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Found 18 papers, 1 papers with code
Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation
We also present our first results of an iterative training cycle that outperforms the baseline and where the data added to the training dataset is selected based on the corner case decision function.
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving
As common evaluation metrics are not an adequate safety indicator, recent works employ approaches to identify safety-critical VRU and back-annotate the risk to the object detector.
Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving
Based on these predictions - and additional contextual information such as the course of the road, (traffic) rules, and interaction with other road users - the highly automated vehicle (HAV) must be able to reliably and safely perform the task assigned to it, e. g., moving from point A to B.
Description of Corner Cases in Automated Driving: Goals and Challenges
Scaling the distribution of automated vehicles requires handling various unexpected and possibly dangerous situations, termed corner cases (CC).
Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders
For this purpose, we propose a novel approach that allows for the generation of out-of-distribution datasets based on a given in-distribution dataset.
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving
Systems and functions that rely on machine learning (ML) are the basis of highly automated driving.
Quantile Surfaces -- Generalizing Quantile Regression to Multivariate Targets
In this article, we present a novel approach to multivariate probabilistic forecasting.
Extended Coopetitive Soft Gating Ensemble
This article is about an extension of a recent ensemble method called Coopetitive Soft Gating Ensemble (CSGE) and its application on power forecasting as well as motion primitive forecasting of cyclists.
Knowledge Representations in Technical Systems -- A Taxonomy
The recent usage of technical systems in human-centric environments leads to the question, how to teach technical systems, e. g., robots, to understand, learn, and perform tasks desired by the human.
Multi-Sensor Data and Knowledge Fusion -- A Proposal for a Terminology Definition
Fusion is a common tool for the analysis and utilization of available datasets and so an essential part of data mining and machine learning processes.
Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence
Heterogeneous, open sets of agents (cooperating and interacting vehicles, infrastructure, e. g. cameras and laser scanners, and VRUs equipped with smart devices and body-worn sensors) exchange information forming a multi-modal sensor system with the goal to reliably and robustly detect VRUs and their intentions under consideration of real time requirements and uncertainties.
Starting Movement Detection of Cyclists Using Smart Devices
In near future, vulnerable road users (VRUs) such as cyclists and pedestrians will be equipped with smart devices and wearables which are capable to communicate with intelligent vehicles and other traffic participants.
Smart Device based Initial Movement Detection of Cyclists using Convolutional Neuronal Networks
For future traffic scenarios, we envision interconnected traffic participants, who exchange information about their current state, e. g., position, their predicted intentions, allowing to act in a cooperative manner.
Coopetitive Soft Gating Ensemble
In this article, we propose the Coopetititve Soft Gating Ensemble or CSGE for general machine learning tasks and interwoven systems.
Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble
In future, vehicles and other traffic participants will be interconnected and equipped with various types of sensors, allowing for cooperation on different levels, such as situation prediction or intention detection.
Highly Automated Learning for Improved Active Safety of Vulnerable Road Users
Highly automated driving requires precise models of traffic participants.
Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure
We show in numerical evaluations on scenes where cyclists are starting or turning right that the cooperation leads to an improvement in both the ability to keep track of a cyclist and the accuracy of the track particularly when it comes to occlusions in the visual system.
Where is my Device? - Detecting the Smart Device's Wearing Location in the Context of Active Safety for Vulnerable Road Users
This article describes an approach to detect the wearing location of smart devices worn by pedestrians and cyclists.
