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

@Article {
author = {Cañas, Paola Natalia},
title = {Dynamic Risk Assessment Methodology with an LDM-Based System for Parking Scenarios},
pages = {7},
keywds = {
Advanced driver assistance systems; Automobile drivers; Risk perception
}
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).

}
isbn = {979-835039946-2},
date = {2023-09-24},
}