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arXiv · 2404.04040

Dynamic Risk Assessment Methodology with an LDM-based System for Parking Scenarios

Paola Natalia Cañas·Mikel García·Nerea Aranjuelo·Marcos Nieto·Aitor Iglesias·Igor Rodríguez
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Abstract

This paper describes the methodology for building a dynamic risk assessment for ADAS (Advanced Driving Assistance Systems) algorithms in parking scenarios, fusing exterior and interior perception for a better understanding of the scene and a more comprehensive risk estimation. This includes the definition of a dynamic risk methodology that depends on the situation from inside and outside the vehicle, the creation of a multi-sensor dataset of risk assessment for ADAS benchmarking purposes, and a Local Dynamic Map (LDM) that fuses data from the exterior and interior of the car to build an LDM-based Dynamic Risk Assessment System (DRAS).

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Paola Natalia Cañas, Mikel García, Nerea Aranjuelo, Marcos Nieto, Aitor Iglesias, Igor Rodríguez. 2024-04-05. Dynamic Risk Assessment Methodology with an LDM-based System for Parking Scenarios. https://doi.org/10.1109/itsc57777.2023.10422385

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