KI-PMF: Knowledge Integrated Plausible Motion Forecasting

no code implementations • 18 Oct 2023 • Abhishek Vivekanandan, Ahmed Abouelazm, Philip Schörner, J. Marius Zöllner

Accurately forecasting the motion of traffic actors is crucial for the deployment of autonomous vehicles at a large scale.

Autonomous Vehicles Motion Forecasting +1

Plausibility Verification For 3D Object Detectors Using Energy-Based Optimization

no code implementations • 2 Nov 2022 • Abhishek Vivekanandan, Niels Maier, J. Marius Zoellner

Environmental perception obtained via object detectors have no predictable safety layer encoded into their model schema, which creates the question of trustworthiness about the system's prediction.

Autonomous Vehicles Object +2

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

no code implementations • 10 May 2022 • Julian Wörmann, Daniel Bogdoll, Christian Brunner, Etienne Bührle, Han Chen, Evaristus Fuh Chuo, Kostadin Cvejoski, Ludger van Elst, Philip Gottschall, Stefan Griesche, Christian Hellert, Christian Hesels, Sebastian Houben, Tim Joseph, Niklas Keil, Johann Kelsch, Mert Keser, Hendrik Königshof, Erwin Kraft, Leonie Kreuser, Kevin Krone, Tobias Latka, Denny Mattern, Stefan Matthes, Franz Motzkus, Mohsin Munir, Moritz Nekolla, Adrian Paschke, Stefan Pilar von Pilchau, Maximilian Alexander Pintz, Tianming Qiu, Faraz Qureishi, Syed Tahseen Raza Rizvi, Jörg Reichardt, Laura von Rueden, Alexander Sagel, Diogo Sasdelli, Tobias Scholl, Gerhard Schunk, Gesina Schwalbe, Hao Shen, Youssef Shoeb, Hendrik Stapelbroek, Vera Stehr, Gurucharan Srinivas, Anh Tuan Tran, Abhishek Vivekanandan, Ya Wang, Florian Wasserrab, Tino Werner, Christian Wirth, Stefan Zwicklbauer

The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models.

Autonomous Driving BIG-bench Machine Learning