P. Georgieva,
M. V. Drummond,
3D Object Detection for Self-Driving Vehicles Enhanced by Object Velocity,
E Proof
Received 7 December 2023, accepted 24 December 2023. Date of publication 00 xxxx 0000, date of current version 00 xxxx 0000.
Digital Object Identifier 10.1109/ACCESS.2024.3353051
3D Object Detection for Self-Driving Vehicles
Enhanced by Object Velocity
LEANDRO ALEXANDRINO 1,2,3, HADI Z. OLYAEI3, ANDRÉ ALBUQUERQUE3,
PETIA GEORGIEVA 1,2,4, (Senior Member, IEEE),
AND MIGUEL V. DRUMMOND 1,2, (Member, IEEE)
1
AQ:2 Instituto de Telecomunicações, 3810-193 Aveiro, Portugal
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AQ:3 Universidade de Aveiro, 3810-193 Aveiro, Portugal
3
AQ:4 Bosch Car Multimedia, 4705-820 Braga, Portugal
4
AQ:5 Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal
AQ:6 Corresponding author: Leandro Alexandrino (l.alexandrino@ua.pt)
AQ:7 This work was supported in part by the European Union (EU)-NextGenerationEU through the National Recovery and Resilience Plan,
Bulgaria, under Project BG-RRP-2.004-0005; and in part by FCT/MCTES through the National Funds co-funded EU Funds under Project
UIDB/50008/2020-UIDP/50008/2020.
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ABSTRACT AQ:8 A large number of vision sensors has been proposed for enabling self-driving vehicles to
perceive their surroundings. Among them, Light Detection And Ranging (LiDAR) presents the unique
advantage of acquiring a high resolution 3D representation of the vehicle surroundings, in the form of point
clouds, which enables accurate 3D object detection. The success of the fi rst (and current) generation LiDARs
has motivated the development of a second generation of this sensor, now based on coherent detection.
Second generation LiDARs thus enable not only estimating radial distance, but also radial velocity for each
point of the point cloud. The objective of this work is to investigate which benefi ts can be obtained by
considering such an additional information – radial velocity – in 3D object detection. Results show that
considering object velocity is particularly helpful in objects represented by a small number of points.,
30-11-2023
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A. F. Sousa,
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Best Paper Award,
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01-02-2018
