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| 主要な著者: | , , |
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| フォーマット: | Recurso digital |
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Zenodo
2025
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| 主題: | |
| オンライン･アクセス: | https://doi.org/10.5281/zenodo.17062007 |
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| _version_ | 1866902257129226240 |
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| author | Chauhan, Prashant GOEL, SALIL Winter, Stephan |
| author_facet | Chauhan, Prashant GOEL, SALIL Winter, Stephan |
| contents | <p><span>The strategic placement of on-street parking spaces critically impacts urban traffic flow and parking efficiency, yet conventional approaches often rely on reactive policies and macroscopic models that overlook nuanced traffic interactions. This study proposes a novel impact-driven, multi-criteria decision-making framework. It applies microscopic traffic simulation to evaluate candidate parking locations based on their effects on both local and through traffic. By explicitly distinguishing these impacts, the paper captures spatiotemporal dynamics overlooked so far. The paper quantifies changes in key criteria (travel time, search time, walk time) and systematically ranks parking alternatives using a combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Results highlight that strategic placement can significantly reduce cruising times and congestion without imposing excessive walking burdens. The framework offers a transferable and adaptable decision-support tool for urban planners, with potential applications extending to event planning and autonomous vehicle navigation.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17062007 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Impact-Driven Multi-Criteria Decision Approach for Strategic On-Street Parking Placement Chauhan, Prashant GOEL, SALIL Winter, Stephan Parking placement multicriteria decision making microscopic simulation sumo urban traffic management <p><span>The strategic placement of on-street parking spaces critically impacts urban traffic flow and parking efficiency, yet conventional approaches often rely on reactive policies and macroscopic models that overlook nuanced traffic interactions. This study proposes a novel impact-driven, multi-criteria decision-making framework. It applies microscopic traffic simulation to evaluate candidate parking locations based on their effects on both local and through traffic. By explicitly distinguishing these impacts, the paper captures spatiotemporal dynamics overlooked so far. The paper quantifies changes in key criteria (travel time, search time, walk time) and systematically ranks parking alternatives using a combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Results highlight that strategic placement can significantly reduce cruising times and congestion without imposing excessive walking burdens. The framework offers a transferable and adaptable decision-support tool for urban planners, with potential applications extending to event planning and autonomous vehicle navigation.</span></p> |
| title | Impact-Driven Multi-Criteria Decision Approach for Strategic On-Street Parking Placement |
| topic | Parking placement multicriteria decision making microscopic simulation sumo urban traffic management |
| url | https://doi.org/10.5281/zenodo.17062007 |