To solve the problem that traditional long baseline（LBL） positioning system is easily affected by severe sound speed varying results in low calibration precision, low efficiency and inconsistent position using diffe...To solve the problem that traditional long baseline（LBL） positioning system is easily affected by severe sound speed varying results in low calibration precision, low efficiency and inconsistent position using different references, we propose a high precision array calibration method. We use distances between beacons to build error adjustment model. This model improves the calibration performance of traditional calibration method. The theory shows this method can achieve equal calibration precision with distance measurement precision in horizon. This method can improve the calibration efficiency, solve position ambiguity and achieve high precision especially in deep ocean. The shallow water experiment shows this method has millimeter calibration precision which is equal to distance measurement error. The calibration precision improves from centimeter to millimeter compared to traditional calibration method.The method also decreases the operation complexity. The localized positions are more close to GPS compared to traditional method, which has great application values.展开更多
Many traffic accidents occur in parking lots.One of the serious safety risks is vehicle-pedestrian conflict.Moreover,with the increasing development of automatic driving and parking technology,parking safety has recei...Many traffic accidents occur in parking lots.One of the serious safety risks is vehicle-pedestrian conflict.Moreover,with the increasing development of automatic driving and parking technology,parking safety has received significant attention from vehicle safety analysts.However,pedestrian protection in parking lots still faces many challenges.For example,the physical structure of a parking lot may be complex,and dead corners would occur when the vehicle density is high.These lead to pedestrians’sudden appearance in the vehicle’s path from an unexpected position,resulting in collision accidents in the parking lot.We advocate that besides vehicular sensing data,high-precision digital map of the parking lot,pedestrians’smart device’s sensing data,and attribute information of pedestrians can be used to detect the position of pedestrians in the parking lot.However,this subject has not been studied and explored in existing studies.Tofill this void,this paper proposes a pedestrian tracking framework integrating multiple information sources to provide pedestrian position and status information for vehicles and protect pedestrians in parking spaces.We also evaluate the proposed method through real-world experiments.The experimental results show that the proposed framework has its advantage in pedestrian attribute information extraction and positioning accuracy.It can also be used for pedestrian tracking in parking spaces.展开更多
基金supported by the National Natural Science Foundation of China(61531012)
文摘To solve the problem that traditional long baseline（LBL） positioning system is easily affected by severe sound speed varying results in low calibration precision, low efficiency and inconsistent position using different references, we propose a high precision array calibration method. We use distances between beacons to build error adjustment model. This model improves the calibration performance of traditional calibration method. The theory shows this method can achieve equal calibration precision with distance measurement precision in horizon. This method can improve the calibration efficiency, solve position ambiguity and achieve high precision especially in deep ocean. The shallow water experiment shows this method has millimeter calibration precision which is equal to distance measurement error. The calibration precision improves from centimeter to millimeter compared to traditional calibration method.The method also decreases the operation complexity. The localized positions are more close to GPS compared to traditional method, which has great application values.
基金Our research in this paper was partially supported by JST COI JPMJCE1317.
文摘Many traffic accidents occur in parking lots.One of the serious safety risks is vehicle-pedestrian conflict.Moreover,with the increasing development of automatic driving and parking technology,parking safety has received significant attention from vehicle safety analysts.However,pedestrian protection in parking lots still faces many challenges.For example,the physical structure of a parking lot may be complex,and dead corners would occur when the vehicle density is high.These lead to pedestrians’sudden appearance in the vehicle’s path from an unexpected position,resulting in collision accidents in the parking lot.We advocate that besides vehicular sensing data,high-precision digital map of the parking lot,pedestrians’smart device’s sensing data,and attribute information of pedestrians can be used to detect the position of pedestrians in the parking lot.However,this subject has not been studied and explored in existing studies.Tofill this void,this paper proposes a pedestrian tracking framework integrating multiple information sources to provide pedestrian position and status information for vehicles and protect pedestrians in parking spaces.We also evaluate the proposed method through real-world experiments.The experimental results show that the proposed framework has its advantage in pedestrian attribute information extraction and positioning accuracy.It can also be used for pedestrian tracking in parking spaces.
