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Dynamic Risk Assessment Methodology with an LDM-based System for Parking Scenarios
- Source :
- 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain, 2023, pp. 5034-5039
- Publication Year :
- 2024
-
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).
Details
- Database :
- arXiv
- Journal :
- 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain, 2023, pp. 5034-5039
- Publication Type :
- Report
- Accession number :
- edsarx.2404.04040
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1109/ITSC57777.2023.10422385