In this paper,we propose a new method to achieve automatic matching of multi-scale roads under the constraints of smaller scale data.The matching process is:Firstly,meshes are extracted from two different scales road ...In this paper,we propose a new method to achieve automatic matching of multi-scale roads under the constraints of smaller scale data.The matching process is:Firstly,meshes are extracted from two different scales road data.Secondly,several basic meshes in the larger scale road network will be merged into a composite one which is matched with one mesh in the smaller scale road network,to complete the N∶1(N>1)and 1∶1 matching.Thirdly,meshes of the two different scale road data with M∶N(M>1,N>1)matching relationships will be matched.Finally,roads will be classified into two categories under the constraints of meshes:mesh boundary roads and mesh internal roads,and then matchings between the two scales meshes will be carried out within their own categories according to the matching relationships.The results show that roads of different scales will be more precisely matched using the proposed method.展开更多
Increasing frame torsional stiffness of off-road vehicle will lead to the decrease of body torsional deformation, but the increase of torsional loads of frame and suspension system and the decrease of wheel adhesive w...Increasing frame torsional stiffness of off-road vehicle will lead to the decrease of body torsional deformation, but the increase of torsional loads of frame and suspension system and the decrease of wheel adhesive weight. In severe case, a certain wheel will be out of contact with road surface. Appropriate matching of body, frame and suspension torsional stiffnesses is a difficult problem for off-road vehicle design. In this paper, these theoretically analytic models of the entire vehicle, body, frame and suspension torsional stiffness are constructed based on the geometry and mechanism of a light off-road vehicle's body, frame and suspension. The body and frame torsional stiffnesses can be calculated by applying body CAE method, meanwhile the suspension's rolling angle stiffness can be obtained by the bench test of the suspension's elastic elements. Through fixing the entire vehicle, using sole timber to raise wheels to simulate the road impact on a certain wheel, the entire vehicle torsional stiffness can be calculated on the geometric relation and loads of testing. Finally some appropriate matching principles of the body, frame and suspension torsional stiffness are summarized according to the test and analysis results. The conclusion can reveal the significance of the suspension torsional stiffness on off-road vehicle's torsion-absorbing capability. The results could serve as a reference for the design of other off-road vehicles.展开更多
To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states,a road traffic states estimation algorithm based on matching of the regional traffic at...To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states,a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work.First of all,the road traffic running states were divided into several different modes.The concept of the regional traffic attracters of the target link was put forward for effective matching.Then,the reference sequences of characteristics of traffic running states with the contents of the target link's traffic running states and regional traffic attracters under different modes were established.In addition,the current and historical regional traffic attracters of the target link were matched through certain matching rules,and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data,which were processed with Kalman filter to obtain the final recovery data.Finally,some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm.The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy.展开更多
As an independent navigation method,inertial navigation system(INS)has played a huge advantage in a lot of special conditions.But its positioning error will accumulate with time,so it is difficult to work independentl...As an independent navigation method,inertial navigation system(INS)has played a huge advantage in a lot of special conditions.But its positioning error will accumulate with time,so it is difficult to work independently for a long time.The vehicle loaded with the inertial navigation system usually drives on the road,so the high precision road data based on geographic information system(GIS)can be used as a bind of auxiliary information,which could correct INS errors by the correlation matching algorithm.The existing road matching methods rely on mathematical models,mostly for global positioning system(GPS)trajectory data,and are limited to model parameters.Therefore,based on the features of inertial navigation trajectory and road,this paper proposes a road data aided vehicle inertial navigation method based on the learning to rank and iterative closest contour point(ICCP)algorithm.Firstly,according to the geometric and directional features of inertial navigation trajectory and road,the combined feature vector is constructed as the input value;Furthermore,the scoring function and RankNet neural network based on the features of vehicle trajectory data and road data are constructed,which can learn and extract the features;Then,the nearest point of each track point and its corresponding road data set to be matched is calculated.The average translation between the two data sets is calculated by using the position relationship between each group of track points to be matched and road points;Finally,the trajectory data set is iteratively translated according to the translation amount,and the matching track point set is obtained when the trajectory error converges to complete the matching.During experiments,it is compared with other algorithms including the hidden Markov model(HMM)matching method.The experimental results show that the algorithm can effectively suppress the divergence of trajectory error.The matching accuracy is close to HMM algorithm,and the computational efficiency can meet the requirements of the traditional matching algorithm.展开更多
This paper presents a framework for road network change detection in order to update the Canadian National Topographic DataBase (NTDB). The methodology has been developed on the basis of road extraction from IRS\|pan ...This paper presents a framework for road network change detection in order to update the Canadian National Topographic DataBase (NTDB). The methodology has been developed on the basis of road extraction from IRS\|pan images (with a 5.8 m spatial resolution) by using a wavelet approach. The feature matching and conflation techniques are used to road change detection and updating. Elementary experiments have showed that the proposed framework could be used for developing an operational road database updating system.展开更多
A new real-time map matching algorithm based on fuzzy logic is proposed. 3 main factors affecting the reliability of map matching, including the distance between the vehicle location and the matching road segment, the...A new real-time map matching algorithm based on fuzzy logic is proposed. 3 main factors affecting the reliability of map matching, including the distance between the vehicle location and the matching road segment, the angle between the vehicle direction and the road segment direction and the road connectivity are discussed. Fuzzy rules for the distance, angle and connectivity are presented to calculate the matching reliability. 2 indicators for estimating the matching reliability are then derived, one is the lower limit of the reliability, and the other is the limit error of the difference between the maximal value and the second-maximal value of the reliability. A real-time map-matching system based on fuzzy logic is therefore developed. Using the real data of global positioning system(GIS) based navigation and geographic information system(GPS) based road map, the method is verified and the (results) prove the effectiveness of the proposed method.展开更多
基金The National Natural Science Foundation of China(Nos.4110136241471386)。
文摘In this paper,we propose a new method to achieve automatic matching of multi-scale roads under the constraints of smaller scale data.The matching process is:Firstly,meshes are extracted from two different scales road data.Secondly,several basic meshes in the larger scale road network will be merged into a composite one which is matched with one mesh in the smaller scale road network,to complete the N∶1(N>1)and 1∶1 matching.Thirdly,meshes of the two different scale road data with M∶N(M>1,N>1)matching relationships will be matched.Finally,roads will be classified into two categories under the constraints of meshes:mesh boundary roads and mesh internal roads,and then matchings between the two scales meshes will be carried out within their own categories according to the matching relationships.The results show that roads of different scales will be more precisely matched using the proposed method.
