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21 de may. de 2024 · where T represents the length of the time series that the target needs to be approximately, and n represents the length of the sequence of historical time series.. 3.3 Framework. The STBGRN model uses GCN to aggregate and capture the spatial dependence of the urban traffic network. Each road is represented by a point, traffic information on the road is described by the attributes of each node ...
Hace 2 días · This paper demonstrates accurate traffic modeling and forecast using stochastic cell-automata (CA) and distributed fiber-optic sensing (DFOS). Traffic congestion is a dominant issue in highways. To reduce congestion, real-time traffic control by short-term forecast is necessary. For achieving this, data assimilation using a stochastic CA model and DFOS is promising. Data assimilation with a CA ...
Hace 4 días · 1. In traditional research on the AGV scheduling problem, the computation time increases greatly with an increase in the number of AGVs and tasks. We introduce quantum computing technology into ...
23 de may. de 2024 · By deciphering patterns of movement within a city, stakeholders can craft targeted interventions to mitigate trafic congestion peaks, optimizing both resource allocation and individual travel routes. Focused on Barcelona, Spain, this paper draws on data sourced from the city council’s open data service.
24 de may. de 2024 · Through this localized adjustment capability, the LCF significantly enhances the precision and applicability of traffic models in urban traffic management, offering a more accurate and flexible tool for addressing the complex challenges of modern urban environments.
17 de may. de 2024 · to shared spaces, including pedestrian models, vehicle models, and shared space models. Categorization shows that traffic modeling can be separated into macroscopic (leveraging aggregate representations, e.g., [16]) and microscopic (depiction of individual agents, e.g., [8,10]) modeling.
24 de may. de 2024 · Overall traffic modeling is an increasingly complex field, with richer data making full use of available computing power even as that increases. “Better computers will make the simulation process much faster,” says Rydergren. “Taking the national forecasting model as an example, to run a single simulation takes 24 hours.
