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

Fuente: arXiv
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Autori principali: Fu, Yongjie, Turkcan, Mehmet K., Ghasemi, Mahshid, Mo, Zhaobin, Zang, Chengbo, Adhikari, Abhishek, Kostic, Zoran, Zussman, Gil, Di, Xuan
Natura: Preprint
Pubblicazione: 2024
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author Fu, Yongjie
Turkcan, Mehmet K.
Ghasemi, Mahshid
Mo, Zhaobin
Zang, Chengbo
Adhikari, Abhishek
Kostic, Zoran
Zussman, Gil
Di, Xuan
author_facet Fu, Yongjie
Turkcan, Mehmet K.
Ghasemi, Mahshid
Mo, Zhaobin
Zang, Chengbo
Adhikari, Abhishek
Kostic, Zoran
Zussman, Gil
Di, Xuan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2501_10396
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications
Fu, Yongjie
Turkcan, Mehmet K.
Ghasemi, Mahshid
Mo, Zhaobin
Zang, Chengbo
Adhikari, Abhishek
Kostic, Zoran
Zussman, Gil
Di, Xuan
Systems and Control
Artificial Intelligence
Computers and Society
Networking and Internet Architecture
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.
title AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications
topic Systems and Control
Artificial Intelligence
Computers and Society
Networking and Internet Architecture
url https://arxiv.org/abs/2501.10396