53results about How to "Improve association accuracy" patented technology

The invention relates to an OSPA (Optimal Subpattern Assignment) distance track correlation method with a fixed sliding window, which comprises the steps of: describing a local track into a set, introducing an OSPA distance evaluation between target track sets, judging whether two local tracks belong to the same track; and designing a method introduced with an upper triangular block matrix and a track correlation matrix to form a pairwise matching process between tracks of all sensors, on the basis, further designing a recursion OSPA track distance computing method with a fixed sliding window. According to the OSPA distance suggested by the OSPA distance track correlation method, same tracks can be effectively correlated, and problems of track crossing, track branching and track asynchronization can be effectively dealt. Compared with a weighting track correlation method and an independent sequential track correlation method, the OSPA distance track correlation method has special advantages on the aspects of correlation precision and track asynchronization.

The present invention provides a multi-sensor data fusion method, a device and a vehicle. The invention aims to solve the problem of low association accuracy of the data of a plurality of sensors in the prior art. According to the multi-sensor data fusion method, the device and the vehicle, a plurality of sensors are used for detecting data of a plurality of dimensions of objects in the same area.The method includes the following steps that: a corresponding data interval is set for each dimension of a first object according to the data of a plurality of dimensions of the first object detectedby a first sensor, wherein the first object is any object detected by the first sensor; whether a unique second object exists in all objects detected by a second sensor is judged, and the data of each dimension of the second object are all in the data intervals set correspondingly set for the first object; and if the unique second object exists in all the objects detected by the second sensor, and the first object and the second object are associated to correspond to the same object in the area.

The invention provides a traffic object fusion association method and device in a driving environment and edge calculation equipment, and relates to an intelligent traffic technology and an automatic driving technology. The method comprises the steps: obtaining first environment information and second environment information; the first environment information and the second environment information are collected through different sensors; determining first lane information of a first traffic object in the first environment information according to the first environment information, and determining second lane information of a second traffic object in the second environment information according to the second environment information; According to the information of the first traffic object in the first environment information, the information of the second traffic object in the second environment information, the first lane information and the second lane information, determining whether the first traffic object and the second traffic object have an association relationship. According to the scheme provided by the invention, the information of the lane where the traffic object is located can be combined to determine whether the traffic object has the association relationship, so that the fusion association accuracy of the traffic object can be improved.