Dynamic Risk Assessment Methodology with an LDM-based System for Parking Scenarios
<|reference_start|>Dynamic Risk Assessment Methodology with an LDM-based System for Parking Scenarios: 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).<|reference_end|>
@article{cañas2024dynamic,
    title={Dynamic Risk Assessment Methodology with an LDM-based System for Parking
  Scenarios},
    author={Paola Natalia Ca~nas, Mikel Garc'ia, Nerea Aranjuelo, Marcos Nieto,
  Aitor Iglesias and Igor Rodr'iguez},
    journal={2023 IEEE 26th International Conference on Intelligent
  Transportation Systems (ITSC), Bilbao, Spain, 2023, pp. 5034-5039},
    year={2024},
    doi={10.1109/ITSC57777.2023.10422385},
    archivePrefix={arXiv},
    eprint={2404.04040},
    primaryClass={cs.CV cs.SY eess.SY}
}