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Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments

  • Abstract In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.

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Author:Joschua Schulte-TiggesORCiD, Marco Förster, Gjorgji NikolovskiORCiD, Michael RekeORCiD, Alexander FerreinORCiD, Daniel KasznerORCiD, Dominik MatheisORCiD, Thomas WalterORCiD
Parent Title (English):Sensors
Place of publication:Basel
Document Type:Article
Year of Completion:2022
Date of first Publication:2022/09/21
Date of the Publication (Server):2023/01/25
Tag:Benchmark; Lidar; Self-driving
Length:20 Seiten
This article belongs to the Special Issue "Sensor Fusion for Vehicles Navigation and Robotic Systems"
Institutes:FH Aachen / Fachbereich Elektrotechnik und Informationstechnik
FH Aachen / MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik
collections:Verlag / MDPI
Open Access / Gold
Licence (German):License LogoCreative Commons - Namensnennung