LiDAR system benchmarking for VRU detection in heavy goods vehicle blind spots

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)
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Abstract

This article is related to using modern LiDARs and neural networks based algorithms for vulnerable road users (VRU) detection. The problem is obvious especially when considering blind spots of heavy goods vehicles. LiDARs have developed a lot recently and the results indicate that adults can be detected up-to 75 m distance from the sensor even thought that pattern recognition requires sufficient point cloud-resolution. Two different LiDAR brands have been compared to understand costbenefits between LiDAR technologies. The results have been conducted using an automated passenger car while considering feasibility to big trucks. Due to automotive requirements, the processing rate is also considered since usually, the main bottleneck is computation power, which is limited in automotive products. The used neural network algorithm is Yolo based and has been designed for VRU detection.
Original languageEnglish
Title of host publication2021 IEEE 17th International Conference on Intelligent Computer Communication and Processing (ICCP)
EditorsSergiu Nedevschi, Rodica Potolea, Radu Razvan Slavescu
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages299-303
Number of pages5
ISBN (Electronic)978-1-6654-0976-6
ISBN (Print)978-1-6654-0977-3
DOIs
Publication statusPublished - 16 Mar 2022
MoE publication typeA4 Article in a conference publication
EventIEEE 17th International Conference on Intelligent Computer Communication and Processing - Technical University of Cluj-Napoca, Cluj-Napoca, Romania
Duration: 28 Oct 202130 Oct 2021
https://iccp.ro/iccp2021/

Conference

ConferenceIEEE 17th International Conference on Intelligent Computer Communication and Processing
Country/TerritoryRomania
CityCluj-Napoca
Period28/10/2130/10/21
Internet address

Keywords

  • 3D Object Detection
  • neural network
  • LiDAR
  • heavy goods vehicle
  • VRU
  • blind spot safety

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