trajectory prediction
The dataset consists of vessel tracking data in the form of AIS observations in the Baltic Sea during years 2017-19. The AIS observations have been enriched with vessel metadata such as power, max speed and draft. The data has been collected for master’s thesis work and the data has been splitter into training and validation sets. The AIS observations do not cover all months of the collection period.
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The odometric model is simulated herein. We described the trajectory of such one odometric model, with the delta of the heading angle given as one parameter of the simulation. The iterations show that the trajectory is well in the continuity of the variations of the heading angle. Moreover the distance in X and in Y are shown for the vehicle to be driven in the trajectory of the odometric model.
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The dataset consists of tracking data of over 23,000 vehicles travelling though five different roundabouts in Sydney, Australia. This data was collected by a vehicle outfitted with a ibeo.HAD Feature Fusion detection and tracking system. This system uses 6 ibeo LUX 4 beam, 25 Hz Lidar scanners to identify road users at a range of up to 200m, and has an on-board computer for classification and tracking, in real time.
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