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How can linking data make the mountain experience more interesting, healthier, environmentally friendly and safer? Together with partners, we asked for concrete ideas and examples of use in an open innovation ideas competition. Now the best idea has been awarded a prize: The winner is 22-year-old student Hannah Aster from Salzburg with her idea “Fast on the mountain without a car”. Through a smart linking of different alpine real-time data sources, exciting and practical services can be created – of course taking data protection into account. Both guests and locals who want to use the mountain for recreation and sporting activities, as well as companies and organisations in the fields of tourism, sport and safety can benefit. But what could such services look like? That’s what we asked the committed community in an open innovation ideas competition: “31 innovative ideas were submitted and evaluated by a jury consisting of experts from the fields of data […]

[…] information services, including Salzburg Verkehr, wegfinder and the international parking data service Parkopedia, will adopt the Salzburg parking data to inform tourists about any congestion situations. The Park&Ride facilities Salzburg Messe and Salzburg Süd will also be integrated into the data service with real-time information. This is intended to achieve a steering effect in congestion situations. Impact monitoring of steering measures Um die Wirkungen von verkehrssteuernden Maßnahmen zu umfassen, wird im Pilotversuch auch ein umfangreiches Wirkungsmonitoring durchgeführt. Auf Basis der über EVIS.AT berechneten Echtzeit-Verkehrslage werden den gesamten Sommer hindurch Staulängen bzw. Verlustzeiten im gesamten Straßennetz in der Stadt Salzburg erfasst. Darüber hinaus erfolgt eine Erfassung von Verkehrsstärken mit straßenseitigen Detektoren bzw. eine vollständige Erfassung der Auslastungen der Parkeinrichtungen. About the DOMINO research project Offering simple, convenient and networked mobility services for all users – that is the vision of DOMINO, the “hub for intermodal mobility services and technologies”. The main goal of the DOMINO […]

GAMES will focus on how digitalisation could enable electric shared vehicle fleets to answer mobility needs while also creating new revenue streams by providing flexibility services for the electricity grid and energy communities.

Salzburg Research is regularly commissioned to analyse real travel time losses in local public transport. With an objective detailed evaluation as a data basis, transport planners can optimise the route network plan.

[…] The conceptual cornerstones of the i-Twin solution are: Semantic Integration Patterns based on relevant standards for the semantic description of asset information (e.g. RAMI4.0/AAS, OPC UA Companion Specifications) as well as recommendations for industrially used protocols and domain standards. Semantic Integration Patterns for minimally invasive integration of manufacturing applications. Semantic Integration Patterns for analytics systems based on available standards for the exchange of machine learning and AI models. A messaging system for semantically annotated data streams. A security and identity management service to protect data processed in the integration platform’s middleware. The project consortium, led by a research group specialized in semantic data integration, combines the research interests of three system providers (CMMS, OT software platform, edge nodes) and an industrial company (discrete manufacturing) with the expertise of the participating research partners (Data Science, Motion Data Intelligence). i-Twin is funded by BMK (Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation, and Technology) […]

Die Bereitstellung einer gut instandgehaltenen Fahrradinfrastruktur wirkt sich positiv auf den Fahrkomfort sowie die Sicherheit im Straßenverkehr aus und schafft die Voraussetzung, dass dieses als Alternative zum motorisierten Individualverkehr oder zum öffentlichen Verkehr angenommen wird. In dieser Studie wird mit Daten aus Smartphone-Beschleunigungssensoren und mithilfe eines k-means++-Algorithmus ein Clusterverfahren angewandt, um die Qualität von Fahrbahnabschnitten festzustellen. Dieses ist einfach und kostengünstig auf großflächige Radinfrastrukturen anwendbar und zeigt in einer Fallstudie für die Stadt Salzburg, dass schlecht befahrbare Fahrbahnabschnitte gut lokalisiert und infolge gezielt instandgehalten werden können.

