Improving Simulation-Based Origin-Destination Demand Calibration Using Sample Segment Counts Data
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913709889159168 |
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| author | Alanqary, Arwa Zhang, Chao Li, Yechen Arora, Neha Osorio, Carolina |
| author_facet | Alanqary, Arwa Zhang, Chao Li, Yechen Arora, Neha Osorio, Carolina |
| contents | This paper introduces a novel approach to demand estimation that utilizes partial observations of segment-level track counts. Building on established simulation-based demand estimation methods, we present a modified formulation that integrates sample track counts as a regularization term. This approach effectively addresses the underdetermination challenge in demand estimation, moving beyond the conventional reliance on a prior OD matrix. The proposed formulation aims to preserve the distribution of the observed track counts while optimizing the demand to align with observed path-level travel times. We tested this approach on Seattle's highway network with various congestion levels. Our findings reveal significant enhancements in the solution quality, particularly in accurately recovering ground truth demand patterns at both the OD and segment levels. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_19528 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Improving Simulation-Based Origin-Destination Demand Calibration Using Sample Segment Counts Data Alanqary, Arwa Zhang, Chao Li, Yechen Arora, Neha Osorio, Carolina Emerging Technologies Systems and Control This paper introduces a novel approach to demand estimation that utilizes partial observations of segment-level track counts. Building on established simulation-based demand estimation methods, we present a modified formulation that integrates sample track counts as a regularization term. This approach effectively addresses the underdetermination challenge in demand estimation, moving beyond the conventional reliance on a prior OD matrix. The proposed formulation aims to preserve the distribution of the observed track counts while optimizing the demand to align with observed path-level travel times. We tested this approach on Seattle's highway network with various congestion levels. Our findings reveal significant enhancements in the solution quality, particularly in accurately recovering ground truth demand patterns at both the OD and segment levels. |
| title | Improving Simulation-Based Origin-Destination Demand Calibration Using Sample Segment Counts Data |
| topic | Emerging Technologies Systems and Control |
| url | https://arxiv.org/abs/2502.19528 |