Anita Graser

AIT Austrian Institute of Technology | ait · Center for Mobility Systems

Processing is an object-oriented Python framework for the popular open source Geographic Information System QGIS, which provides a seamless integration of geoprocessing tools from a variety of different software libraries. In this paper, we present the development history, software architecture and features of the Processing framework, which make i...

The movement and transport of people and goods is spatial by its very nature. Thus, geospatial fundamentals of transport systems need to be adequately considered in transport models. Until recently, this was not always the case. Instead, transport research and geography evolved widely independently in domain silos. However, driven by recent concept...

Movement data analysis is a high-interest topic in many scientific domains. Even though Python is the scripting language of choice in the GIS world, currently there is no Python library that would enable researchers and practitioners to interact with and analyse movement data efficiently. To close this gap, we present MovingPandas, a new Python lib...

Effectively communicating uncertainties inherent to statistical models is a challenging yet crucial aspect of the modeling process. This is particularly important in applied research, where output is used and interpreted by scientists and decision makers alike. In disaster risk reduction, susceptibility maps for natural hazards are vital for spatia...

Trajectory data combines the complexities of time series, spatial data, and (sometimes irrational) movement behavior. As data availability and computing power have increased, so has the popularity of deep learning from trajectory data. This review paper provides the first comprehensive overview of deep learning approaches for trajectory data. We ha...

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated significant impact in various domains including traff...

In this paper, we present an architecture for mobility data spaces enabling trustworthy and reliable data operations along with its main constituent parts. The architecture makes use of a data lake for scalable storage of diverse mobility data sets, on top of which separate computing and storage layers are implemented to allow independent scaling w...

This paper presents our ongoing work towards XAI for Mobility Data Science applications, focusing on explainable models that can learn from dense trajectory data, such as GPS tracks of vehicles and vessels using temporal graph neural networks (GNNs) and counterfactuals. We review the existing GeoXAI studies, argue the need for comprehensible explan...

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated significant impact in various domains including traff...

Driven by foundation models, recent progress in AI and machine learning has reached unprecedented complexity. For instance, the GPT-3 language model consists of 175 billion parameters and a training-data size of 570 GB. While it has achieved remarkable performance in generating text that is difficult to distinguish from human-authored content, a si...

Driven by foundation models, recent progress in AI and machine learning has reached unprecedented complexity. For instance, the GPT-3 language model consists of 175 billion parameters and a training-data size of 570 GB. While it has achieved remarkable performance in generating text that is difficult to distinguish from human-authored content, a si...

Data-driven machine learning is playing a crucial role in the advancements of Industry 4.0, specifically in enhancing predictive maintenance and quality inspection. Federated learning (FL) enables multiple participants to develop a machine learning model without compromising the privacy and confidentiality of their data. In this paper, we evaluate...

Situational awareness is one of the most important factors for efficient and effective response in crisis and disaster situations. Up-to-date, valid and relevant data is one of the means to support crisis management actions, and the development and use of social media, as it is common nowadays, has become a very interesting research topic. In this...

Movement datasets are often complex and require sophisticated processing and analysis. A thorough understanding of the dataset is needed to choose the right methods and to interpret their results. Misunderstandings and violations of assumptions about dataset characteristics can lead to flawed analysis results and wrong conclusions. To address this...

Pressing issues related to the movement of people and goods can be tackled today thanks to improvements in tracking and communications technology that have made it possible to collect movement data on a big scale. Maritime data from the Automatic Identification System (AIS) is one of the fast growing sources of movement data. Existing approaches fo...

Exploratory analysis is an important tool to formulate hypotheses about data and build data-driven models. To efficiently explore massive movement datasets, researcher and analysts require appropriate exploratory analysis tools. However, there is a lack of appropriate tools for movement data exploration that can handle large data volumes. We theref...

Movement data exploration presents a significant challenge due to the heterogeneity of movement datasets and analysis tasks. Furthermore, there is a lack of established tools for the exploratory analysis of movement data, as well as a lack of literature on best practices for applying corresponding concepts using commonly available data analysis too...

Bike-sharing has developed into an established part of many urban transportation systems. However, new bike-sharing systems (BSS) are still built and existing ones are extended. Particularly for large BSS, location planning is complex since factors determining potential usage are manifold. We propose a semi-automatic approach for creating or extend...

In this paper we introduce and compare the results of two novel data-driven trajectory prediction approaches computing future locations of moving objects from massive historical movement data.

Pressing issues related to the movement of people and goods can be tackled today thanks to improvements in tracking and communications technology that have made it possible to collect movement data on a big scale. Maritime data from the Automatic Identification System (AIS) is one of the fast growing sources of movement data. Existing approaches fo...

Bike-sharing has developed into an established part of many urban transportation systems. However, new bike-sharing systems (BSS) are still built and existing ones are extended. Particularly for large BSS, location planningis complex since factors determining potential usage are manifold. We propose a semi-automatic approach forcreating or extendin...

Learn how to use QGIS 3 to take your cartographic products to the highest level. QGIS 3.4 opens up exciting new possibilities for creating beautiful and compelling maps! Building on the first edition, the authors take you step-by-step through the process of using the latest map design tools and techniques in QGIS 3. With numerous new map designs...

