路面不平度的分形特征

Fractal behavior of road profile roughness

利用激光式不平度测试仪测定了混凝土路面、砖路面、土路面的不平度,采用均方根法计算了3种路面的分形维数,分别为1.845,1.689和1.561.结果表明:分形维数越大,则轮廓曲线越复杂,充满空间的能力也越强,细节越丰富;而分形维数越小,则细节越少.提出了路面不平度指数的概念,路面不平度指数具有描述路面不平度的唯一性,是路面分级的主要指标之一.3种路面的路面不平度指数相差很大,分别是:混凝土路面为1.237,砖路面为3.435,而土路面达14.610.

By using a laser profiler, the surface height variations of three types of road, concrete, brick and soil roads, were obtained. Fractal dimensions of three types of road profile roughness were calculated by root mean square method, which were 1. 845, 1. 689 and 1. 561, respectively. The results showed that the road surface gives irregular performance and statistical self-similarity, which means that each portion can be considered as a reduced-scale image of the whole. A higher fractal dimension means a more complex road surface profile, and thus a unit area is more extensively covered by the profile curve. On the contrary, a lower fractal dimension presents only a limited amount of details. The concept of road roughness index was proposed in order to evaluate the quantification of road roughness. Road surface roughness index is defined as a combinative parameter of fractal dimension and root mean square deviation of road surface profile. Such a definition exhibits a unique performance when applied to quantify road surface roughness. Differences among three contrasting road types were found to be great, indicating a fractal dimension of 1. 237, 3. 435 and 14. 610, respectively, for concrete, brick and soil road.