Towards autonomous driving: a machine learning-based pedestrian detection system using 16-layer LiDAR
Conference paper
Mihai, S., Shah, P., Mapp, G., Nguyen, H. and Trestian, R. 2020. Towards autonomous driving: a machine learning-based pedestrian detection system using 16-layer LiDAR. COMM 2020. Bucharest, Romania 18 - 20 Jun 2020 Institute of Electrical and Electronics Engineers (IEEE). pp. 271-276 https://doi.org/10.1109/COMM48946.2020.9142042
Type | Conference paper |
---|---|
Title | Towards autonomous driving: a machine learning-based pedestrian detection system using 16-layer LiDAR |
Authors | Mihai, S., Shah, P., Mapp, G., Nguyen, H. and Trestian, R. |
Abstract | The advent of driverless and automated vehicle technologies opens up a new era of safe and comfortable transportation. However, one of the most important features that an autonomous vehicle requires, is a reliable pedestrian detection mechanism. Many solutions have been proposed in the literature to achieve this technology, ranging from image processing algorithms applied on a camera feed, to filtering LiDAR scans for points that are reflected off pedestrians. To this extent, this paper proposes a machine learning-based pedestrian detection mechanism using a 16-layer Velodyne Puck LITE LiDAR. The proposed mechanism compensates for the low resolution of the LiDAR through the use of linear interpolation between layers, effectively introducing 15 pseudo-layers to help obtain timely detection at practical distances. The pedestrian candidates are then classified u sing a Support Vector Machine ( SVM), and the algorithm is verified by accuracy testing using real LiDAR frames acquired under different road scenarios. |
Conference | COMM 2020 |
Page range | 271-276 |
ISBN | |
Electronic | 9781728156118 |
Electronic | 9781728156101 |
Paperback | 9781728156125 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Publication dates | |
18 Jun 2020 | |
Online | 16 Jul 2020 |
Publication process dates | |
Deposited | 04 Jun 2020 |
Accepted | 25 May 2020 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/COMM48946.2020.9142042 |
Language | English |
Book title | Proceedings of the 13th International Conference on Communications (COMM) |
https://repository.mdx.ac.uk/item/88z45
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