2 research outputs found
PolyMerge: A Novel Technique aimed at Dynamic HD Map Updates Leveraging Polylines
Currently, High-Definition (HD) maps are a prerequisite for the stable
operation of autonomous vehicles. Such maps contain information about all
static road objects for the vehicle to consider during navigation, such as road
edges, road lanes, crosswalks, and etc. To generate such an HD map, current
approaches need to process pre-recorded environment data obtained from onboard
sensors. However, recording such a dataset often requires a lot of time and
effort. In addition, every time actual road environments are changed, a new
dataset should be recorded to generate a relevant HD map.
This paper addresses a novel approach that allows to continuously generate or
update the HD map using onboard sensor data. When there is no need to
pre-record the dataset, updating the HD map can be run in parallel with the
main autonomous vehicle navigation pipeline.
The proposed approach utilizes the VectorMapNet framework to generate vector
road object instances from a sensor data scan. The PolyMerge technique is aimed
to merge new instances into previous ones, mitigating detection errors and,
therefore, generating or updating the HD map.
The performance of the algorithm was confirmed by comparison with ground
truth on the NuScenes dataset. Experimental results showed that the mean error
for different levels of environment complexity was comparable to the
VectorMapNet single instance error.Comment: 6 pages, 9 figure