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...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
TIB Open Publishing
2025-07-01
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| Series: | SUMO Conference Proceedings |
| Subjects: | |
| Online Access: | https://www.tib-op.org/ojs/index.php/scp/article/view/2590 |
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