en:research
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| en:research [2019/06/27 14:08] – [ESCAPE Project] xuphilip | en:research [2019/06/27 14:13] – [PREDiMAP Project] xuphilip | ||
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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, | * A comparative dataset containing the experimental data, labeled training sets in typical traffic scenarios in both France and China with ground-truth, | ||
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| ====== PREDiMAP Project ====== | ====== PREDiMAP Project ====== | ||
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| The objective of the project is to gather research teams from China, Japan, Thailand and France with complementary skills and expertise to conduct research in the area of advanced perception systems for intelligent vehicles making a large use of digital maps. The partnership will benefit from different experiences in the fields of embedded perception systems for intelligent vehicles, digital geographic and road map information production and use, and more generally spatial information sciences. The originality of the project is to fully consider the dual concept for intelligent vehicle applications: | The objective of the project is to gather research teams from China, Japan, Thailand and France with complementary skills and expertise to conduct research in the area of advanced perception systems for intelligent vehicles making a large use of digital maps. The partnership will benefit from different experiences in the fields of embedded perception systems for intelligent vehicles, digital geographic and road map information production and use, and more generally spatial information sciences. The originality of the project is to fully consider the dual concept for intelligent vehicle applications: | ||
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en/research.txt · Last modified: 2021/11/28 15:04 by xuphilip
