Overcoming Data Scarcity in Calibrating SUMO Scenarios With Evolutionary Algorithms
Traffic simulations play a crucial role in urban planning and mobility management by providing insights into transportation systems. However, their effectiveness heavily depends on accurate demand calibration, often requiring large amounts of observational data. This poses a challenge in settings w...
| 出版年: | SUMO Conference Proceedings |
|---|---|
| 主要な著者: | , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
TIB Open Publishing
2025-07-01
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| 主題: | |
| オンライン･アクセス: | https://www.tib-op.org/ojs/index.php/scp/article/view/2590 |