A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approa...A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.展开更多
目的:观察老年人肘关节位置觉的重测信度。方法:应用Biodex System 4 pro型等速测试系统测试20例健康老年人双侧肘关节位置觉(采用主动位置重现和被动位置重现测试法),由2名测试者负责重复测试,前后2次测试时间间隔一周,使用组内相关系...目的:观察老年人肘关节位置觉的重测信度。方法:应用Biodex System 4 pro型等速测试系统测试20例健康老年人双侧肘关节位置觉(采用主动位置重现和被动位置重现测试法),由2名测试者负责重复测试,前后2次测试时间间隔一周,使用组内相关系数(intraclass correlation coefficient,ICC)对所得结果进行信度分析。结果:受试者在肘关节屈曲15°、屈曲45°和屈曲75°时,其主动位置重现绝对误差角度的重测信度ICC值分别为0.899、0.879和0.869,被动位置重现绝对误差角度的重测信度分别为0.894、0.863和0.882;主动位置重现的绝对误差角度小于被动位置重现。结论:采用Biodex等速测试系统中主动位置重现和被动位置重现测试法对老年人肘关节位置觉进行重复测试时,ICC值为0.863～0.899,提示老年人肘关节位置觉重测的相关性良好。展开更多
The paper aims to challenge non-GPS navigation problems by using visual sensors and geo-referenced images. An area-based method is proposed to estimate full navigation parameters(FNPs), including attitude, altitude an...The paper aims to challenge non-GPS navigation problems by using visual sensors and geo-referenced images. An area-based method is proposed to estimate full navigation parameters(FNPs), including attitude, altitude and horizontal position, for unmanned aerial vehicle(UAV) navigation. Our method is composed of three main modules: geometric transfer function, local normalized sobel energy image(LNSEI) based objective function and simplex-simulated annealing(SSA) based optimization algorithm. The adoption of relatively rich scene information and LNSEI, makes it possible to yield a solution robustly even in the presence of very noisy cases, such as multi-modal and/or multi-temporal images that differ in the type of visual sensor, season, illumination, weather, and so on, and also to handle the sparsely textured regions where features are barely detected or matched. Simulation experiments using many synthetic images clearly support noise resistance and estimation accuracy, and experimental results using 2367 real images show the maximum estimation error of 5.16(meter) for horizontal position, 9.72(meter) for altitude and 0.82(degree) for attitude.展开更多
基金Project(90820302) supported by the National Natural Science Foundation of China
文摘A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.
文摘The paper aims to challenge non-GPS navigation problems by using visual sensors and geo-referenced images. An area-based method is proposed to estimate full navigation parameters(FNPs), including attitude, altitude and horizontal position, for unmanned aerial vehicle(UAV) navigation. Our method is composed of three main modules: geometric transfer function, local normalized sobel energy image(LNSEI) based objective function and simplex-simulated annealing(SSA) based optimization algorithm. The adoption of relatively rich scene information and LNSEI, makes it possible to yield a solution robustly even in the presence of very noisy cases, such as multi-modal and/or multi-temporal images that differ in the type of visual sensor, season, illumination, weather, and so on, and also to handle the sparsely textured regions where features are barely detected or matched. Simulation experiments using many synthetic images clearly support noise resistance and estimation accuracy, and experimental results using 2367 real images show the maximum estimation error of 5.16(meter) for horizontal position, 9.72(meter) for altitude and 0.82(degree) for attitude.
