This article proposes a monocular trajectory intersection method,a videometrics measurement with a mature theoretical system to solve the 3D motion parameters of a point target.It determines the target’s motion param...This article proposes a monocular trajectory intersection method,a videometrics measurement with a mature theoretical system to solve the 3D motion parameters of a point target.It determines the target’s motion parameters including its 3D trajectory and velocity by intersecting the parametric trajectory of a motion target and series of sight-rays by which a motion camera observes the target,in contrast with the regular intersection method for 3D measurement by which the sight-rays intersect at one point.The method offers an approach to overcome the technical failure of traditional monocular measurements for the 3D motion of a point target and thus extends the application fields of photogrammetry and computer vision.Wide application is expected in passive observations of motion targets on various mobile beds.展开更多
It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are main...It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are mainly used to estimate the real-time traffic conditions on road segments, and has done little for turn delay estimation. However, turn delays on road intersections contribute significantly to the overall travel time on road networks in modem cities. In this paper, we present a technical framework to calculate the turn delays on road networks with float car data. First, the original floating car data collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly, the refined trajectory data set was distributed among 96 time intervals （from 0：00 to 23： 59）. All of the intersections where the trajectories passed were connected with the trajectory segments, and constituted an experiment sample, while the intersections on arterial streets were specially selected to form another experiment sample. Thirdly, a principal curve-based algorithm was presented to estimate the turn delays at the given intersections. The algorithm argued is not only statistically fitted the real traffic conditions, but also is insensitive to data sparseness and missing data problems, which currently are almost inevitable with the widely used floating car data collecting technology. We adopted the floating car data collected from March to June in Beijing city in 2011, which contains more than 2.6 million trajectories generated from about 20000 GPS-equipped taxicabs and accounts for about 600 GB in data volume. The result shows the principal curve based algorithm we presented takes precedence over traditional methods, such as mean and median based approaches, and holds a higher estimation accuracy （about 10%-15% higher in RMSE）, as well as reflecting the changing trend of traffic congestion. With the estimation result for the travel delay at intersec展开更多
Advances of positioning and wireless commu- nication technologies make it possible to collect a large number of trajectory data of moving vehicles in a fast and convenient fashion. The data can be applied to various f...Advances of positioning and wireless commu- nication technologies make it possible to collect a large number of trajectory data of moving vehicles in a fast and convenient fashion. The data can be applied to various fields such as traffic study. In derive average delay of traffic and verify the results with this paper, we attempt to flow arotmd intersections changes of time. The intersection zone is delineated first. Positioning points geographically located within this zone are selected, and then outliers are removed. Turn trips are extracted from selected trajectory data. Each trip, physically consisting of time-series positioning points, is identified with entry road segment and turning direction, i.e. target road segment. Turn trips are grouped into different categories according to their time attributes. Then, delay of each trip during a turn is calculated with its recorded speed. Delays of all trips in the same period of time are plotted to observe the change pattern of traffic conditions. Compared to conven- tional approaches, the proposed method can be applied to those intersections without fixed data collection devices such as loop detectors since a large number of trajectory data can always provide a more complete spatio-temporal picture of a road network. With respect to data availability, taxi trajectory data and an intersection in Shanghai are employed to test the proposed methodology. Results demonstrate its applicability.展开更多
Vehicles have been increasingly equipped with GPS receivers to record their trajectories,which we call floating car data.Compared with other data sources,these data are characterized by low cost,wide coverage,and rapi...Vehicles have been increasingly equipped with GPS receivers to record their trajectories,which we call floating car data.Compared with other data sources,these data are characterized by low cost,wide coverage,and rapid updating.The data have become an important source for road network extraction.In this paper,we propose a novel approach for mining road networks from floating car data.First,a Gaussian model is used to transform the data into bitmap,and the Otsu algorithm is utilized to detect road intersections.Then,a clothoid-based method is used to resample the GPS points to improve the clustering accuracy,and the data are clustered based on a distance-direction algorithm.Last,road centerlines are extracted with a weighted least squares algorithm.We report on experiments that were conducted on floating car data from Wuhan,China.To conclude,existing methods are compared with our method to prove that the proposed method is practical and effective.展开更多
By using Lagrangian method, the flow properties of a dusty-gas point source in a supersonic free stream were studied and the particle parameters in the near-symmetry-axis region were obtained . It is demonstrated that...By using Lagrangian method, the flow properties of a dusty-gas point source in a supersonic free stream were studied and the particle parameters in the near-symmetry-axis region were obtained . It is demonstrated that fairly inertial particles travel along oscillating and intersecting trajectories between the bow and termination shock waves . In this region, formation of ' mufti- layer structure' in panicle distribution with alternating low- and high density layers is revealed. Moreover, sharp accumulation of particles occurs near the envelopes of particle trajectories .展开更多
文摘This article proposes a monocular trajectory intersection method,a videometrics measurement with a mature theoretical system to solve the 3D motion parameters of a point target.It determines the target’s motion parameters including its 3D trajectory and velocity by intersecting the parametric trajectory of a motion target and series of sight-rays by which a motion camera observes the target,in contrast with the regular intersection method for 3D measurement by which the sight-rays intersect at one point.The method offers an approach to overcome the technical failure of traditional monocular measurements for the 3D motion of a point target and thus extends the application fields of photogrammetry and computer vision.Wide application is expected in passive observations of motion targets on various mobile beds.
