing a model for collaborative ontology engineering in order to semantically lift the data while preserving the flexible nature of the activity of tagging.

Im vorliegenden Vortrag wurde im Rahmen der Konferenz 'State of the Map Poland 2018' der aktuelle Ansatz zum Kartographieren von Innenraumumgebungen für OpenStreetMap (OSM), wie Gebäuden, vorgestellt und erläutert. Der Fokus des Vortrags lag dabei auf den von den Autoren entwickelten Indoor-Tools und Methodiken für OSM.

Transport models are key in predicting travel behaviour and planning transport systems. Transport models can be either aggregated or disaggregated. Disaggregation means that travel behaviour is represented on an individual level, which can be beneficial because it offers a higher detail level and reduces aggregation bias. Input data for transport models can be both expensive and inaccessible, especially comprehensive data. Thus, it is advantageous to explore the utilisation of open data, which is free and accessible. The objective of the thesis was to evaluate how OpenStreetMap and other Open Data can be utilised in disaggregated transport modelling. The scope of the study was Uppsala, Sweden. In the thesis, a disaggregate transport model was designed, which only considered commuting trips made by public transport. Destinations and a synthetic population were estimated based on OpenStreetMap map features, SCB census data, and LuTRANS land use data. A travel survey was utilised in model calibration, and UL boarding data was used for model validation. The results showed that OpenStreetMap provided sufficient data for estimating a synthetic population and destinations for a disaggregate transport model when combined with other open data sources. Population and land usecensus data were essential for calibrating the model. However, the model came with limitations caused by assumptions, generalisation, technical constraints, and the partial incompleteness of open data. The thesis concludes that Open Data, such as OpenStreetMap, can be utilised sufficiently for transport modelling, with proper assumptions and processing. The openness of the data also increases the replicability of such a model. / Transportmodeller är viktiga i att förutspå resvanemönster och för att kunna planera transportsystemet. Transportmodeller kan vara antingen aggregeradeeller disaggregerade. Disaggregering betyder att resvanor är representerade påindividuell nivå, vilket kan vara fördelaktigt då det innebär en högre detalj nivå och mindre partiskhet orsakad av aggregering (aggregation bias). Indata förtransportmodeller kan vara både dyrt och svåråtkomligt, speciellt för mer omfattande data. Därav kan det vara till stor nytta att utforska möjligheten att använda öppnadata (Open Data), som är gratis och lättåtkomligt. Syftet med examensarbetetvar att utvärdera hur OpenStreetMap och annan Open Data kan användas idisaggregerad transportmodellering. Den geografiska omfattningen av studien är Uppsala tätort. En disaggregerad transportmodell togs fram i examensarbetet, sombara tog hänsyn till jobbresor med kollektivtrafik. Destinationer och en syntetiskbefolkning uppskattades utifrån OpenStreetMap objekt, befolkningsdata från SCB, samt markanvändningsdata från LuTRANS. En resvaneundersökning utnyttjadesför modellkalibrering och påstigningsdata från UL användes för modellvalidering.Resultaten visade att OpenStreetMap erbjöd tillräckligt med data för att ta framoch uppskatta en syntetisk befolkning och destinationer för en disaggregeradtransportmodell, om den kombineras med andra öppna datakällor. Befolkning- ochmarkanvändningsdata var avgörande i att kalibrera modellen. Dock så innefattar modellen vissa begränsningar som är orsakada av antaganden, generalisering, tekniskabegränsningar, samt ofullständigheten av Open Data. Slutsatsen är att Open Data, så som OpenStreetMap, kan utnyttjas för transportmodellering, om det kombineras med välformulerade antaganden och processering av datan. Datans öppenheten medför även en ökad replikerbarhet för en sådan modell.

In der vorliegenden Publikation wird ein Verfahren beschrieben, dass eine infrastrukturlose Positionierung im Inneren von Gebäuden ermöglicht. Unter infrastrukturlos wird in diesem Zusammenhang die autarke Positionierung eines Systems auf Basis seiner Inertialsensorik ohne den Einsatz von im Gebäude installierter Zusatzlösungen, wie Funksysteme, verstanden. Aufgrund der insbesondere über die Zeit erhöhten Fehlerbehaftung solcher Sensoren werden bei diesem Verfahren Innenraumkarten in den Lokalisierungsprozess einbezogen. Diese Kartendaten erlauben den Ausschluss invalider Positionen und Bewegungen, wie das Durchqueren von Wänden, und ermöglichen somit eine wesentliche Verbesserung der Ortungsgenauigkeit.

