In this work, we propose LargeST as a new benchmark dataset (see Figure 1), with the goal of facilitating the development of accurate and efficient methods in the context of large-scale traffic forecasting. The distinguishing characteristic of LargeST lies not only in its extensive graph size, encompassing a total of 8,600 sensors in California, but also in its substantial temporal coverage and rich node information – each sensor contains 5 years of data and comprehensive metadata.
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The Beijing Traffic Dataset collects traffic speeds at 5-minute granularity for 3126 roadway segments in Beijing between 2022/05/12 and 2022/07/25.
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VLUC (Video-Like Urban Computing) is a benchmark for video-like computing on citywide traffic density and crowd prediction. It consists of two new datasets BousaiTYO and BousaiOSA and existing datasets TaxiBJ, BikeNYC I-II, and TaxiNYC.
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