InformaApp - Publikationen

Raphaela Pagany, Anna Marquardt, Roland Zink

Zeitschriftenartikel

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

Sustainability, vol. 11, no. 8

2019

DOI: 10.3390/su11082301

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.

Zeitschriftenartikel

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

2019

DOI: 10.3390/ijgi8020066

Digital Mobil Elektrotechnik und Medientechnik TC Freyung

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.

Zeitschriftenartikel

Digital Mobil Elektrotechnik und Medientechnik TC Freyung

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

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

2018

Vortrag

Raphaela Pagany

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

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

2018

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

2018

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

2018

Raphaela Pagany, Luis Ramirez Camargo, Wolfgang Dorner

Zeitschriftenartikel

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

International Journal of Sustainable Transportation, pp. 1-17

2018

DOI: 10.1080/15568318.2018.1481243

Digital Mobil Nachhaltig Elektrotechnik und Medientechnik TC Freyung

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.

Zeitschriftenartikel

Anna Marquardt, Raphaela Pagany, Roland Zink

Wohin mit den Strom-Tankstellen

arcAKTUELL: Location Intelligence - Das Wesentliche finden, no. 2, pp. 60-61

2018

Digital TC Freyung

Vortrag

F. Oloo, Raphaela Pagany, G. Kothencz

Multi-dimensionality of Uncertainty in Big Geospatial Sensor Data

GI Forum 2018, Salzburg, Österreich

2018

Digital TC Freyung

Zeitschriftenartikel

F. Oloo, Raphaela Pagany, G. Kothencz

Multi-dimensionality of Uncertainty in Big Geospatial Sensor Data

GI Forum - Journal of Geographic Information Science, no. Issue 1, pp. 3-15

2018

DOI: 10.1553/giscience2018_01_s3

Developments in sensor technology have contributed immensely to the growth of big geospatial sensor data. Moreover, advances in telecommunications have made it possible to use in-situ sensors to capture and transfer data about the environment in near real-time. The combination of various sensor types within a predefined geographic space and the possibility of making measurements at high temporal resolution contributes to a better understanding of our environment while also generating big geospatial sensor data. Big data from multi-sensor networks, particularly those that capture dynamic characteristics of the environment, have not been spared the challenges that face other types of big data. Specifically, the quality of data and the propagation of uncertainty through the multi-sensor data processing workflows have remained a major concern in the big geospatial sensor data research community. Attempts to document, quantify and communicate the uncertainty associated with sensor data and related sensor network outputs have been made mainly in the context of individual projects. This paper aims to document the state-of-art in defining uncertainty with regard to multi-sensor geospatial data. In particular, we analyse the current literature to outline different types of uncertainty, and document methods for handling uncertainty in the different stages of multi-sensor geospatial data collection, processing and delivery.

Digital Mobil TC Freyung

Vortrag

Geostatistische Risikoberechnung zur dynamischen Wildunfallwarnung

Posterpräsentation

5. Tag der Forschung, Deggendorf

2018

TC Freyung

Vortrag