Artificial Intelligence Application on Intelligent Transportation System
A special issue of Electronics (ISSN 2079-9292).
Deadline for manuscript submissions: 16 August 2024 | Viewed by 1371
Special Issue Editors
Interests: intelligent maintenance management of asphalt pavement; structural health monitoring; pavement distress detection based on computer vision; time series forecasting; building information modeling
Interests: ground-penetrating radar and nondestructive testing; signal and image processing; deep learning; Dempster-Shafer theory and uncertainty reasoning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Intelligent Transportation System (ITS) stands as a comprehensive and expansive transportation and management system, encompassing a multitude of domains. Its central focus lies in the intricate interplay between people, vehicles, and road infrastructure, harnessing the capabilities of information technology to elevate traffic efficiency and safety. As artificial intelligence (AI) technology continues to advance, the manifold applications of AI have made significant strides in enhancing the efficiency, safety, and sustainability of transportation networks within the ITS paradigm. AI has emerged as a pivotal force in addressing the intricate challenges posed by the future of urban transportation.
Amidst the myriad constituents of ITS, the ongoing trend towards the smartification of transportation infrastructure (including roads, bridges, tunnels, and more) and the relentless pursuit of autonomous driving technology in vehicles stand out as current focal points in ITS research. This Special Issue endeavors to compile the latest applications of artificial intelligence technology in both intelligent transportation infrastructure and autonomous driving. The topics covered include, but are not limited to:
(1) AI-based traffic infrastructure damage detection.
(2) AI-based traffic infrastructure structural health monitoring.
(3) AI-based traffic infrastructure digital twin and maintenance management.
(4) AI-based traffic infrastructure design and construction.
(5) AI-based autonomous driving perception and sensor fusion.
(6) AI-based autonomous driving path planning and decision making.
(7) AI-based autonomous driving vehicle control and optimization.
(8) AI-based intelligent transportation system environmental friendliness.
Dr. Chengjia Han
Dr. Zheng Tong
Guest Editors
Manuscript Submission Information
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Keywords
- intelligent transportation system
- artificial intelligence
- transport infrastructure
- digital twin
- autonomous driving
- pattern recognition
- sustainability
