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HORIZON-CL5-2021-D6-01-01
HORIZON-CL5-2021-D6-01-01: More powerful and reliable on-board perception and decision-making technologies addressing complex environmental conditions (CCAM Partnership)
ExpectedOutcome:Project results are expected to contribute to all of the following expected outcomes:
Sólo fondo perdido 0 €
Europeo
Esta convocatoria está cerrada Esta línea ya está cerrada por lo que no puedes aplicar. Cerró el pasado día 19-10-2021.
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ExpectedOutcome:Project results are expected to contribute to all of the following expected outcomes:

Determination of the appropriate compositions of cost-efficient sensor suites that most effectively and reliably deliver the lateral, spatial and temporal resolution needed for real-time driving decision-making of Connected and Automated Vehicles (CAVs).Ability to perform advanced environment and traffic recognition and prediction, limiting false detections and non-detections of obstacles, with particular attention to Vulnerable Road Users (VRU), in order to reduce existing disparities in the harm-to-exposure ratios of these vulnerable groups.Ability to determine the appropriate course of action of a CAV in a real world environment with a wide range of traffic scenarios and identify use cases in which the vehicle’s decision-making might be contradictory to existing traffic rules (e.g. to make way for a priority vehicle, to obey police officers directing traffic).Availability of robust, transparent and accurate systems to enable the safe and reliable operation of automated vehicles in expanding Operational Design Domains (ODDs) including all weather conditions, complex... ver más

ExpectedOutcome:Project results are expected to contribute to all of the following expected outcomes:

Determination of the appropriate compositions of cost-efficient sensor suites that most effectively and reliably deliver the lateral, spatial and temporal resolution needed for real-time driving decision-making of Connected and Automated Vehicles (CAVs).Ability to perform advanced environment and traffic recognition and prediction, limiting false detections and non-detections of obstacles, with particular attention to Vulnerable Road Users (VRU), in order to reduce existing disparities in the harm-to-exposure ratios of these vulnerable groups.Ability to determine the appropriate course of action of a CAV in a real world environment with a wide range of traffic scenarios and identify use cases in which the vehicle’s decision-making might be contradictory to existing traffic rules (e.g. to make way for a priority vehicle, to obey police officers directing traffic).Availability of robust, transparent and accurate systems to enable the safe and reliable operation of automated vehicles in expanding Operational Design Domains (ODDs) including all weather conditions, complex urban environments, challenges in rural environments, etc.Standardization mandate for performance requirements for environment perception systems with respect to different automation levels and ODDs.
Scope:To achieve secure and trustworthy interaction between vehicles, infrastructure and road users, robust (e.g. weather resilient) and accurate on-board environment positioning and perception systems are essential for the extraction of reliable information required for real-time driving decision-making. Furthermore, advanced on-board decision-making functionalities need to handle the diversity of use cases in their respective operational domains. Such functionalities have to guarantee the safety and reliability of future automated vehicles, which will integrate complex in-vehicle systems-of-systems with advanced sensors, control and actuators, relying on extensive computational power and an increased dependency on software for decision-making.

The proposed actions are expected to address the development and demonstration of each of the following aspects:

More powerful and reliable embedded in-vehicle perception systems with increased performance, (weather) resilience and accuracy based on enhanced sensing, localization (with reliable, dynamic, high-definition digital maps, reliable and precise location from EU satellite navigation services) and improved object/person classification and cognition (with greater integration with infrastructure-based perception systems and other vehicles to complete data fusion and real time updates). System self-assessment methods for environment perception technologies and improved hardware integration into the vehicle need also to avoid reliability issues due to environmental stresses, temperature shifts, vibrations, potential malicious attacks, low speed crashes, etc.On-board, real-time, fail-safe, unambiguous and traceable decision-making systems for safe Connected and Automated Vehicles (CAVs) based on complex in-vehicle systems-of-systems requiring extensive computational power and highly advanced algorithms in order to address complex traffic scenarios (with VRU). These systems should be cost effective and respecting the protection of personal data with improved minimum risk manoeuvres in the event that the limit of the ODD is reached or in the case of a malfunction. In order to achieve the expected outcomes, international cooperation is advised, in particular with projects or partners from the US, Japan, Canada, South Korea, Singapore, Australia.

This topic implements the co-programmed European Partnership on ‘Connected, Cooperative and Automated Mobility’ (CCAM).


Specific Topic Conditions:Activities are expected to achieve TRL 6-7 by the end of the project – see General Annex B.




Cross-cutting Priorities:Co-programmed European PartnershipsInternational Cooperation


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Temáticas Obligatorias del proyecto: Temática principal:

Características del consorcio

Ámbito Europeo : La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Tipo y tamaño de organizaciones: El diseño de consorcio necesario para la tramitación de esta ayuda necesita de:

Características del Proyecto

Requisitos de diseño: Duración:
Requisitos técnicos: ExpectedOutcome:Project results are expected to contribute to all of the following expected outcomes: ExpectedOutcome:Project results are expected to contribute to all of the following expected outcomes:
¿Quieres ejemplos? Puedes consultar aquí los últimos proyectos conocidos financiados por esta línea, sus tecnologías, sus presupuestos y sus compañías.
Capítulos financiables: Los capítulos de gastos financiables para esta línea son:
Personnel costs.
Subcontracting costs.
Purchase costs.
Other cost categories.
Indirect costs.
Madurez tecnológica: La tramitación de esta ayuda requiere de un nivel tecnológico mínimo en el proyecto de TRL 6:. Representa un paso importante en demostrar la madurez de una tecnología. Se construye un prototipo de alta fidelidad que aborda adecuadamente las cuestiones críticas de escala, que opera en un entorno relevante, y que debe ser a su vez una buena representación del entorno operativo real. + info.
TRL esperado:

Características de la financiación

Intensidad de la ayuda: Sólo fondo perdido + info
Fondo perdido:
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Para el presupuesto subvencionable la intensidad de la ayuda en formato fondo perdido podrá alcanzar desde un 70% hasta un 100%.
The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities. The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities.
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Información adicional de la convocatoria

Efecto incentivador: Esta ayuda no tiene efecto incentivador. + info.
Respuesta Organismo: Se calcula que aproximadamente, la respuesta del organismo una vez tramitada la ayuda es de:
Meses de respuesta:
Muy Competitiva:
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