Evaluation of LiDAR data processing at the mobile network edge for connected vehicles

Tiia Ojanperä (Corresponding Author), Jukka Mäkelä, Mikko Majanen, Olli Mämmelä, Ossi Martikainen, Jani Väisänen

Research output: Contribution to journalArticleScientificpeer-review

31 Downloads (Pure)

Abstract

5G mobile network technology together with edge computing will create new opportunities for developing novel road safety services in order to better support connected and automated driving in challenging situations. This paper studies the feasibility and benefits of localized mobile network edge applications for supporting vehicles in diverse conditions. We study a particular scenario, where vehicle sensor data processing, required by road safety services, is installed into the mobile network edge in order to extend the electronic horizon of the sensors carried by other vehicles. Specifically, we focus on a LiDAR data-based obstacle warning case where vehicles receive obstacle warnings from the mobile network edge. The proposed solution is based on a generic system architecture. In this paper, we first evaluate different connectivity and computing options associated with such a system using ns-3 simulations. Then, we introduce a proof-of-concept implementation of the LiDAR-based obstacle warning scenario together with first results from an experimental evaluation, conducted both in a real vehicle testbed environment and in a laboratory setting. As a result, we obtain first insights on the feasibility of the overall solution and further enhancements needed.

Original languageEnglish
Article number96
JournalEURASIP Journal on Wireless Communications and Networking
Volume2021
Issue number1
DOIs
Publication statusPublished - Dec 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • 5G
  • Automotive vertical
  • Experimental evaluation
  • LiDAR
  • MEC
  • Simulations
  • Testbed

Fingerprint

Dive into the research topics of 'Evaluation of LiDAR data processing at the mobile network edge for connected vehicles'. Together they form a unique fingerprint.

Cite this