A Framework for Generating Network-Based Moving Objects

By Thomas Brinkhoff. GeoInformatica, 2002

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On Trip Planning Queries in Spatial Databases (2005, methodology): “To generate synthetic datasets we obtained two real road networks, the city of Oldenburg(OL) with 6105 nodes and 7035 edges and San Joaquin county(TG) with 18263 nodes and 23874 edges, from [8].”
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring (2005, result): “In accordance with the experimental study of [XMA05], our datasets are created with the spatiotemporal generator of [ B02 ].”
The new Casper: query processing for location services without compromising privacy (2006, methodology): “In all the experiments of this section, we use the Network-based Generator of Moving Objects [9] to generate a set of moving objects.”
SINA: scalable incremental processing of continuous queries in spatio-temporal databases (2004, methodology): “We use the Network-based Generator of Moving Objects [3] to generate a set of moving objects and moving queries.”
Privacy Preservation in the Publication of Trajectories (2008, methodology): “For this purpose, we generated synthetic trajectories of moving objects using Brinkhoff’s generator [4].”
Trajectory Data Mining (2015, neutral): “BerlinMod [29] and Thomas-Brinkhoff [10].”
PRIVE: anonymous location-based queries in distributed mobile systems (2007, methodology): “Our workload consists of user locations and movement patterns, and is generated using IAPG [5], which models user movement on public roads.”