基金This research was supported by the National Natural Science Foundation of China （Grant No. 41271408）, the National Hi-tech Research and Development Program of China （No. 2012AA12A211） and State Key Laboratory of Resources and Environmental Information System Open Foundation （No. 088RA500KA）. And we also thank the anonymous referees for their helpful comments and suggestions.
文摘It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are mainly used to estimate the real-time traffic conditions on road segments, and has done little for turn delay estimation. However, turn delays on road intersections contribute significantly to the overall travel time on road networks in modem cities. In this paper, we present a technical framework to calculate the turn delays on road networks with float car data. First, the original floating car data collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly, the refined trajectory data set was distributed among 96 time intervals （from 0：00 to 23： 59）. All of the intersections where the trajectories passed were connected with the trajectory segments, and constituted an experiment sample, while the intersections on arterial streets were specially selected to form another experiment sample. Thirdly, a principal curve-based algorithm was presented to estimate the turn delays at the given intersections. The algorithm argued is not only statistically fitted the real traffic conditions, but also is insensitive to data sparseness and missing data problems, which currently are almost inevitable with the widely used floating car data collecting technology. We adopted the floating car data collected from March to June in Beijing city in 2011, which contains more than 2.6 million trajectories generated from about 20000 GPS-equipped taxicabs and accounts for about 600 GB in data volume. The result shows the principal curve based algorithm we presented takes precedence over traditional methods, such as mean and median based approaches, and holds a higher estimation accuracy （about 10%-15% higher in RMSE）, as well as reflecting the changing trend of traffic congestion. With the estimation result for the travel delay at intersec
文摘Advances of positioning and wireless commu- nication technologies make it possible to collect a large number of trajectory data of moving vehicles in a fast and convenient fashion. The data can be applied to various fields such as traffic study. In derive average delay of traffic and verify the results with this paper, we attempt to flow arotmd intersections changes of time. The intersection zone is delineated first. Positioning points geographically located within this zone are selected, and then outliers are removed. Turn trips are extracted from selected trajectory data. Each trip, physically consisting of time-series positioning points, is identified with entry road segment and turning direction, i.e. target road segment. Turn trips are grouped into different categories according to their time attributes. Then, delay of each trip during a turn is calculated with its recorded speed. Delays of all trips in the same period of time are plotted to observe the change pattern of traffic conditions. Compared to conven- tional approaches, the proposed method can be applied to those intersections without fixed data collection devices such as loop detectors since a large number of trajectory data can always provide a more complete spatio-temporal picture of a road network. With respect to data availability, taxi trajectory data and an intersection in Shanghai are employed to test the proposed methodology. Results demonstrate its applicability.
基金supported by the Joint Fund for Innovation and Development of Automobile Industry of National Natural Science Foundation of China[Grant Number U1764262]the National Natural Science Foundation of China[Grant Number 42101448].
文摘Vehicles have been increasingly equipped with GPS receivers to record their trajectories,which we call floating car data.Compared with other data sources,these data are characterized by low cost,wide coverage,and rapid updating.The data have become an important source for road network extraction.In this paper,we propose a novel approach for mining road networks from floating car data.First,a Gaussian model is used to transform the data into bitmap,and the Otsu algorithm is utilized to detect road intersections.Then,a clothoid-based method is used to resample the GPS points to improve the clustering accuracy,and the data are clustered based on a distance-direction algorithm.Last,road centerlines are extracted with a weighted least squares algorithm.We report on experiments that were conducted on floating car data from Wuhan,China.To conclude,existing methods are compared with our method to prove that the proposed method is practical and effective.
基金Foundation items : the National Natural Science Foundation of China ( NSFC grant No.90205024) the Russian Foundation for Basic Research (RFBR grant No. 02-01-00770) RFBR-NSFC grant No.99-01-39020)
文摘By using Lagrangian method, the flow properties of a dusty-gas point source in a supersonic free stream were studied and the particle parameters in the near-symmetry-axis region were obtained . It is demonstrated that fairly inertial particles travel along oscillating and intersecting trajectories between the bow and termination shock waves . In this region, formation of ' mufti- layer structure' in panicle distribution with alternating low- and high density layers is revealed. Moreover, sharp accumulation of particles occurs near the envelopes of particle trajectories .
