Suche nach „[Pagany] [Raphaela]“ hat 58 Publikationen gefunden

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Beitrag (Sammelband oder Tagungsband)

C. Hoermann, Raphaela Pagany, K. Kirchner, Wolfgang Dorner, M. Heurich, I. Storch

Predicting the risk of deer-vehicle collisions by inferring rules learnt from deer experience and movement patterns in the vicinity of roads

[Accepted for publication]

Proceedings of the 2020 10th International Conference on Advanced Computer Information Technologies (ACIT) [September 6-8, 2020; Deggendorf]

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Beitrag (Sammelband oder Tagungsband)

Raphaela Pagany, Javier Valdés, Wolfgang Dorner

Risk prediction of wildlife-vehicle collisions comparing machine learning methods and data use

[Accepted for publication]

Proceedings of the 2020 10th International Conference on Advanced Computer Information Technologies (ACIT) [September 6-8, 2020; Deggendorf]

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Vortrag

C. Hoermann, Raphaela Pagany, K. Kirchner, Wolfgang Dorner, M. Heurich, I. Storch

Predicting the risk of deer-vehicle collisions by inferring rules learnt from deer experience and movement patterns in the vicinity of roads

2020 10th International Conference on Advanced Computer Information Technologies (ACIT), Deggendorf

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Vortrag

Raphaela Pagany, Javier Valdés, Wolfgang Dorner

Risk prediction of wildlife-vehicle collisions comparing machine learning methods and data use

2020 10th International Conference on Advanced Computer Information Technologies (ACIT), Deggendorf

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Zeitschriftenartikel

J. Trager, L. Kalová, Raphaela Pagany, Wolfgang Dorner

Warning apps for road safety – a technological and economical perspective for autonomous driving

[Article submitted]

International Journal of Human–Computer Interaction

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Zeitschriftenartikel

Raphaela Pagany

Wildlife-vehicle collisions—Influencing factors, data collection and research methods

[Article submitted]

Biological Conservation

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Vortrag

Raphaela Pagany

Spatiotemporal risk prediction of wildlife-vehicle collisions

IENE - Infrastructure and Ecology Network Europe, Évora, Portugal (conference postponed)

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Vortrag

Raphaela Pagany

Risk prediction on road—Exemplified for wildlife-vehicle collisions

ESAR - Expert Symposium on Accident Research, Hannover (conference postponed)

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Vortrag

C. Hoermann, Raphaela Pagany, F. Ossi, F. Cagnacci, Wolfgang Dorner, M. Heurich

L‘ecologia del movimento e gli investimenti stradali: Un‘analisi a larga scala sul capriolo europeo (Capreolus capreolus)

Workshop Wildunfälle in Südtirol - Incidenti stradali con la fauna selvatica in Alto Adige, Bozen, Italy

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Vortrag

Simon Graf, Raphaela Pagany, Wolfgang Dorner, A. Weigold

Georeferencing of Road Infrastructure from Photographs using Computer Vision and Deep Learning for Road Safety Applications

5th International Conference on Geographical Information Systems Theory, Applications and Management, Heraklion, Greece

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Vortrag

Raphaela Pagany, Alexander Faschingbauer, Simon Graf, Wolfgang Dorner

Geoanalyse mit Methoden der Künstlichen Intelligenz - Datenaufbereitung, Homogenisierung und Anwendung am Fallbeispiel der (Wild-)Unfallprognose

Posterpräsentation

Fachsymposium Mobilität der Zukunft, Deggendorf

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Vortrag

Raphaela Pagany, Alexander Faschingbauer, Simon Graf, Wolfgang Dorner

Geoanalyse mit Methoden der Künstlichen Intelligenz - Datenaufbereitung, Homogenisierung und Anwendung am Fallbeispiel der (Wild-)Unfallprognose

Posterpräsentation

AGIT Symposium & Expo 2019 - Angewandte Geoinformatik, Salzburg, Österreich

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Beitrag (Sammelband oder Tagungsband)

Simon Graf, Raphaela Pagany, Wolfgang Dorner, A. Weigold

Georeferencing of road infrastructure from photographs using computer vision and deep learning for road safety applications

Proceedings of the 5th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM) [May 3-5, 2019; Heraklion, Greece], vol. Vol. 1

DOI: 10.5220/0007706800710076

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Zeitschriftenartikel

Raphaela Pagany, Anna Marquardt, Roland Zink

Electric Charging Demand Location Model—A User- and Destination-Based Locating Approach for Electric Vehicle Charging Stations

