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Aug 17, 2022 · How technology can help make urban transport work for people. A data-driven approach helps Lynette Cheah to tackle concerns about self-driving buses and delivery-truck congestion. By. Andy Tay....
- Andy Tay
Sep 13, 2017 · Summary. The shift to next-generation mobility systems won’t be easy for cities to manage. Some cities have chosen a wait-and-see approach, opting to watch mobility trends and develop...
Apr 24, 2024 · Advances toward technology-enabled transport. The application of AI in transport has been growing significantly. As of this writing, typical use cases include autonomous vehicles, drones ...
Jun 3, 2023 · This survey paper explores the landscape of Intelligent Urban Transportation Systems (IUTS) by analyzing AI-driven innovations and forecasting future directions.
Urban transportation refers to the movement of people and goods within a city or urban area. It is an important aspect of the urban system, impacting the liveability of the city and the well-being of its residents.
Typical examples include using AI such as deep neuron networks (DNN) to predict urban road traffic, and using computer vision technologies to detect the road objects for autonomous driving. The focus of such research is mainly on increasing the accuracy of traffic prediction and object detection within strict time frames.
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May 20, 2021 · Data-driven technologies make it possible not only to integrate urban systems and coordinate urban domains, but also to couple urban networks in order to improve land use, focus urban development, optimize resource utilization, reduce operational costs, and streamline urban processes.
