Development of a Safety System for Intelligent Cyclist modelling

Malik, Faheem, Dala, Laurent and Busawon, Krishna (2020) Development of a Safety System for Intelligent Cyclist modelling. In: 2020 3rd International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering, ELECOM 2020 - Proceedings. IEEE, Piscataway, NJ, pp. 22-27. ISBN 9781728157085, 9781728157078

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This paper is concerned with the modelling of cyclist road traffic crashes by considering multiple factors affecting the safety of cyclists. There are very few works in the literature dealing with such a problem. The available models in the literature are only based upon the probabilistic function of human error. In this study, we propose an intelligent safety system for modelling cycling infrastructure. The historic crash dataset for the Tyne and Wear County, north-east of England is used as a case study. There are five predictive road safety models develops using the Artificial Neural Network, with the output for the riskiest road type infrastructure. The study demonstrates that infrastructure, spatial variables, personal characteristics, and environmental conditions affect safety, which can also be used for predicting safety. These identified variables are modelled both individually and in combination with each other, and a plausible high accuracy is achieved in all the five models (> 85 accuracy). This demonstrates the benefit of using ANN for effective and efficient modelling of the safety variable for infrastructure design and planning. It is hoped that the proposed model can help in designing better cyclist infrastructure and contribute towards the development of a sustainable transportation system.

Item Type: Book Section
Additional Information: Funding information: We would like to thank Northumbria University for sponsoring the research (Research Development Fund) and Gateshead city council for providing access to crash data.
Uncontrolled Keywords: artificial neural network, cycling safety, infrastructure, real-Time safety modelling
Subjects: H300 Mechanical Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Elena Carlaw
Date Deposited: 12 Aug 2021 11:24
Last Modified: 12 Aug 2021 11:31

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