29 citations · 121 across the 63 of their papers we have counts for
13 papers · 1 filter
Modular Fault Diagnosis Framework for Complex Autonomous Driving Systems
Stefan Orf, Sven Ochs, Jens Doll +4
Fault diagnosis is crucial for complex autonomous mobile systems, especially for modern-day autonomous driving (AD). Different actors, numerous use cases, and complex heterogeneous…
Empowering Autonomous Shuttles with Next-Generation Infrastructure
Sven Ochs, Melih Yazgan, Rupert Polley +9
As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how peo…
From One to the Power of Many: Invariance to Multi-LiDAR Perception from Single-Sensor Datasets
Marc Uecker, J. Marius Zöllner
Recently, LiDAR segmentation methods for autonomous vehicles, powered by deep neural networks, have experienced steep growth in performance on classic benchmarks, such as nuScenes…
Efficient Data Representation for Motion Forecasting: A Scene-Specific Trajectory Set Approach
Abhishek Vivekanandan, J. Marius Zöllner
Representing diverse and plausible future trajectories is critical for motion forecasting in autonomous driving. However, efficiently capturing these trajectories in a compact set…
Label-Free Model Failure Detection for Lidar-based Point Cloud Segmentation
Daniel Bogdoll, Finn Sartoris, Vincent Geppert +2
Autonomous vehicles drive millions of miles on the road each year. Under such circumstances, deployed machine learning models are prone to failure both in seemingly normal situatio…
Iterative Filter Pruning for Concatenation-based CNN Architectures
Svetlana Pavlitska, Oliver Bagge, Federico Peccia +2
Model compression and hardware acceleration are essential for the resource-efficient deployment of deep neural networks. Modern object detectors have highly interconnected convolut…
A Review of Reward Functions for Reinforcement Learning in the context of Autonomous Driving
Ahmed Abouelazm, Jonas Michel, J. Marius Zoellner
Reinforcement learning has emerged as an important approach for autonomous driving. A reward function is used in reinforcement learning to establish the learned skill objectives an…
A Survey on Intermediate Fusion Methods for Collaborative Perception Categorized by Real World Challenges
Melih Yazgan, Thomas Graf, Min Liu +2
This survey analyzes intermediate fusion methods in collaborative perception for autonomous driving, categorized by real-world challenges. We examine various methods, detailing the…
CoCar NextGen: a Multi-Purpose Platform for Connected Autonomous Driving Research
Marc Heinrich, Maximilian Zipfl, Marc Uecker +9
Real world testing is of vital importance to the success of automated driving. While many players in the business design purpose build testing vehicles, we designed and build a mod…
Scene-Extrapolation: Generating Interactive Traffic Scenarios
Maximilian Zipfl, Barbara Schütt, J. Marius Zöllner
Verifying highly automated driving functions can be challenging, requiring identifying relevant test scenarios. Scenario-based testing will likely play a significant role in verify…
One Stack to Rule them All: To Drive Automated Vehicles, and Reach for the 4th level
Sven Ochs, Jens Doll, Daniel Grimm +15
Most automated driving functions are designed for a specific task or vehicle. Most often, the underlying architecture is fixed to specific algorithms to increase performance. There…
Leveraging Swarm Intelligence to Drive Autonomously: A Particle Swarm Optimization based Approach to Motion Planning
Sven Ochs, Jens Doll, Marc Heinrich +4
Motion planning is an essential part of autonomous mobile platforms. A good pipeline should be modular enough to handle different vehicles, environments, and perception modules. Th…
Can you see me now? Blind spot estimation for autonomous vehicles using scenario-based simulation with random reference sensors
Marc Uecker, J. Marius Zöllner
In this paper, we introduce a method for estimating blind spots for sensor setups of autonomous or automated vehicles and/or robotics applications. In comparison to previous method…