Trotz der wachsenden Bedeutung des Radverkehrs in städtischen Mobilitätssystemen und einem zum Teil bedeutenden Anteil am Gesamtverkehrsaufkommen, sind zahlreiche Aspekte der Fahrradmobilität nach wie vor unbekannt. Konzepte und Methoden der Geoinformatik halten Möglichkeiten zur ganzheitlichen Untersuchung der Fahrradmobilität bereit. Die Idee eines Geographischen Informationsobservatoriums (GIO) birgt das Potenzial für ein besseres systemisches Verständnis der Fahrradmobilität und daraus abgeleitete, neue Erkenntnisse. Im Projekt Bicycle Observatory – Am Puls des Radverkehrs wird unter anderem erforscht, inwieweit eine räumlich differenzierte, kontinuierliche Beobachtung der Fahrradmobilität umsetzbar ist und welcher Informationsgewinn daraus erwartet werden kann.

Aggregation of sparse probe vehicle data (PVD) is a crucial issue in travel time reliability (TTR) analysis. This study, therefore, examines the effect of temporal and spatial aggregation of sparse PVD on the results of a linear regression analysis where two different measures of TTR are analyzed as the dependent variable. Our results show that by aggregating the data to longer time intervals and coarser spatial units the linear model can explain a higher proportion of the variance in TTR. Furthermore, we find that the effects of road design characteristics in particular depend on the variable used to represent TTR. We conclude that the temporal and spatial aggregation of sparse PVD affects the results of linear regression explaining TTR.

Cooperative Intelligent Transport Systems (C-ITS) technologies will play a significant role in the communication of automated vehicles. So far, vulnerable road users such as cyclists or pedestrians are often excluded from the communication and therefore are not able to actively create awareness for themselves. The Austrian research project Bike2CAV aims at improving bicyclists’ safety via Cooperative Intelligent Transport Systems (CITS) technologies. The work introduces the implemented prototype of a CITS-enabled helmet consisting of a GNSS (Global Navigation Satellite System) device (XSens MTi 680G) to determine the current location and two additional IMUs (MetamotionR by Mbientlab) mounted on the left and right hand to recognize turn intentions indicated by hand signals. The overall goal is to evaluate the C-ITS-prototype in real-world situations, especially whether localization accuracies (0.1 m accuracy at 95% confidence) can be achieved. For the LBS 2021 conference, first results will be available.

This study investigates the perceived safety of passengers while being on board of a driverless shuttle without a steward present. The aim of the study is to draw conclusions on factors that influence and contribute to perceived safety of passengers in driverless shuttles. For this, four different test rides were conducted, representing aspects that might challenge passengers’ perceived safety once driverless shuttles become part of public transport: passengers had to ride the shuttle on their own (without a steward present), had to interact with another passenger, and had to react to two different unexpected technical difficulties. Passengers were then asked what had influenced their perceived safety and what would contribute to it. Results show that perceived safety of passengers was high across all different test rides. The most important factors influencing the perceived safety of passengers were the shuttle’s driving style and passengers’ trust in the technology. The driving style was increasingly less important as […]

As part of the EMotion project, a top-class consortium with Salzburg Research, KTM and other partners is developing a cost-effective, energy-efficient and comfortable electric two-wheeler. A prototype is in the works, and the results of an international study on needs and acceptance are available. Although the Corona Crisis reduced mobility and thus also the emission of climate-damaging CO2 worldwide by about seven percent, a sharp increase in emissions can probably be expected again soon. By 2030, however, one to two billion tonnes of CO2 should be saved worldwide every year in order to achieve the Paris climate goals and slow down climate change. The transport sector has a not insignificant contribution to make here – and part of a solution can and will be electric mobility. Innovative e-two-wheeler as a green mobility alternative The Austrian lighthouse project „EMotion – Electric Mobility in L-Category Vehicles for all Generations” aims to design an innovative and user-friendly mobility […]

