During predation, a flying insect can form a stealth flight path. This behavior is called motion camouflage. Based on the study results of this behavior, the perception and neurology of flying insects, a novel bio-ins...During predation, a flying insect can form a stealth flight path. This behavior is called motion camouflage. Based on the study results of this behavior, the perception and neurology of flying insects, a novel bio-inspired guidance law is proposed for the terminal guidance for small aerial vehicle with charge-coupled device imaging seekers. The kinematics relationship between a small aerial vehicle and target is analyzed, and a two-dimensional guidance law model is established by using artificial neural networks. To compare with the proportional guidance law, the numerical simulations are carried out in the vertical plane and in the horizontal plane respectively. The simulation results show that the ballistic of the small aerial vehicle is straighter and the normal acceleration is smaller by using the bio-inspired guidance law than by using the proportional guidance law. That is to say, the bio-inspired guidance law just uses the information of the target from the imaging seeker,but the performance of it can be better than that of the proportional guidance law.展开更多
Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditiona...Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.展开更多
基金supported by the National Defence Foundation of China(No.62201070404)
文摘During predation, a flying insect can form a stealth flight path. This behavior is called motion camouflage. Based on the study results of this behavior, the perception and neurology of flying insects, a novel bio-inspired guidance law is proposed for the terminal guidance for small aerial vehicle with charge-coupled device imaging seekers. The kinematics relationship between a small aerial vehicle and target is analyzed, and a two-dimensional guidance law model is established by using artificial neural networks. To compare with the proportional guidance law, the numerical simulations are carried out in the vertical plane and in the horizontal plane respectively. The simulation results show that the ballistic of the small aerial vehicle is straighter and the normal acceleration is smaller by using the bio-inspired guidance law than by using the proportional guidance law. That is to say, the bio-inspired guidance law just uses the information of the target from the imaging seeker,but the performance of it can be better than that of the proportional guidance law.
文摘Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.
