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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.04688 |
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| _version_ | 1866929410794323968 |
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| author | Qiu, Mei Lin, Wei Chien, Stanley Christopher, Lauren Chen, Yaobin Hu, Shu |
| author_facet | Qiu, Mei Lin, Wei Chien, Stanley Christopher, Lauren Chen, Yaobin Hu, Shu |
| contents | Vehicle weaving on highways contributes to traffic congestion, raises safety issues, and underscores the need for sophisticated traffic management systems. Current tools are inadequate in offering precise and comprehensive data on lane-specific weaving patterns. This paper introduces an innovative method for collecting non-overlapping video data in weaving zones, enabling the generation of quantitative insights into lane-specific weaving behaviors. Our experimental results confirm the efficacy of this approach, delivering critical data that can assist transportation authorities in enhancing traffic control and roadway infrastructure. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_04688 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enhancing Vehicle Re-identification and Matching for Weaving Analysis Qiu, Mei Lin, Wei Chien, Stanley Christopher, Lauren Chen, Yaobin Hu, Shu Computer Vision and Pattern Recognition Vehicle weaving on highways contributes to traffic congestion, raises safety issues, and underscores the need for sophisticated traffic management systems. Current tools are inadequate in offering precise and comprehensive data on lane-specific weaving patterns. This paper introduces an innovative method for collecting non-overlapping video data in weaving zones, enabling the generation of quantitative insights into lane-specific weaving behaviors. Our experimental results confirm the efficacy of this approach, delivering critical data that can assist transportation authorities in enhancing traffic control and roadway infrastructure. |
| title | Enhancing Vehicle Re-identification and Matching for Weaving Analysis |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2407.04688 |