Skip to main content
Ir a la página de inicio de la Comisión Europea (se abrirá en una nueva ventana)
español español
CORDIS - Resultados de investigaciones de la UE
CORDIS

Robust Automated Driving in Extreme Weather

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Test plan regarding the most appropriate test method (se abrirá en una nueva ventana)

Report defining how to test single components and integrated automated vehicle systems in virtual and real domains. It will consider specific uses-cases under extreme weather conditions.

Initial readiness assessment of specific datasets (se abrirá en una nueva ventana)

Report on the quantitative evaluation of the ROADVIEW DRL method on public datasets using a limited feature size.

Interim impact report (se abrirá en una nueva ventana)

Interim impact report on communication and dissemination activities, including those at the international level. An update of the DCP plan will be considered.

SW on Improved Localization Using High-density Map Updating - First report (se abrirá en una nueva ventana)

A first report related SW of a compressed HD map representation that can cope with the seasonal changes and can be kept updated while excluding the dynamic objects.

SW on Adaptive Sensor Fusion and Perception Solutions - First report (se abrirá en una nueva ventana)

A first report on algorithms and SW developed to detect weather-related physical conditions (e.g., heavy rain, fog, slush and snow), free space detection, object detection and tracking, and adaptive sensor fusion.

Stakeholder report and strategy (se abrirá en una nueva ventana)

Stakeholder report and strategy including detailed stakeholder mapping and strategies to reach key target audiences.

Vehicle dynamics modelling methodology (se abrirá en una nueva ventana)

A public report will be published along with any relevant publications on vehicle dynamics modelling methodologies. In addition, a representative library of vehicle dynamics models for a selection of vehicles available within the consortium will be delivered.

Definition of the complex environment conditions (se abrirá en una nueva ventana)

An extended ODD taxonomy will be reported considering harsh weather conditions and complex urban/rural environments.

SW on Collaborative Perception Solutions - First report (se abrirá en una nueva ventana)

A first report on improving vehicle perception with sharing information provided by sensors from other connected vehicles or VRUs and roadside infrastructure.

Use cases and scenarios (se abrirá en una nueva ventana)

A set of use cases with multiple scenarios will be reported based on the ODD taxonomy defined in Task 2.1.

Plan for the dissemination and communication activities (se abrirá en una nueva ventana)

Plan for the dissemination and communication activities including defined strategy, tools, channels and (international) activities.

Reference dataset of measured weather characteristics (se abrirá en una nueva ventana)

Reference datasets for the controlled environment and real-world site weather characteristics will be delivered, with a detailed report on data collection methodology.

ROADVIEW website (se abrirá en una nueva ventana)

ROADVIEW website with dedicated areas for different stakeholder groups.

ROADVIEW Demonstration 1 (se abrirá en una nueva ventana)

Report on the demonstration of early ROADVIEW system components implementations to be used in the subsequent demonstrations.

Library of validated statistical noise models (se abrirá en una nueva ventana)

A library of validated statistical noise models for the selected perception sensor technologies will be delivered with a detailed report on implementation and validation methods used.

Publicaciones

Synthetic Extreme Weather for AI training: Concept and Validation (se abrirá en una nueva ventana)

Autores: Letícia Cristófoli Duarte Silva, Maikol Funk Drechsler, Yuri Poledna, Werner Huber, Thiago Antonio Fiorentin
Publicado en: 2023 Third International Conference on Digital Data Processing (DDP), 2024, ISSN 2473-2001
Editor: IEEExplore
DOI: 10.1109/DDP60485.2023.00044

The effect of camera data degradation factors on panoptic segmentation for automated driving

Autores: Wang, Yiting, Zhao, Haonan, Debattista, Kurt and Donzella, Valentina
Publicado en: 26th IEEE International Conference on Intelligent Transportation Systems (ITSC 2023), 2023
Editor: WRAP Warwick

3D-OutDet: A Fast and Memory Efficient Outlier Detector for 3D LiDAR Point Clouds in Adverse Weather (se abrirá en una nueva ventana)

Autores: Abu Mohammed Raisuddin, Tiago Cortinhal, Jesper Holmblad, Eren Erdal Aksoy
Publicado en: TechRxiv, 2023
Editor: TechRxiv
DOI: 10.36227/techrxiv.24297166.v1

Semantics-aware LiDAR-Only Pseudo Point Cloud Generation for 3D Object Detection (se abrirá en una nueva ventana)

Autores: Tiago Cortinhal, Idriss Gouigah, Eren Erdal Aksoy
Publicado en: arXiv, 2023
Editor: arXiv
DOI: 10.48550/arXiv.2309.08932

Raw camera data object detectors: an optimisation for automotive processing and transmission (se abrirá en una nueva ventana)

Autores: Pak Hung Chan, Chuheng Wei, Anthony Huggett, Valentina Donzella
Publicado en: TechRxiv, 2023
Editor: TechRxiv
DOI: 10.36227/techrxiv.23807499.v1

Correlating traditional image quality metrics and DNN-based object detection: a case study with compressed camera data (se abrirá en una nueva ventana)

Autores: Daniel Gummadi, Pak Hung Chan, Hetian Wang, Valentina Donzella
Publicado en: TechRxiv, 2023
Editor: TechRxiv
DOI: 10.36227/techrxiv.24566371.v1

Analysis of Faster R-CNN network prediction in the presence of lens occlusion and video compression (se abrirá en una nueva ventana)

Autores: Gabriele Baris, Boda Li, Pak Hung Chan, Carlo Alberto Avizzano, Valentina Donzella
Publicado en: TechRxiv, 2023
Editor: TechRxiv
DOI: 10.36227/techrxiv.23047412.v1

A noise analysis of 4D RADAR: robust sensing for automotive? (se abrirá en una nueva ventana)

Autores: Pak Hung Chan, Sepeedeh Shahbeigi Roudposhti, Xinyi Ye, Valentina Donzella
Publicado en: TechRxiv, 2023
Editor: TechRxiv
DOI: 10.36227/techrxiv.24517249.v1

Pixelwise Road Surface Slipperiness Estimation for Autonomous Driving with Weakly Supervised Learning

Autores: Julius Pesonen
Publicado en: Machine Learning, Data Science and Artificial Intelligence, 2023
Editor: Aaltodoc publication archive

A Novel Score-based LiDAR Point Cloud degradation Analysis Method (se abrirá en una nueva ventana)

Autores: Sepeedeh Shahbeigi, Honahan Robinson, Valentina Donzella
Publicado en: IEEE Transactions and Journals, 2024, ISSN 1803-7232
Editor: IEEE Xplore
DOI: 10.1109/ACCESS.2024.3359300

Depth- and semantics-aware multi-modal domain translation: Generating 3D panoramic color images from LiDAR point clouds (se abrirá en una nueva ventana)

Autores: Tiago Cortinhal, Eren Erdal Aksoy
Publicado en: Robotics and Autonomous Systems, 2023, ISSN 0921-8890
Editor: Science Direct | Elsevier
DOI: 10.1016/j.robot.2023.104583

SWEET: A Realistic Multiwavelength 3D Simulator for Automotive Perceptive Sensors in Foggy Conditions (se abrirá en una nueva ventana)

Autores: Amine Ben-Daoued; Pierre Duthon; Frédéric Bernardin
Publicado en: Journal of Imaging, 2023, ISSN 2313-433X
Editor: MDPI
DOI: 10.3390/jimaging9020054

Buscando datos de OpenAIRE...

Se ha producido un error en la búsqueda de datos de OpenAIRE

No hay resultados disponibles

Mi folleto 0 0