In recent years, trials of autonomous shuttle vehicles have been conducted worldwide. Currently, there exists no generalized process model for deployment and continuous operation of shuttles. Shuttle suppliers use their own developed procedures, making it difficult for the relevant stakeholders (e.g., public authorities) to assess the risk of potential shuttle deployment. The Digibus® Austria flagship project, among other goals, develops an approach for the virtual risk assessment of identified critical spots along proposed shuttle paths. Embedded into the deployment process, this serves as a significant body of evidence for safety assurance in shuttle deployment. Conducted simulation studies optimizing the shuttle’s trajectory for concrete maneuvers, along with derived requirements for the associated virtual environment, are part of the first noteworthy outcomes. Concretely, the developed virtual environment is integrated in the framework used for virtual validation. The framework is then used for a detailed evaluation of a right-turn maneuver, analyzing possible shuttle trajectories. Considerable differences in sensor […]

Automated driving systems are in need of accurate localization, i.e., achieving accuracies below 0.1 m at confidence levels above 95%. Although during the last decade numerous localization techniques have been proposed, a common methodology to validate their accuracies in relation to a ground-truth dataset is missing so far. This work aims at closing this gap by evaluating four different methods for validating localization accuracies of a vehicle’s position trajectory to different ground truths: (1) a static driving-path, (2) the lane-centerline of a high-definition (HD) map with validated accuracy, (3) localized vehicle body overlaps of the lane-boundaries of a HD map, and (4) longitudinal accuracy at stop points. The methods are evaluated using two localization test datasets, one acquired by an automated vehicle following a static driving path, being additionally equipped with roof-mounted localization systems, and a second dataset acquired from manually-driven connected vehicles. Results show the broad applicability of the approach for evaluating localization accuracy […]

IoT Lifecycle Management is a part of the Trustworthy IoT for CPS (IoT4CPS) project and explores the current state of technology progress for data acquisition and management along the entire IoT- and CPS-based product lifecycle in the Connected and Automated Mobility (CAM) sector. We report on the definition of extended data models and data analysis methods and the design of tools that follow recent initiatives, standards and recommendations in this sector. The work also provides the implementation of a Digital Twin prototype that is designed to identify security and safety measures of CAM applications and correlate these measures with multi-tenancy features of smart vehicles along the product lifecycle. Apart from the security and safety features, the report explores privacy, trust and ethics of CAM applications, within complex environments of smart cities and smart factories.

In the context of intelligent transport systems, dynamic route planning is an eagerly researched topic. While the research community during the last decade has focused on performance and scalability of dynamic route planning algorithms, the question concerning route qualities has been widely neglected. The current work contributes to this question by proposing a methodology to assess the quality of arbitrary routes based on seven spatio‐temporal route quality metrics (five spatial and two temporal ones). The methodology is evaluated by calculating quality metrics for 45 routes being derived from three dynamic route planning systems for three selected origin–destination pairs during one day. For objectively assessing route qualities, the approach matches the route planning results to a reference digital road network and uses reference travel times for calculating quality metrics. A spatio‐temporal cross‐evaluation illustrates different quality aspects in the context of both quality dimensions and demonstrates the usefulness of the proposed approach.

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Autonomous shuttle trials are carried out all over the world. So far, these trials are predominately based on trial and error approaches. During the last years, shuttle suppliers have developed their proprietary deployment and operation processes, whereas a more generalized process model is missing so far. In the Digibus® Austria flagship project, a consortium of 13 partners joined forces to develop methods and technologies for deploying and operating autonomous shuttles in public transport. Among other goals, the project aims at the definition of a generalized process model for autonomous shuttle trials, building on existing models as well as individual learnings. The proposed model consists of actors, components, decisions and activities and has been tested in the context of several shuttle trials in Austria. Although the process model so far only reflects the state in Austria, most activities should be applicable to other countries as well. The model is considered as a first step towards future […]

Online event on the necessary framework conditions and steps for the use of automated vehicles.

With the help of neural networks, the research team at Salzburg Research was able to predict the latency in communication networks with a mean error of 1.95%.