University of Oulu

Infrastructure based communication architecture to facilitate autonomous driving and communications

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Author: Rajapakshalage, Dhanushka1
Organizations: 1University of Oulu, Faculty of Information Technology and Electrical Engineering, Communications Engineering
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 4.4 MB)
Pages: 49
Persistent link: http://urn.fi/URN:NBN:fi:oulu-201909242926
Language: English
Published: Oulu : D. Rajapakshalage, 2019
Publish Date: 2019-09-26
Thesis type: Master's thesis (tech)
Tutor: Rajatheva, Rajatheva
Reviewer: Rajatheva, Rajatheva
Pirinen, Pekka
Description:

Abstract

The traditional autonomous vehicle (AV) architecture places a heavy burden on graphics processing units of the vehicle due to heavy signal processing requirements. Ultimately this results in performance degradation in AVs. This is mainly due to advanced sensors, which enable the vision for AVs, like Light Detection and Ranging (LiDAR), radars and cameras. In most of the AV models accepted by many leading automobile companies, LiDAR plays a significant role. It generates a high definition (HD) point cloud of the surroundings to obtain a precise map. AV makes decisions based on that by processing Terabyte (Tb) scale data within the AV. Still, vehicle-mounted LiDARs are not capable of providing information beyond a human driver’s vision.

To provide a solution for the above-mentioned drawbacks of the traditional AVs, we propose an infrastructure based communication architecture to facilitate autonomous driving and communications. A set of coordinated LiDAR modules with integrated transceivers, which are mounted at an elevation with a bird’s eye view, can provide a much larger field of vision (FoV). Decisions are taken from a centralized body. We prove the technical feasibility of the system from sensing and communication point of view. The proposed architecture can play a supportive role with traditional AV architectures and it can be applied to many cases such as to automate harbours and factory floors.

In the second part of the thesis, we address a resource allocation problem with ultra-reliable and low latency communication (URLLC) for a factory floor. We have analytically proven the capability of the proposed system to establish a reliable (packet error probability less than 10^(-5)) and low latency (less than 1 ms transmission delay) links with sufficient throughput (kilobit scale) using a convex optimization problem. Latency, throughput and reliability variations are studied under the short packet transmission of the proposed system.

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Copyright information: © Dhanushka Rajapakshalage, 2019. This publication is copyrighted. You may download, display and print it for your own personal use. Commercial use is prohibited.