research
∙
09/18/2023
Traffic Scene Similarity: a Graph-based Contrastive Learning Approach
Ensuring validation for highly automated driving poses significant obsta...
share
research
∙
09/18/2023
Conditioning Latent-Space Clusters for Real-World Anomaly Classification
Anomalies in the domain of autonomous driving are a major hindrance to t...
research
∙
09/13/2023
Utilizing Hybrid Trajectory Prediction Models to Recognize Highly Interactive Traffic Scenarios
Autonomous vehicles hold great promise in improving the future of transp...
research
∙
09/05/2023
Traffic Light Recognition using Convolutional Neural Networks: A Survey
Real-time traffic light recognition is essential for autonomous driving....
research
∙
08/10/2023
Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving
In recent years there have been remarkable advancements in autonomous dr...
research
∙
07/17/2023
Adversarial Attacks on Traffic Sign Recognition: A Survey
Traffic sign recognition is an essential component of perception in auto...
research
∙
06/08/2023
Unscented Autoencoder
The Variational Autoencoder (VAE) is a seminal approach in deep generati...
research
∙
06/06/2023
Bridging the Gap Between Multi-Step and One-Shot Trajectory Prediction via Self-Supervision
Accurate vehicle trajectory prediction is an unsolved problem in autonom...
research
∙
05/23/2023
From Model-Based to Data-Driven Simulation: Challenges and Trends in Autonomous Driving
Simulation is an integral part in the process of developing autonomous v...
research
∙
04/21/2023
Inverse Universal Traffic Quality – a Criticality Metric for Crowded Urban Traffic Scenes
An essential requirement for scenario-based testing the identification o...
research
∙
04/21/2023
A Comprehensive Review on Ontologies for Scenario-based Testing in the Context of Autonomous Driving
The verification and validation of autonomous driving vehicles remains a...
research
∙
02/06/2023
Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey
Deep neural networks (DNN) which are employed in perception systems for ...
research
∙
01/31/2023
Holistic Graph-based Motion Prediction
Motion prediction for automated vehicles in complex environments is a di...
research
∙
01/05/2023
Impact, Attention, Influence: Early Assessment of Autonomous Driving Datasets
Autonomous Driving (AD), the area of robotics with the greatest potentia...
research
∙
11/24/2022
Self Supervised Clustering of Traffic Scenes using Graph Representations
Examining graphs for similarity is a well-known challenge, but one that ...
research
∙
11/24/2022
Fingerprint of a Traffic Scene: an Approach for a Generic and Independent Scene Assessment
A major challenge in the safety assessment of automated vehicles is to e...
research
∙
10/26/2022
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception
LiDAR sensors are an integral part of modern autonomous vehicles as they...
research
∙
09/27/2022
Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise
Although numerous methods to reduce the overfitting of convolutional neu...
research
∙
09/27/2022
Suppress with a Patch: Revisiting Universal Adversarial Patch Attacks against Object Detection
Adversarial patch-based attacks aim to fool a neural network with an int...
research
∙
09/01/2022
One Ontology to Rule Them All: Corner Case Scenarios for Autonomous Driving
The core obstacle towards a large-scale deployment of autonomous vehicle...
research
∙
08/31/2022
A Realism Metric for Generated LiDAR Point Clouds
A considerable amount of research is concerned with the generation of re...
research
∙
07/15/2022
Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection
Standard approaches for adversarial patch generation lead to noisy consp...
research
∙
07/13/2022
DLCSS: Dynamic Longest Common Subsequences
Autonomous driving is a key technology towards a brighter, more sustaina...
research
∙
07/13/2022
Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers
Great progress has been achieved in the community of autonomous driving ...
research
∙
05/17/2022
An Application of Scenario Exploration to Find New Scenarios for the Development and Testing of Automated Driving Systems in Urban Scenarios
Verification and validation are major challenges for developing automate...
research
∙
05/03/2022
Multimodal Detection of Unknown Objects on Roads for Autonomous Driving
Tremendous progress in deep learning over the last years has led towards...
research
∙
04/22/2022
Balancing Expert Utilization in Mixture-of-Experts Layers Embedded in CNNs
This work addresses the problem of unbalanced expert utilization in spar...
research
∙
04/21/2022
Is Neuron Coverage Needed to Make Person Detection More Robust?