文摘Increasing frame torsional stiffness of off-road vehicle will lead to the decrease of body torsional deformation, but the increase of torsional loads of frame and suspension system and the decrease of wheel adhesive weight. In severe case, a certain wheel will be out of contact with road surface. Appropriate matching of body, frame and suspension torsional stiffnesses is a difficult problem for off-road vehicle design. In this paper, these theoretically analytic models of the entire vehicle, body, frame and suspension torsional stiffness are constructed based on the geometry and mechanism of a light off-road vehicle's body, frame and suspension. The body and frame torsional stiffnesses can be calculated by applying body CAE method, meanwhile the suspension's rolling angle stiffness can be obtained by the bench test of the suspension's elastic elements. Through fixing the entire vehicle, using sole timber to raise wheels to simulate the road impact on a certain wheel, the entire vehicle torsional stiffness can be calculated on the geometric relation and loads of testing. Finally some appropriate matching principles of the body, frame and suspension torsional stiffness are summarized according to the test and analysis results. The conclusion can reveal the significance of the suspension torsional stiffness on off-road vehicle's torsion-absorbing capability. The results could serve as a reference for the design of other off-road vehicles.
基金Projects(D07020601400707,D101106049710005)supported by the Beijing Science Foundation Plan Project,ChinaProjects(2006AA11Z231,2012AA112401)supported by the National High Technology Research and Development Program of China(863 Program)Project(61104164)supported by the National Natural Science Foundation of China
文摘To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states,a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work.First of all,the road traffic running states were divided into several different modes.The concept of the regional traffic attracters of the target link was put forward for effective matching.Then,the reference sequences of characteristics of traffic running states with the contents of the target link's traffic running states and regional traffic attracters under different modes were established.In addition,the current and historical regional traffic attracters of the target link were matched through certain matching rules,and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data,which were processed with Kalman filter to obtain the final recovery data.Finally,some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm.The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy.
基金National Key Research and Development Plan(2016YFB0502300)。
文摘As an independent navigation method,inertial navigation system(INS)has played a huge advantage in a lot of special conditions.But its positioning error will accumulate with time,so it is difficult to work independently for a long time.The vehicle loaded with the inertial navigation system usually drives on the road,so the high precision road data based on geographic information system(GIS)can be used as a bind of auxiliary information,which could correct INS errors by the correlation matching algorithm.The existing road matching methods rely on mathematical models,mostly for global positioning system(GPS)trajectory data,and are limited to model parameters.Therefore,based on the features of inertial navigation trajectory and road,this paper proposes a road data aided vehicle inertial navigation method based on the learning to rank and iterative closest contour point(ICCP)algorithm.Firstly,according to the geometric and directional features of inertial navigation trajectory and road,the combined feature vector is constructed as the input value;Furthermore,the scoring function and RankNet neural network based on the features of vehicle trajectory data and road data are constructed,which can learn and extract the features;Then,the nearest point of each track point and its corresponding road data set to be matched is calculated.The average translation between the two data sets is calculated by using the position relationship between each group of track points to be matched and road points;Finally,the trajectory data set is iteratively translated according to the translation amount,and the matching track point set is obtained when the trajectory error converges to complete the matching.During experiments,it is compared with other algorithms including the hidden Markov model(HMM)matching method.The experimental results show that the algorithm can effectively suppress the divergence of trajectory error.The matching accuracy is close to HMM algorithm,and the computational efficiency can meet the requirements of the traditional matching algorithm.
文摘This paper presents a framework for road network change detection in order to update the Canadian National Topographic DataBase (NTDB). The methodology has been developed on the basis of road extraction from IRS\|pan images (with a 5.8 m spatial resolution) by using a wavelet approach. The feature matching and conflation techniques are used to road change detection and updating. Elementary experiments have showed that the proposed framework could be used for developing an operational road database updating system.
基金Projects(40301043 and 40171078) supported by the National Natural Science Foundation of China
文摘A new real-time map matching algorithm based on fuzzy logic is proposed. 3 main factors affecting the reliability of map matching, including the distance between the vehicle location and the matching road segment, the angle between the vehicle direction and the road segment direction and the road connectivity are discussed. Fuzzy rules for the distance, angle and connectivity are presented to calculate the matching reliability. 2 indicators for estimating the matching reliability are then derived, one is the lower limit of the reliability, and the other is the limit error of the difference between the maximal value and the second-maximal value of the reliability. A real-time map-matching system based on fuzzy logic is therefore developed. Using the real data of global positioning system(GIS) based navigation and geographic information system(GPS) based road map, the method is verified and the (results) prove the effectiveness of the proposed method.