针对海量浮动车数据特点和快速处理要求,提出了一种基于矢量道路地图栅格化的海量浮动车数据方法,该算法的关键是矢量道路栅格化过程中包括了道路缓冲区和属性信息。道路缓冲区的宽度由一个与浮动车数据位置误差和道路宽度相关的置信区域决定;矢量道路缓冲区转换成栅格图后,栅格图中像素的位置对应着实际地理坐标,而像素值的灰度值表示道路的等级、名称、编号等属性或方向等信息;然后将海量浮动车数据与栅格道路地图进行叠加处理。这种方法不仅可以精确地计算出城市道路地图坐标系与浮动车数据坐标系之间的变换参数,而且还能够快速地获取区域路网以及特定道路的行驶速度。最后,通过超过一千万个真实的武汉市浮动车数据,并与经典的浮动车数据处理算法进行比较,验证了矢量道路栅格化方法处理海量浮动车数据的可行性和有效性。
A method for quickly extracting road traveling speeds from huge number of floating car data was proposed based on vector road map rasterization.The key component of the method is to convert vector road data to raster data based on buffer and attributes of road sections.The width of a road buffer was constructed based on a distance confidence region by taking into account the position errors of floating car data and width of road.Then all roads buffer were converted to raster map,in which pixel position corresponds to geographical position,and grey scale of pixel value represents attributes of vector road such as hierarchy,name,number or direction.After that,huge volume of floating car data and road network raster map was overlapped.Hence not only accurate coordinate transformation parameters between floating car data and urban road map can be easily calculated,but also road networks and special roads traveling speed can be quickly extracted.Finally,the feasibility and effectiveness of this method were examined by comparing with traditional floating car data process algorithms using more than 10 millions of real floating car data of Wuhan City.