Esta dissertação está inserida na área de configuração urbana, com foco em sistemas viários segregados por cidades. O objetivo desta pesquisa foi a exploração de dados viários urbanos disponíveis na Web e a extração de parâmetros com aplicabilidade em análises de morfologias de cidades. A intenção do trabalho foi corroborar a hipótese: A qualidade adquirida por dados de mapas colaborativos permite sua utilização em análises da morfologia urbana a nível local. Mapas colaborativos são plataformas online que agregam informações geográficas fornecidas pelos próprios usuários, de acordo com a experiência local. O Projeto OpenStreetMap foi utilizado como fonte de dados para avaliar o potencial e as limitações dos mapas colaborativos na representação das malhas viárias de municípios brasileiros. Os sistemas viários foram expressos em forma de grafos, em que as arestas representaram as ruas e os nós, as interseções entre ruas. Do ponto de vista da Engenharia de Transportes, o foco do uso da Teoria de Grafos em pesquisas de morfologias viárias está em questões como mensuração da acessibilidade, eficiência e resiliência da rede a falhas. As principais ferramentas computacionais utilizadas foram as bibliotecas OSMnx e Networkx, escritas em linguagem Python, com funções de construção e análises de redes. Para avaliar a viabilidade de utilização das ferramentas e da plataforma de dados propostos, foi realizada uma comparação com o estudo de Lima, Silva e van der Waerden (2003). Esse trabalho avaliou a compacidade e a acessibilidade global das malhas viárias de 11 cidades, com intuito de comparar exemplos brasileiros com estrangeiros. A reprodução do estudo de referência foi possível, com construção de redes com aumento médio de 47% de elementos, o que indicou expansão e maior detalhamento dos sistemas viários. Além disso, foi detectada uma diferença na comparação das cidades brasileiras com o panorama internacional. Marília e São Carlos apresentaram malhas mais próximas do padrão americano, junto com Piracicaba que já estava nesse grupo. Por outro lado, a malha viária de Presidente Prudente passou ao grupo de cidades mais próximas do padrão europeu. Em seguida, os materiais propostos neste trabalho foram utilizados para montar um banco de dados com mais de 300 cidades brasileiras de diferentes portes. Os parâmetros avaliados caracterizaram os municípios de acordo com a conectividade, acessibilidade e regularidade da malha viária. A grande variação destes aspectos ressaltou a diferença nas configurações ocasionadas pelos fatores influentes na formação de malhas viárias: processo histórico-social de crescimento urbano, limites geográficos e diferentes políticas de expansão. / This dissertation is inserted in the area of urban configuration, focusing on road systems segregated by cities. The objective of this research was the exploration of urban road data available on the Web and the extraction of parameters with applicability in analyzes of city morphologies. The intention of the work was to corroborate the hypothesis: The quality acquired by collaborative maps data allows its use in analyzes of the urban morphology at the local level. Collaborative maps are online platforms that aggregate geographic information provided by the users themselves, according to local experience. The OpenStreetMap Project was used as a data source to evaluate the potential and limitations of collaborative maps in the representation of road networks in Brazilian municipalities. The road systems were expressed in graph form, in which the edges represented the streets and nodes, the intersections between streets. From the point of view of Transport Engineering, the focus of the use of Graph Theory in research on road morphologies is on issues such as accessibility, efficiency and network resilience to failure measurement. The main computational tools used were the OSMnx and Networkx libraries, written in Python language, with built-in functions and network analysis. To evaluate the feasibility of using the proposed tools and data platform, a comparison was made with the study by Lima, Silva and van der Waerden (2003). This work evaluated the compactness and global accessibility of the road networks of 11 cities, in order to compare Brazilian examples with foreigners. The reproduction of the reference study was possible, with construction of networks with an average increase of 47% of elements, which indicated expansion and greater detailing of the road systems. In addition, a difference was detected in the comparison of Brazilian cities with the international panorama. Marília and São Carlos presented meshes closer to the American standard, along with Piracicaba who was already in that group. On the other hand, the road network of Presidente Prudente passed to the group of cities closest to the European standard. Then, the materials proposed in this work were used to build a database with more than 300 Brazilian cities of different sizes. The evaluated parameters characterized the municipalities according to the connectivity, accessibility and regularity of the road network. The great variation of these aspects highlighted the difference in the configurations caused by influencing factors in the formation of road networks: historical-social process of urban growth, geographical limits and different expansion policies