6 citations · 11 across the 15 of their papers we have counts for
6 papers · 1 filter
Temporal Residual Bottleneck for Robust Asynchronous Collaborative Perception
Melih Yazgan, Ahmed Abouelazm, J. Marius Zöllner
Collaborative perception extends the sensing range of autonomous vehicles, but its performance degrades when shared features arrive stale or incomplete. Most latency-robust methods…
Beyond Waypoint Regression: Query-Based Cost Learning over Reachable Ego Futures for End-to-End Driving
Ahmed Abouelazm, Rupert Polley, Qingyuan Zhang +4
End-to-end planners based on waypoint regression achieve strong open-loop accuracy, but they primarily learn to mimic expert geometry and remain difficult to adapt to deployment-ti…
Safety-Critical Scenarios Emerge from Initial Scenes
Yin Wu, Jiarong Wei, Carl Esselborn +4
Safety-critical driving scenario generation has largely focused on manipulating the behavior of surrounding agents while starting from an initial scene from driving data. This assu…
Uncertainty-Aware and Temporally Regulated Expert Advice in Reinforcement Learning for Autonomous Driving
Ahmed Abouelazm, Felix Klingebiel, Philip Schörner +1
Exploration in reinforcement learning for autonomous driving is inherently unsafe: agents must experience novel behaviors to learn, yet exploration can lead to collisions or off-ro…
Beyond Scalar Rewards: Distributional Reinforcement Learning with Preordered Objectives for Safe and Reliable Autonomous Driving
Ahmed Abouelazm, Jonas Michel, Daniel Bogdoll +2
Autonomous driving involves multiple, often conflicting objectives such as safety, efficiency, and comfort. In reinforcement learning (RL), these objectives are typically combined…
Efficient Cross-Country Data Acquisition Strategy for ADAS via Street-View Imagery
Yin Wu, Daniel Slieter, Carl Esselborn +3
Deploying ADAS and ADS across countries remains challenging due to differences in legislation, traffic infrastructure, and visual conventions, which introduce domain shifts that de…