Sustainability, vol. 11, no. 8

DOI: 10.3390/su11082301

Abstract anzeigen

In recent years, with the increased focus on climate protection, electric vehicles (EVs) have become a relevant alternative to conventional motorized vehicles. Even though the market share of EVs is still comparatively low, there are ongoing considerations for integrating EVs in transportation systems. Along with pushing EV sales numbers, the installation of charging infrastructure is necessary. This paper presents a user- and destination-based approach for locating charging stations (CSs) for EVs—the electric charging demand location (ECDL) model. With regard to the daily activities of potential EV users, potential positions for CSs are derived on a micro-location level in public and semipublic spaces using geographic information systems (GIS). Depending on the vehicle users’ dwell times and visiting frequencies at potential points of interest (POIs), the charging demand at such locations is calculated. The model is mainly based on a survey analyzing the average time spent per daily activity, regional data about driver and vehicle ownership numbers, and the georeferenced localization of regularly visited POIs. Optimal sites for parking and charging EVs within the POIs neighborhood are selected based on walking distance calculations, including spatial neighborhood effects, such as the density of POIs. In a case study in southeastern Germany, the model identifies concrete places with the highest overall demand for CSs, resulting in an extensive coverage of the electric energy demand while considering as many destinations within the acceptable walking distance threshold as possible.

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Zeitschriftenartikel

Raphaela Pagany, Wolfgang Dorner

Do Crash Barriers and Fences Have an Impact on Wildlife-Vehicle Collisions? An Artificial Intelligence and GIS-Based Analysis

ISPRS International Journal of Geo-Information, vol. 8, no. 2

DOI: 10.3390/ijgi8020066

Abstract anzeigen

Wildlife–vehicle collisions (WVCs) cause significant road mortality of wildlife and have led to the installation of protective measures along streets. Until now, it has been difficult to determine the impact of roadside infrastructure that might act as a barrier for animals. The main deficits are the lack of geodata for roadside infrastructure and georeferenced accidents recorded for a larger area. We analyzed 113 km of road network of the district Freyung-Grafenau, Germany, and 1571 WVCs, examining correlations between the appearance of WVCs, the presence or absence of roadside infrastructure, particularly crash barriers and fences, and the relevance of the blocking effect for individual species. To receive infrastructure data on a larger scale, we analyzed 5596 road inspection images with a neural network for barrier recognition and a GIS for a complete spatial inventory. This data was combined with the data of WVCs in GIS to evaluate the infrastructure’s impact on accidents. The results show that crash barriers have an effect on WVCs, as collisions are lower on roads with crash barriers. In particular, smaller animals have a lower collision share. The risk reduction at fenced sections could not be proven as fenced sections are only available at 3% of the analyzed roads. Thus, especially the fence dataset must be validated by a larger sample number. However, these preliminary results indicate that the combination of artificial intelligence and GIS may be used to analyze and better allocate protective barriers or to apply it in alternative measures, such as dynamic WVC risk-warning.

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Zeitschriftenartikel

Raphaela Pagany, Wolfgang Dorner

Achtung Wildwechsel! Wie ein dynamische GIS-Lösung hilft, Unfälle zu verhindern

arcAKTUELL: Operational Intelligence - Vorausschauend planen, no. 3, pp. 60-61

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Vortrag

Raphaela Pagany

WilDa - Dynamische Wildunfallwarnung mit Hilfe von Verkehrs-, Unfall- und Umweltdaten

4. Jahreskonferenz des Netzwerks INDIGO (Internet und Digitalisierung Ostbayern), Deggendorf

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Vortrag

C. Hoermann, Raphaela Pagany, Wolfgang Dorner, M. Heurich

Experience of roe deer individuals helps to prevent traffic accidents

BioMove Symposium 2018: Integrating Biodiversity Research with Movement Ecology, Potsdam

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Vortrag

C. Hoermann, Raphaela Pagany, Wolfgang Dorner, M. Heurich

Movement ecology meets roads

48th Annual Meeting of the Ecological Society of Germany, Austria and Switzerland, Wien, Österreich

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Zeitschriftenartikel

Raphaela Pagany, Luis Ramirez Camargo, Wolfgang Dorner

A review of spatial localization methodologies for the electric vehicle charging infrastructure

International Journal of Sustainable Transportation, pp. 1-17

DOI: 10.1080/15568318.2018.1481243

Abstract anzeigen

With view to the high share of the transport sector in total energy consumption, e-mobility should play an important role within the transition of the energy systems. Policymakers in several countries consider electric vehicles (EV) as an alternative to fossil-fueled vehicles. In order to allow for the development of EV, the charging infrastructure has to be set up at locations with high charging potential, identified by means of various criteria such as demand density or trip length. Many methodologies for locating charging stations (CS) have been developed in the last few years. First, this paper presents a broad overview of publications in the domain of CS localization. A classification scheme is proposed regarding modeling theory and empirical application; further on, models are analyzed, distinguishing between users, route or destination centricity of the approaches and outcomes. In a second step, studies in the field of explicit spatial location planning are reviewed in more detail, that is, in terms of their target criteria and the specialization of underlying analytical processes. One divergence of these approaches lies in the varying level of spatial planning, which could be crucial depending on the planning requirements. It is striking that almost all CS locating concepts are proposed for urban areas. Other constraints, such as the lack of extensive empirical EV traffic data for a better understanding of the driving behavior, are identified. This paper provides an overview of the CS models, a classification approach especially considering the problem’s spatial dimension, and derives perspectives for further research.