Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Florian Schule"'
Autor:
Julian Forster, Hendrik P. A. Lensch, Roland Schweiger, Matthias Limmer, Dennis Baudach, Florian Schule
Publikováno v:
ITSC
This paper proposes an approach that predicts the road course from camera sensors lever-aging deep learning techniques. Road pixels are identified by training a multi-scale convolutional neural network on a large number of full-scene-labeled night-ti
Autor:
Markus Gressmann, Alexander Bachmann, Lars Kahlke, Benoit Vanholme, Leo Neumann, Florian Schule
Publikováno v:
ITSC
Increasingly complex automated driving functions require ever more accurate environment models. If relevant information is missing, automated vehicle control may induce safety risks. In this paper, we describe a joint development of BMW and Continent
Publikováno v:
ITSC
Digital maps are a key information for road course estimation in large distances, especially for automated driving with higher speeds or during nighttime. However, digital maps may contain errors caused by road changes or inaccurate recordings. As th
Publikováno v:
ITSC
Localization on a digital map is a crucial point for many advanced driver assistance systems that make use of digital map data. State of the art work mainly relies on inaccurate Global Positioning System (GPS) measurements, special and costly sensors
Publikováno v:
Intelligent Vehicles Symposium
Accurate and robust environment perception is a prerequisite for advanced driver assistance systems such as parking assistance, collision avoidance or night vision systems but also for robot navigation. In this context, occupancy grid mapping is a co
Publikováno v:
ITSC
This paper presents an advanced road course prediction algorithm focusing on longer distances. It shows how to simply combine the different sensors available in modern cars for a road course estimation task. Concretely, a digital-map-based estimation
Autor:
Florian Schule, Klaus Dietmayer, Oliver Hartmann, Raimar Wagner, Roland Schweiger, Michael Gabb
Publikováno v:
Intelligent Vehicles Symposium
Detecting the road geometry at night time is an essential precondition to provide optimal illumination for the driver and the other traffic participants. In this paper we propose a novel approach to estimate the current road curvature based on three
Publikováno v:
Intelligent Vehicles Symposium
The camera relative pose is essential information for driver assistance systems in general, and especially so for systems that aim to visualize obstacles or other relevant objects for the driver. In order to display objects that were not detected in
Publikováno v:
Intelligent Vehicles Symposium
This paper presents a generic grid mapping approach which can be used to map huge areas. A special map definition based on so called grid patches is proposed to limit memory usage and make it real time capable. The grid cells of this map can hold arb
Autor:
Marcus Konrad, Florian Schule, Magdalena Szczot, Matthias Serfling, Otto Lohlein, Klaus Dietmayer
Publikováno v:
Intelligent Vehicles Symposium
This contribution presents a lane estimation system for night applications which covers distances up to 140 m in rural environment. The high detection range is essential for upcoming warning systems to decide whether a detected object is on the road