The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Later among the works it cites.

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