Introduction to the Special Issue on Intelligent Transportation Systems Empowered by AI Technologiesopen access
- Authors
- Kong, Seung-Hyun; Lv, Yisheng; Vu, Hai L.; Cano, Juan-Carlos; Choi, Jun-Won; Kum, Dongsuk; Morris, Brendan Tran
- Issue Date
- Oct-2019
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Citation
- IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v.20, no.10, pp.3765 - 3770
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Volume
- 20
- Number
- 10
- Start Page
- 3765
- End Page
- 3770
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147026
- DOI
- 10.1109/TITS.2019.2940856
- ISSN
- 1524-9050
- Abstract
- There has been an increasing level of demand for faster, safer and greener transportation systems with higher levels of capacity and convenience, though the implementation of transportation systems overall is often restricted by geographical limitations, presenting a challenge to scientists and engineers in the field. However, we have been witnessing the evolution of the transportation systems over the last few decades, and at present we are facing a new era of intelligent transportation systems (ITS) empowered by artificial intelligence (AI) technologies. There have been classification, deep learning, and reinforcement learning techniques, to name a few, which collectively have enabled almost all technical elements of the ITS. For example, autonomous vehicle technologies are now mature enough to introduce self-driving cars, taxis, buses, and trucks on the roads and streets; traffic signals are controlled by AI-based systems for far more enhanced traffic efficiency; and machine learning based on big data is improving the operational performance of transportation systems to the next level of safety, efficiency, and sustainability.
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