Review of LiDAR Sensor Data Acquisition and Compression for Automotive Applications

Ievgeniia Maksymova, Christian Steger, Norbert Druml

Research output: Contribution to journalConference articleResearchpeer-review

Abstract

Due to specific dynamics of the operating environment and required safety regulations, the amount of acquired data of an automotive LiDAR sensor that has to be processed is reaching several Gbit/s. Therefore, data compression is much-needed to enable future multi-sensor automated vehicles. Numerous techniques have been developed to compress LiDAR raw data; however, these techniques are primarily targeting a compression of 3D point cloud, while the way data is captured and transferred from a sensor to an electronic computing unit (ECU) was left out. The purpose of this paper is to discuss and evaluate how various low-level compression algorithms could be used in the automotive LiDAR sensor in order to optimize on-chip storage capacity and link bandwidth. We also discuss relevant parameters that affect amount of collected data per second and what are the associated issues. After analyzing compressing approaches and identifying their limitations, we conclude several promising directions for future research.
Original languageEnglish
Article number852
JournalProceedings MDPI
Volume2
Issue number13
DOIs
Publication statusPublished - 2018
EventEurosensors 2018 - Karl Franzens Universität Graz, Graz, Austria
Duration: 9 Sep 201812 Sep 2018
https://www.eurosensors2018.eu

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