|Publication type:||Conference other|
|Type of review:||Not specified|
|Title:||Visualizing traffic data with Google Earth : real-time air traffic in 3D|
|Conference details:||Swiss Transport Research Conference, Ascona, 1-3 September 2010|
|Subjects:||Air traffic; 3D visualization; Google earth; Traffic data|
|Abstract:||During the last decades, traffic demand increased continuously for all transport modes, while supply, i.e. infrastructures and their management, could often not keep pace with this growth. Some of the consequences are severe congestions, delays, emissions (green-house gases, articles), all leading to enormous costs. One important input to optimally manage traffic systems is accurate and reliable information on the system’s current and predicted state. Depending on the transport mode under consideration, a variety of traffic data sources is available, capturing either local conditions or the movement of objects through time and space. From these data, appropriate traffic information can be extracted and based on this, management decisions can be made and/or services provided. Due to the widespread use of intelligent communication technologies (ICT) and the arising convergence of communication, navigation, and positioning technologies/devices, many new services have emerged, often belonging to the group of so called location based services (LBS). Regarding the field of transport, these services include, amongst others, information on traffic state, recommendations of routes to travel together with corresponding travel time information, availability of taxis or public transport connections. With mobile or computer based applications and a variety of tools specialized in visualizing traffic and geographic information as well as other contents (e.g., Google Earth), traffic participants are able to get appropriate and useful information while travelling through transport networks. In this paper, we present a framework to compute and visualize traffic information in real-time and in two or three dimensional space. To demonstrate its practical use, we apply the approach to real-time data from air traffic over parts of Switzerland and Central Europe, where trajectories of a number of airplanes equipped with ADS-B are visualized. After a system's overview we provide an introduction to the algorithm, discuss computational aspects and present some examples using real data.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Data Analysis and Process Design (IDP)|
|Appears in collections:||Publikationen School of Engineering|
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