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Modeling of high-level driving decisions from naturalistic driving data for multi-agent traffic simulation

Traditional hierarchical driving stacks for simulated traffic agents have inherent shortcomings in generating trajectories that are both feasible and naturalistic on high and low abstraction levels.
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