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AdaV
Adaptive multimodal data fusion for object detection in adverse weather conditions for autonomous vehicles
FunderFrench National Research Agency (ANR)
Funder Contribution €259,802.00
DurationFrom 01 Jan 2025
Project codeANR-24-CE22-1244
Identifiers
Description
The AdaV project treats the issue of perception in complex environment and adverse meteorological conditions for autonomous vehicles. In fact, the lack of visibility due to bad weather is a challenging issue which hinders the safety of navigation in unknown and uncertain environments. For that, this project focuses on the use of conventional and nonconventional sensors to achieve dynamic object detection for road scene analysis. The main aim is to focus on sensor modeling by the estimation of its uncertainty and reliability in various atmospheric conditions (fog, snow, rain) with the use of a model-free approach and an evidential model. Providing a robust source model will lead to an adaptive evidential multimodal fusion according to the state of visibility in a road scene.
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The AdaV project treats the issue of perception in complex environment and adverse meteorological conditions for autonomous vehicles. In fact, the lack of visibility due to bad weather is a challenging issue which hinders the safety of navigation in unknown and uncertain environments. For that, this project focuses on the use of conventional and nonconventional sensors to achieve dynamic object detection for road scene analysis. The main aim is to focus on sensor modeling by the estimation of its uncertainty and reliability in various atmospheric conditions (fog, snow, rain) with the use of a model-free approach and an evidential model. Providing a robust source model will lead to an adaptive evidential multimodal fusion according to the state of visibility in a road scene.
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