LatenAux: Toward latency-aware trajectory prediction for autonomous driving via consolidated auxiliary learning
Accurate trajectory forecasting is essential for enabling autonomous vehicles to navigate safely in complex traffic environments. Current models typically assume that predictions are latency-free, an idealistic simplification that fails in real-world settings, where processing, computation, and tran...
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| 主要な著者: | , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Tsinghua University Press
2026-03-01
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| シリーズ: | Communications in Transportation Research |
| 主題: | |
| オンライン･アクセス: | https://www.sciopen.com/article/10.26599/COMMTR.2026.9640010 |
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