US 2023/0147100 A1 · Clustering Track Pairs for Multi-Sensor Track Association

Abstract

This document describes systems and techniques for clustering track pairs for multi-sensor track association. Many track-association algorithms use pattern-matching processes that can be computationally complex. Clustering tracks derived from different sensors present on a vehicle may reduce the computational complexity by reducing the pattern-matching problem into groups of subproblems. The weakest connection between two sets of tracks is identified based on both the perspective from each track derived from a first sensor and the perspective of each track derived from a second sensor. By identifying and pruning the weakest connection between two sets of tracks, a large cluster of tracks may be split into smaller clusters. The smaller clusters may require fewer computations by limiting the quantity of candidate track pairs to be evaluated. Fewer computations result in processing the sensor information more efficiently that, in turn, may increase the safety and reliability of an automobile.

Claims20

Dependent claims

A system comprising:

at least one processor configured to:
determine candidate track pairs, each candidate track pair representing a connection between a first track obtained by a first sensor and a second track obtained by a second sensor, the connection based on an association between the first track and the second track to represent a same object;
responsive to identifying a connection with a weakest strength associated with the candidate track pairs, prune a weakest candidate track pair, the weakest candidate track pair having the connection with the weakest strength;
responsive to pruning the weakest candidate track pair, cluster the candidate track pairs into at least a first cluster of the candidate track pairs and a second cluster of the candidate track pairs;
determine, based on track-association techniques, a set of object track pairs from the at least first cluster of the candidate track pairs and the second cluster of the candidate track pairs, a first track and a second track of each respective object track pair in the set of object track pairs representing the same object;
and
output the set of object track pairs to an automotive system of a vehicle to control operations of the vehicle.

4 more elements

A computer-readable storage medium comprising instructions that, when executed, cause at least one processor to:

determine candidate track pairs, each candidate track pair representing a connection between a first track obtained by a first sensor and a second track obtained by a second sensor, the connection based on an association between the first track and the second track to represent a same object;
responsive to identifying a connection with a weakest strength associated with the candidate track pairs, prune a weakest candidate track pair, the weakest candidate track pair having the connection with the weakest strength;
responsive to pruning the weakest candidate track pair, cluster the candidate track pairs into at least a first cluster of the candidate track pairs and a second cluster of the candidate track pairs;
determine, based on track-association techniques, a set of object track pairs from the at least first cluster of the candidate track pairs and the second cluster of the candidate track pairs, a first track and a second track of each respective object track pair in the set of object track pairs representing the same object;
and
output the set of object track pairs to an automotive system of a vehicle to control operations of the vehicle.

3 more elements

Dependencies are inferred from the claim text.

Clustering Track Pairs for Multi-Sensor Track Association

Life of this patent

Clustering Track Pairs for Multi-Sensor Track Association

Life of this patent

Abstract

Claims20