1故障现象一辆一汽大众2010年8月出厂的奥迪A6L-2.8FSI,行驶里程为80 200 km,发动机型号CCEA,功率162 k W。右前照灯中的日间行车LED灯不亮,仪表显示灯光报警。2故障诊断及排除连接大众诊断仪6160,故障码：02746右侧日间行驶灯对搭铁短...1故障现象一辆一汽大众2010年8月出厂的奥迪A6L-2.8FSI,行驶里程为80 200 km,发动机型号CCEA,功率162 k W。右前照灯中的日间行车LED灯不亮,仪表显示灯光报警。2故障诊断及排除连接大众诊断仪6160,故障码：02746右侧日间行驶灯对搭铁短路。根据数据流分析：1右前日间行驶灯泡断开;2左前日间行驶灯泡接通。展开更多
To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transfo...To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.展开更多
文摘1故障现象一辆一汽大众2010年8月出厂的奥迪A6L-2.8FSI,行驶里程为80 200 km,发动机型号CCEA,功率162 k W。右前照灯中的日间行车LED灯不亮,仪表显示灯光报警。2故障诊断及排除连接大众诊断仪6160,故障码：02746右侧日间行驶灯对搭铁短路。根据数据流分析：1右前日间行驶灯泡断开;2左前日间行驶灯泡接通。
基金The Cultivation Fund of the Key Scientific and Technical Innovation Project of Higher Education of Ministry of Education (No.705020)
文摘To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.