Objectives: Emergency medical services have been established in many countries all over the world. Good first care improves the outcome of patients in terms of hospital stay duration, chances of full recovery and of treatment costs. In this paper, we present an integrated approach combining spatial information and integer optimization for emergenc...

Origin–destination flow maps are a popular option to visualize connections between different spatial locations, where specific routes between the origin and destination are unknown or irrelevant. Visualizing origin–destination flows is challenging mainly due to visual clutter which appears quickly as data sets grow. Clutter reduction techniques are...

Even though we are currently witnessing an unprecedented growth in the collection of movement data, practitioners in many fields still struggle with gaining access to reusable mobility data, such as traffic flows and speeds. Data availability varies considerably between different cities and regions. While some publish comprehensive open datasets, o...

Space, and in particular public space for movement and leisure, is a valuable and scarce resource, especially in today’s growing urban centres. The distribution and absolute amount of urban space—especially the provision of sufficient pedestrian areas, such as sidewalks—is considered crucial for shaping living and mobility options as well as transp...

Map data for pedestrian routing and navigation provided by OpenStreetMap is getting more and more detailed, but current approaches often fail to take advantage of available information. This paper addresses the issue of integrating open spaces, such as squares and plazas, into pedestrian routing graphs to support realistic crossing behaviour. We ev...

This chapter presents study results on perceived dangers of urban cycling based on interviews with cyclists and polls conducted in the city of Vienna, Austria. The interviews and polls were conducted as part of the nationally funded projects COEXIST and Com-oVer in 2012 and 2013. The study analyzed all records of injury accidents from the national...

This paper describes a novel approach to improve prediction models which estimate vehicle speeds and their diurnal variation for road network links in urban street networks using only static map attributes. The presented approach takes into account previously neglected spatial information by integrating network centrality measures for closeness (in...

We present a sensitivity analysis for a mechanical model, which is used to estimate the energy demand of battery electric vehicles. This model is frequently used in literature, but its parameters are often chosen incautiously, which can lead to inaccurate energy demand estimates. We provide a novel prioritization of parameters and quantify their im...

Learn how to use QGIS to take your cartographic products to the highest level. With step-by-step instructions for creating the most modern print map designs seen in any instructional materials to-date, this book covers everything from basic styling and labeling to advanced techniques like illuminated contours and dynamic masking. See how QGIS is...

As a result of OpenStreetMap’s (OSM) openness and wide availability, there is increasing interest in using OSM street network data in routing applications. But due to the heterogeneous nature of Volunteered Geographic Information (VGI) in general and OSM in particular, there is no universally valid answer to questions about the quality of these dat...

The problem of map-matching sparse and noisy GPS trajectories to road networks has gained increasing importance in recent years. A common state-of-the-art solution to this problem relies on a Hidden Markov Model (HMM) to identify the most plausible road sequence for a given trajectory. While this approach has been shown to work well on sparse and n...

Recent years have witnessed a steep increase in the collection of movement data through GPS trajectories. Such data sets have great potential for providing insights into mobility demand and behaviour for city planners, or to improve routing services for the end user. We propose a method for inferring popularity from GPS trajectories. The inferred p...

Research on human perception and wayfinding strategies has provided valuable insights into how humans navigate in space. In particular, the state of the art suggests that pedestrians orient themselves to objects, also known as landmarks [1]-[3]. Still, today’s commonly available outdoor navigation tools such as Google Maps do not take advantage of...

Nowadays pedestrians are making increasing use of mobile navigation and way finding tools in a variety of contexts, such as the fastest route to work, selecting a more scenic route to a place of interest, or exploring unknown surroundings. Google Maps, the most used app in the world in 2013, is the most prominent example of a popular navigation too...

Navigation instructions in pre- and on-trip routing services are usually based on street names and types, distances, and turn directions. However, in digital street graphs it is common that street names for separately mapped pedestrian and cycle links are missing. This leads to unsatisfactory instructions containing “unknown road” records. Often, t...

Reliable energy estimation methods are a very important step to addressing the range anxiety problem of electric vehicle adoption. Besides driving patterns and vehicle parameters, geographic information about elevation changes is one of the most important pieces of information to predict energy consumption. This paper presents a method to assess th...

This work combines data from studies on threat perception by cyclists with data of actual traffic accidents involving cyclists: it presents survey results on perceived dangers of urban cycling based on interviews with cyclists and polls conducted in the city of Vienna (Austria) over the last two years. These results are contrasted with an analysis...

This article presents a novel open source toolbox for street network comparison based on the Sextante geoprocessing framework for the open source Geographic Information System Quantum GIS (QGIS). In the spirit of open science, the toolbox enables researchers worldwide to assess the quality of street networks such as OpenStreetMap (OSM) by calculati...

The use of Floating Car Data (FCD) systems for the generation of traffic information has been discussed in numerous publications, many of which are based on simulated data or on a small number of vehicles collecting data over a limited time span. We present FLEET, a real-world FCD system, which has been continuously operating since 2003, collecting...

We present an approach for evaluating traffic performance along corridors and its variation based on floating car data (FCD). In contrast to existing work, our approach can cope with long and irregular FCD reporting intervals. Resampling of sparse FCD in time and interpolation increases spatial resolution of FCD positions along the corridors. FCD p...