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    <identifier>10.57760/sciencedb.j00133.00519</identifier>
    <datestamp>2025-12-02T16:51:51Z</datestamp>
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  <dc:date>2025-12-02</dc:date>
  <dc:title>The Vehicle Trajectory Data of Shenzhen</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.j00133.00519</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The study utilizes vehicle trajectory data from Shenzhen in August 2020, released by DiDi Chuxing for the ACM SIGSPATIAL GISCUP 2021 competition. The dataset contains over 8.6 million travel trajectories along with detailed road network topology information. To ensure experimental reliability while controlling the computational cost of spatio-temporal graph neural networks, we selected 20,000 high-frequency road segments during peak hours (7:00-23:00) to build a representative small-scale dataset for experimental analysis.</dc:description>
  <dc:subject>Trajectory Data; Peak Hours; High-Frequency Road Segments</dc:subject>
  <dc:creator>Hui Dong</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.3390/ijgi13120435</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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