The growing use of deep neural networks (DNNs) in safety- and security-c...
research
∙
04/17/2022
Anomaly Detection in Autonomous Driving: A Survey
Nowadays, there are outstanding strides towards a future with autonomous...
research
∙
03/09/2022
Cooperative Trajectory Planning in Uncertain Environments with Monte Carlo Tree Search and Risk Metrics
Automated vehicles require the ability to cooperate with humans for smoo...
research
∙
02/17/2022
Point Cloud Generation with Continuous Conditioning
Generative models can be used to synthesize 3D objects of high quality a...
research
∙
02/14/2022
Learning Reward Models for Cooperative Trajectory Planning with Inverse Reinforcement Learning and Monte Carlo Tree Search
Cooperative trajectory planning methods for automated vehicles, are capa...
research
∙
02/07/2022
Quantification of Actual Road User Behavior on the Basis of Given Traffic Rules
Driving on roads is restricted by various traffic rules, aiming to ensur...
research
∙
02/03/2022
Ad-datasets: a meta-collection of data sets for autonomous driving
Autonomous driving is among the largest domains in which deep learning h...
research
∙
11/30/2021
Semi-Local Convolutions for LiDAR Scan Processing
A number of applications, such as mobile robots or automated vehicles, u...
research
∙
11/26/2021
StarNet: Joint Action-Space Prediction with Star Graphs and Implicit Global Frame Self-Attention
In this work, we present a novel multi-modal multi-agent trajectory pred...
research
∙
11/19/2021
Towards Traffic Scene Description: The Semantic Scene Graph
For the classification of traffic scenes, a description model is necessa...
research
∙
11/05/2021
Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models
In the foreseeable future, autonomous vehicles will require human assist...
research
∙
09/24/2021
Quantifying point cloud realism through adversarially learned latent representations
Judging the quality of samples synthesized by generative models can be t...
research
∙
09/21/2021
Self-Supervised Action-Space Prediction for Automated Driving
Making informed driving decisions requires reliable prediction of other ...
research
∙
09/20/2021
Description of Corner Cases in Automated Driving: Goals and Challenges
Scaling the distribution of automated vehicles requires handling various...
research
∙
09/17/2021
Taxonomy and Survey on Remote Human Input Systems for Driving Automation Systems
Corner cases for driving automation systems can often be detected by the...
research
∙
05/14/2021
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems
Full-stack autonomous driving perception modules usually consist of data...
research
∙
05/04/2021
Reliving the Dataset: Combining the Visualization of Road Users' Interactions with Scenario Reconstruction in Virtual Reality
One core challenge in the development of automated vehicles is their cap...
research
∙
04/14/2021
Safe Continuous Control with Constrained Model-Based Policy Optimization
The applicability of reinforcement learning (RL) algorithms in real-worl...
research
∙
03/22/2021
Temporal Feature Networks for CNN based Object Detection
For reliable environment perception, the use of temporal information is ...
research
∙
02/12/2021
Generalizing Decision Making for Automated Driving with an Invariant Environment Representation using Deep Reinforcement Learning
Data driven approaches for decision making applied to automated driving ...
research
∙
03/30/2020
Parallelization of Monte Carlo Tree Search in Continuous Domains
Monte Carlo Tree Search (MCTS) has proven to be capable of solving chall...
research
∙
02/02/2020
Accelerating Cooperative Planning for Automated Vehicles with Learned Heuristics and Monte Carlo Tree Search
Efficient driving in urban traffic scenarios requires foresight. The obs...
research
∙
06/28/2019