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- W3133721951 abstract "The management of traffic information is an essential component of Intelligent Transport Systems (ITS). This traffic is no longer confined to roads but is increasingly emerging into the airspace. Recent developments in the field of unmanned aerial systems (UAS) enable new ways of transportation. Furthermore, the sensor systems of these traffic participants, such as cars, drones, and also intelligent infrastructure, are becoming increasingly prominent and powerful. Thus, future ITS will be confronted with the challenge of ever-increasing amounts of data from a wide variety of different traffic participants. Based on this, a novel concept is presented, how data from multi-modal traffic users can be accumulated. To accomplish this, a parametrized geographic data-centric model is presented that can map traffic routes of arbitrary shape in 2- and 3D environments. By this, traffic management of multimodal vehicles (cars, UAS, etc.) can be represented by one unique multimodal model. Furthermore, the parametrized data model allows situational data processing (e.g. congestion, weather condition, etc.) on a local and global basis. The geographic model extends Geo JSON as its foundation in order to rely on well-established standards." @default.
- W3133721951 created "2021-03-15" @default.
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- W3133721951 date "2020-12-09" @default.
- W3133721951 modified "2023-09-26" @default.
- W3133721951 title "Spatial Extension Model for Multimodal Traffic Management" @default.
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- W3133721951 doi "https://doi.org/10.1145/3448823.3448854" @default.
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