1 citations · 1 across the 12 of their papers we have counts for
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AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework
Yu Yao, Salil Bhatnagar, Markus Mazzola +5
Rare, yet critical, scenarios pose a significant challenge in testing and evaluating autonomous driving planners. Relying solely on real-world driving scenes requires collecting ma…
Joint Out-of-Distribution Detection and Uncertainty Estimation for Trajectory Prediction
Julian Wiederer, Julian Schmidt, Ulrich Kressel +2
Despite the significant research efforts on trajectory prediction for automated driving, limited work exists on assessing the prediction reliability. To address this limitation we…
A Benchmark for Unsupervised Anomaly Detection in Multi-Agent Trajectories
Julian Wiederer, Julian Schmidt, Ulrich Kressel +2
Human intuition allows to detect abnormal driving scenarios in situations they never experienced before. Like humans detect those abnormal situations and take countermeasures to pr…
A Multi-Task Recurrent Neural Network for End-to-End Dynamic Occupancy Grid Mapping
Marcel Schreiber, Vasileios Belagiannis, Claudius Gläser +1
A common approach for modeling the environment of an autonomous vehicle are dynamic occupancy grid maps, in which the surrounding is divided into cells, each containing the occupan…