A-TEAM: Advanced Traffic Event Analysis and Management Platform for Transportation Data-Driven Problem Solving
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866929395222970368 |
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| author | Bian, Zilin Zuo, Dachuan Gao, Jingqin Ozbay, Kaan Maggio, Matthew D. |
| author_facet | Bian, Zilin Zuo, Dachuan Gao, Jingqin Ozbay, Kaan Maggio, Matthew D. |
| contents | The rapid growth in terms of the availability of transportation data provides great potential for the introduction of emerging data-driven methodologies into transportation-related research and development efforts. However, advanced data-driven models, such as artificial-intelligence based approaches, usually contain complicated modeling structures and require strict data formats along with a very complex execution environment. It is thus often challenging to deploy and implement such data-driven models in a real-world environment. Moreover, a full-fledged application requires not only well developed and calibrated models, but also efficient connections with back end infrastructure such as large databases and front end utilities, such as a user-interface. This paper introduces a novel platform which provides an integrated architecture for deploying multi-purpose real-time traffic management applications. Inspired by the concept of modular design in software system development, this paper proposes a modular platform allowing users to customize their mission specific needs and preferences. The developed platform is capable of incorporating flexible user-provided models and/or data with the ultimate goal of deploying them as a complete application ready for real-world use. To illustrate this novel modular software system concept, this paper presents a work zone management and coordination application that is built upon the developed implementation platform to provide useful decision support to traffic engineers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_15452 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A-TEAM: Advanced Traffic Event Analysis and Management Platform for Transportation Data-Driven Problem Solving Bian, Zilin Zuo, Dachuan Gao, Jingqin Ozbay, Kaan Maggio, Matthew D. Physics and Society The rapid growth in terms of the availability of transportation data provides great potential for the introduction of emerging data-driven methodologies into transportation-related research and development efforts. However, advanced data-driven models, such as artificial-intelligence based approaches, usually contain complicated modeling structures and require strict data formats along with a very complex execution environment. It is thus often challenging to deploy and implement such data-driven models in a real-world environment. Moreover, a full-fledged application requires not only well developed and calibrated models, but also efficient connections with back end infrastructure such as large databases and front end utilities, such as a user-interface. This paper introduces a novel platform which provides an integrated architecture for deploying multi-purpose real-time traffic management applications. Inspired by the concept of modular design in software system development, this paper proposes a modular platform allowing users to customize their mission specific needs and preferences. The developed platform is capable of incorporating flexible user-provided models and/or data with the ultimate goal of deploying them as a complete application ready for real-world use. To illustrate this novel modular software system concept, this paper presents a work zone management and coordination application that is built upon the developed implementation platform to provide useful decision support to traffic engineers. |
| title | A-TEAM: Advanced Traffic Event Analysis and Management Platform for Transportation Data-Driven Problem Solving |
| topic | Physics and Society |
| url | https://arxiv.org/abs/2406.15452 |