  As LiDAR sensors have become ubiquitous, the need for an efficient LiDAR data
compression algorithm has increased. Modern LiDARs produce gigabytes of scan
data per hour and are often used in applications with limited compute,
bandwidth, and storage resources.
  We present a fast, lossless compression algorithm for LiDAR range and
attribute scan sequences including multiple-return range, signal, reflectivity,
and ambient infrared. Our algorithm -- dubbed "Jiffy" -- achieves substantial
compression by exploiting spatiotemporal redundancy and sparsity. Speed is
accomplished by maximizing use of single-instruction-multiple-data (SIMD)
instructions. In autonomous driving, infrastructure monitoring, drone
inspection, and handheld mapping benchmarks, the Jiffy algorithm consistently
outcompresses competing lossless codecs while operating at speeds in excess of
65M points/sec on a single core. In a typical autonomous vehicle use case,
single-threaded Jiffy achieves 6x compression of centimeter-precision range
scans at 500+ scans per second. To ensure reproducibility and enable adoption,
the software is freely available as an open source library.
