In addition to providing convenience and improving safety autonomous vehicle technologies offer an opportunity to reduce energy use by up to twenty percent or more. One strategy for reducing energy use is careful positioning of an autonomous vehicle, the ego vehicle, behind one or more lead vehicles. Most perception pipelines fit a bounding box around the center of mass of a detected object. That approach may not be accurate enough to allow for precise positioning. Here we compare different methods of identifying vehicle boundaries and vehicle type using a combination of simulation and field testing. Approaches will be compared based on required LiDAR resolution and algorithm complexity relative to potential improvement in energy efficiency.
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