UMR CNRS 7253

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en:research [2019/06/27 14:07] – [ESCAPE Project] xuphilipen:research [2019/06/27 14:08] – [PRETIV Project] xuphilip
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 The GNSS receiver in the ESCAPE engine will feature multi-constellation, multi-frequency capabilities and will be enabled to receive and process the upcoming **Galileo OS authenticated signals**, which is one of the key differentiators of the European GNSS, expected to be broadcast starting form 2018. The GNSS receiver in the ESCAPE engine will feature multi-constellation, multi-frequency capabilities and will be enabled to receive and process the upcoming **Galileo OS authenticated signals**, which is one of the key differentiators of the European GNSS, expected to be broadcast starting form 2018.
  
-{{ :en:infographics_background_top_v4.png?400 |}}+{{ :en:infographics_background_top_v4.png?500 |}}
 ====== TORNADO Project ====== ====== TORNADO Project ======
 **__Autonomous vehicles and infrastructure interactions for mobility services in lightly populated zones__**\\ **__Autonomous vehicles and infrastructure interactions for mobility services in lightly populated zones__**\\
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   * Cross-experiments and comparative studies are to be conducted in real transnational traffic situations (France and China) by implementing the jointly developed core algorithms on two different test-bed vehicles of the partners, which will permit cross-fertilization of sensing techniques between the three research groups;   * Cross-experiments and comparative studies are to be conducted in real transnational traffic situations (France and China) by implementing the jointly developed core algorithms on two different test-bed vehicles of the partners, which will permit cross-fertilization of sensing techniques between the three research groups;
   * A comparative dataset containing the experimental data, labeled training sets in typical traffic scenarios in both France and China with ground-truth, which will be used in learning country-specific traffic semantics, and will be opened to public to promote comparative researches on transnational traffic semantics and behaviors. To our knowledge, no such dataset has been proposed for international use.   * A comparative dataset containing the experimental data, labeled training sets in typical traffic scenarios in both France and China with ground-truth, which will be used in learning country-specific traffic semantics, and will be opened to public to promote comparative researches on transnational traffic semantics and behaviors. To our knowledge, no such dataset has been proposed for international use.
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 ====== PREDiMAP Project ====== ====== PREDiMAP Project ======

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en/research.txt · Last modified: 2021/11/28 15:04 by xuphilip
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