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Conference Papers Year : 2017

Embedded Bayesian Percpetion and V2X Communication for Autnomous Driving

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Abstract

This talk presents the technologies developed by the Inria Chroma team to robustly perceive and interpret dynamic environments using Bayesian systems (such as BOF, HSBOF, and CMCDOT) relying on embedded sensors input and V2X communications (vehicle to vehicle and vehicle to infrastructure). These technologies have initially been developed in collaboration with the IRT nanoelec and with industrial partners such as Toyota, Renault, or Probayes SA, with the objective to extend the capabilities of current Advanced Driving Assistance Systems (including autonomous driving functionalities). The technology is also currently transferred to an industrial mobile robots company (EasyMile and BA Systems). We show how heterogeneous sensors can be used efficiently, merged, and filtered in real time into probabilistic grids, and how collision risks can be computed in an optimized way on embedded GPUs, NVIDIA Jetson Tegra X1. The perception of the environment can also be distributed between connected cars and perception units using V2X protocols.
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Dates and versions

hal-01672113 , version 1 (23-12-2017)

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  • HAL Id : hal-01672113 , version 1

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Christian Laugier. Embedded Bayesian Percpetion and V2X Communication for Autnomous Driving. GPU Technology Conference - GTC 2017, May 2017, San Jose, California, United States. ⟨hal-01672113⟩
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