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A Survey of the State-of-the-Art Localisation Techniques and Their Potentials for Autonomous Vehicle Applications

Kuutti, Sampo, Fallah, Saber, Katsaros, Konstantinos, Dianati, Mehrdad, Mccullough, F and Mouzakitis, A (2018) A Survey of the State-of-the-Art Localisation Techniques and Their Potentials for Autonomous Vehicle Applications IEEE Internet of Things, 5 (2). pp. 829-846.

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Abstract

For an autonomous vehicle to operate safely and effectively, an accurate and robust localisation system is essential. While there are a variety of vehicle localisation techniques in literature, there is a lack of effort in comparing these techniques and identifying their potentials and limitations for autonomous vehicle applications. Hence, this paper evaluates the state-of-the-art vehicle localisation techniques and investigates their applicability on autonomous vehicles. The analysis starts with discussing the techniques which merely use the information obtained from on-board vehicle sensors. It is shown that although some techniques can achieve the accuracy required for autonomous driving but suffer from the high cost of the sensors and also sensor performance limitations in different driving scenarios (e.g. cornering, intersections) and different environmental conditions (e.g. darkness, snow). The paper continues the analysis with considering the techniques which benefit from off-board information obtained from V2X communication channels, in addition to vehicle sensory information. The analysis shows that augmenting off-board information to sensory information has potential to design low-cost localisation systems with high accuracy and robustness however their performance depends on penetration rate of nearby connected vehicles or infrastructure and the quality of network service.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
NameEmailORCID
Kuutti, Sampos.j.kuutti@surrey.ac.uk
Fallah, Sabers.fallah@surrey.ac.uk
Katsaros, Konstantinosk.katsaros@surrey.ac.uk
Dianati, MehrdadM.Dianati@surrey.ac.uk
Mccullough, F
Mouzakitis, A
Date : 5 March 2018
Funders : EPSRC
Identification Number : 10.1109/JIOT.2018.2812300
Copyright Disclaimer : Coyright 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.
Depositing User : Melanie Hughes
Date Deposited : 09 Mar 2018 15:40
Last Modified : 27 Apr 2018 09:00
URI: http://epubs.surrey.ac.uk/id/eprint/845978

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