Using Automotive Lidar to Reduce the Energy Consumption of an Ego Autonomous Vehicle

Author

• Logan P. Schexnaydre, Michigan Technological UniversityFollow

Date of Award

2026

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Computer Engineering (PhD)

Administrative Home Department

Department of Electrical and Computer Engineering

Advisor 1

Jeremy P. Bos

Committee Member 1

Tan Chen

Committee Member 2

Anthony J. Pinar

Committee Member 3

Darrell Robinette

Abstract

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model the relationship between lidar precision, drag reduction, and vehicle energy consumption. This work shows that model-fitting processing algorithms enable closer following distances, further reducing energy use. Next, I introduce a method to estimate the road grade a vehicle will experience using the vehicle's geometry. This method demonstrates that automotive lidar is sufficiently precise to support or replace conventional map-based grade information. Finally, I extend the automated vehicle following model to snowy weather conditions to show how residual snow clutter affects the net energy use of the vehicle. The results indicate that both spatial and intensity features are required for filtering snow to achieve position estimation precision and energy savings similar to those achieved in clear weather.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

Schexnaydre, Logan P., "Using Automotive Lidar to Reduce the Energy Consumption of an Ego Autonomous Vehicle", Open Access Dissertation, Michigan Technological University, 2026.

https://digitalcommons.mtu.edu/etdr/2176