data analysis; pattern clustering; public transport; road traffic; traffic engineering computing; visual databases; China; DBSCAN clustering method; LBS; Ripley K function; Wuhan City; average speed; city function zoning; congestion duration; congestion events clustering; congestion intensity distribution; congestion-prone areas; global aggregation degrees; local traffic condition; location based service; public travel choice; road network structure; spatial homogeneity; spatiotemporal correlations; spatiotemporal distribution; spatiotemporal patterns; taxi engine states; taxi trajectory data analysis; time-dependent traffic congestion patterns; traffic congestion regions; traffic control; trajectory data field; trajectory potential; trajectory sequences; urban planning; urban traffic congestion; visualization; Cities and towns; Distribution functions; Graphical models; Public transportation; Roads; Spatiotemporal phenomena;
机译:使用出租车的GPS轨迹数据进行转弯处的交通拥堵分析
机译:基于出租车GPS感知数据的城市经常性交通拥堵空间格局分析的网格映射
机译:基于出租车GPS感知数据的城市经常性交通拥堵空间格局分析的网格映射
机译:从滑行轨迹数据探索时间相关的交通拥堵模式
机译:北京出租车如何工作? GPS数据时空出租车行驶模式的探索性研究
机译:超越通勤:忽略个人的活动-出行方式可能会导致对交通拥堵暴露的评估不准确
机译:基于出租车Gps传感数据的城市交通拥堵空间格局分析