Modeling the Effects of Residual Snow Clutter on Position Estimation and Vehicle Energy Efficiency
Document Type
Conference Proceeding
Publication Date
1-1-2026
Abstract
We model the effect of lidar snow clutter on position estimation algorithms. The uncertainty in position estimation is modeled as uniformly distributed under the assumptions of a well-performing snow filter. We apply this model to characterize the precision of a RANSAC-based segmenter when using spatial and intensity-based snow filters for lead vehicle position estimation. The fitted models of each estimator-filter combination are used to calculate the expected drag reduction and energy consumption from automated vehicle following. The results from these models indicate that the choice of snow filter can reduce a vehicle's energy consumption by 0.421 Wh/km.
Publication Title
2026 IEEE International Workshop on Metrology for Automotive Metroautomotive 2026 Proceedings
ISBN
[9798331551285]
Recommended Citation
Schexnaydre, L.,
Mattson, I.,
Cornwall, C.,
&
Bos, J.
(2026).
Modeling the Effects of Residual Snow Clutter on Position Estimation and Vehicle Energy Efficiency.
2026 IEEE International Workshop on Metrology for Automotive Metroautomotive 2026 Proceedings, 179-184.
http://doi.org/10.1109/MetroAutomotive69354.2026.11644681
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p2/3011