activity
20172024
most citedINTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

354 citations · 368 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.RO2024

Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations

Matthias Bitzer, Reinis Cimurs, Benjamin Coors +4

Simulation plays a crucial role in the rapid development and safe deployment of autonomous vehicles. Realistic traffic agent models are indispensable for bridging the gap between s…

cs.RO2019354 cited

INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

Wei Zhan, Liting Sun, Di Wang +8

Behavior-related research areas such as motion prediction/planning, representation/imitation learning, behavior modeling/generation, and algorithm testing, require support from hig…

cs.RO2018

Generating Comfortable, Safe and Comprehensible Trajectories for Automated Vehicles in Mixed Traffic

Maximilian Naumann, Martin Lauer, Christoph Stiller

While motion planning approaches for automated driving often focus on safety and mathematical optimality with respect to technical parameters, they barely consider convenience, per…

cs.RO20174 cited

Cooperative Motion Planning for Non-Holonomic Agents with Value Iteration Networks

Eike Rehder, Maximilian Naumann, Niels Ole Salscheider +1

Cooperative motion planning is still a challenging task for robots. Recently, Value Iteration Networks (VINs) were proposed to model motion planning tasks as Neural Networks. In th…

cs.RO201710 cited

Towards Cooperative Motion Planning for Automated Vehicles in Mixed Traffic

Maximilian Naumann, Christoph Stiller

While motion planning techniques for automated vehicles in a reactive and anticipatory manner are already widely presented, approaches to cooperative motion planning are still rema…