Research On The Signs Classification System On The Basis Of Traffic Safety Of Sparse Road Network

According to the special environment in Xin Jiang province and relevant national standard,this thesis clarify the formation,principle and points of the traffic signs of sparse road network and proceed a field research for current situation of road traffic signs of sparse road network and summarize the features of the road traffic signs in this region for Xinjiang Uygur Autonomous Region as an example.This thesis analyze the relationship between the traffic safety of sparse road network and road traffic signs and put on the traffic signs can control and manage the traffic safety according to different elements of sparse road network traffic system.We build the new model of road traffic signs control traffic safety use the people-automobile-road-environment elements of sparse road network safety system to providing the reference and basis for signs set of road traffic in this region.We significantly define and systematic the guide sign information elements and quantitatively classify the different levels intersection notice and inform logo for the different level sparse road network in Xinjiang province,at last we research optimizing settings on the basis of sparse road network.For the roads in Xinjiang province have winds,blizzards,complicated weather in winter and rain,snow and fog in some areas are alternating appear and Gobi desert region are widely distributed,many long straight sections are located in special geographical environment,we deeply analyze the reasons of relative traffic accidents and research the special road signs system.Combining sparse road network road traffic signs,special environment of road traffic with setting methods of traffic signs,we provide some advices about setting methods of traffic signs according to the example of development situation of sparse road network in Xinjiang and the change of the pre-road traffic signs in Xinjiang at last,those advices can be used as a reference of road traffic signs set of sparse road network and in the future.