mlsanityData to 7 Oct 2026

AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications

arXiv 2501.10396 ↗First posted 30 Dec 2024eess.SY cs.AI cs.CYcited by 1

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Abstract (arXiv)

We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on the DT focus on its ``eyes," which is the emerging sensing and perception like object detection and tracking, what really distinguishes the DT from a traditional simulator lies in its ``brain," the prediction and decision making capabilities of extracting patterns and making informed decisions from what has been seen and perceived. In order to add value to urban transportation management, DTs need to be powered by artificial intelligence and complement with low-latency high-bandwidth sensing and networking technologies, in other words, cyberphysical systems. This paper can be a pointer to help researchers and practitioners identify challenges and opportunities for the development of DTs; a bridge to initiate conversations across disciplines; and a road map to exploiting potentials of DTs for diverse urban transportation applications.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 107 of its 271 references that are in the map. First posted on arXiv 30 Dec 2024.

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107 of 271 references.

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Citing papers per year: 2026: 1.

1 paper.

  1. 2026Multi-Pedestrian Safety Warning at Urban Intersections Use Case of Digital Twincited by 0