Research On Safe Distance Measuring Method Of Front Vehicle In Foggy Environment

With the rapid development of China's industry,environmental protection issues have received widespread attention.Increasingly serious air pollution and frequent fog weather have severely affected people's lives.At this stage,China's economy as well as science and technology are in a period of rapid development,more and more people choose cars as a means of transportation,which provide convenience to people,but also increase the risk of traffic accidents.Furthermore the probability of traffic accident is increased in foggy environment.Therefore,the safety problem of driving in foggy environment needs to be solved urgently.In order to effectively reduce the occurrence of traffic accidents in foggy environment,this thesis proposes a method for measuring the safe distance of the front vehicle based on vehicle video in foggy environment.The method of tracking vehicles and measuring distance based on vehicle video are not only at low cost and good real-time,but also easier to install.It is an important research field of intelligent transportation assistant driving.In this thesis,the main road environment is structured roads such as urban roads or highways,and the safetly distance with the front vehicle is obtained through vehicle video.Existing fog removal algorithms are difficult to achieve engineering applications on traffic roads due to poor image contrast and high complexity.In this thesis,firstly,we reviewed the privous studies on visibility and fog image degradation model,and collected the visibility calculation of the fog road image.Based on the dark primary channel,we collected image segmentation of the fog image according to visibility.And the atmospheric light value is estimated in the sky area.According to the relevant features of the traffic image,different degrees of fog removal were performed on the segmented image regions.It can retain the edge color details of the original image,then complete the clear processing of foggy images.Secondly,the Edge Drawing algorithm is used for edge detection of the fog removal image,which can effectively extract the required information in the region of interest of the image.Finally,the improved Hough transform is used for detect the edge information of the front vehicle tail.And the distance to the front vehicle can be measured in real-time with the help of the distance measurement model in the circumstance of ensured vehicle recognition and tracking.In order to real-time system processing,this thesis uses a dual-core processing system of DSP and FPGA.And hardware circuits were designed,the circuit board was drawn and welded.The video images actually captured by the vehicle video are further verified through the corresponding algorithm.Under the premise of the Matlab software simulation,the algorithm transplantation was completed based on the hardware platform.The results of laboratory verification show that the accuracy of the measurement of the distance with the front vehicle can be improved under low visibility conditions,and the method has the advantage of high real-time performance and practical engineering significance.