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A Novel Fusion Algorithm to Improve Localisation Accuracy of an Instrumented Bicycle

Miah, S., Milonidis, E., Kaparias, I. & Karcanias, N. ORCID: 0000-0002-1889-6314 (2018). A Novel Fusion Algorithm to Improve Localisation Accuracy of an Instrumented Bicycle. Paper presented at the 97th Annual Meeting of the Transportation Research Board, 7 - 11 January 2018, Washington, USA.


Cycling is an increasingly popular mode of travel in cities due to the great advantages that it offers in terms of space consumption, health and environmental sustainability, and is therefore favoured and promoted by many city authorities. However, the relatively low perceived safety of cycling from the users’ side currently presents itself as a hurdle towards higher uptake levels of cycling, and unfortunately, road accident statistics (1) confirm this perception as reality. A typical collision pattern observed involves cyclists being “crushed” by turning motorised vehicles, due to their presence in the so-called “blind spot”, which is to the left of the vehicle in the UK and to the right in countries with right - hand traffic (2). Up until a few years ago, th e only options for tackling such a problem would be drawn from the domain of “hard” traffic engineering measures, (usually cost-intensive and/or severely disruptive, such as segregated lanes or vehicle type bans in certain streets). However, trends in the development of ubiquitous computing now offer smaller, more accurate and durable tools to support traffic safety interventions. Examples range from simple passive measures (3) to more advanced experimental active cyclist detection system (4). But while such solutions certainly represent steps in the right direction in terms of preventing cyclist - vehicle collisions, they are limited in what they are unable to perform any reliable prediction of accidents due to their inability to accurately track the cyclist’s trajectory and estimate his/her position in a critical time-horizon of 5-10 seconds. Indeed, the accurate (< 1 m) localisation of the cyclist is a necessity when it comes to preventing collisions, but so far remains an important unresolved challenge, as none of the existing mainstream technologies (GPS, WiFi etc.) can achieve it. Enhanced positioning systems, on the other hand, such as U-blox (5) and Spatial (6) Inertial Navigation System (INS), can achieve accurate positioning in theory, but they are specifically designed for four-wheel vehicles and are therefore very expensive when used for tracking bicycles. Besides, the dynamics of a bicycle is very complex and different from an ordinary vehicle, and so the accuracy of such enhanced positioning syst ems will differ greatly when used on a bicycle. The research reported here focuses on the development and testing of an innovative technological solution for accurately localising and tracking cyclists in urban environments using a low-cost micro-electrome chanical systems (MEMS) sensor configuration on a prototype instrumented bicycle system, called “ iBike ” (7). The ultimate goal is to develop a collision prediction and avoidance system, and the present paper presents a novel fusion technique that could be utilised to improve localisation accuracy based on Wireless Communication Technologies (WCT) widely found in cities as well as Global Navigation Satellite System (GNSS) positioning.

Publication Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TE Highway engineering. Roads and pavements
Departments: School of Science & Technology > Engineering
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