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Development of a Safety System for Intelligent Cyclist modelling

Malik, Faheem Ahmed; Dala, Laurent; Busawon, Krishna

Authors

Laurent Dala

Krishna Busawon



Abstract

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

Citation

Malik, F. A., Dala, L., & Busawon, K. (2020, November). Development of a Safety System for Intelligent Cyclist modelling. Presented at 2020 3rd International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM), Balaclava, Mauritius

Presentation Conference Type Conference Paper (published)
Conference Name 2020 3rd International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM)
Start Date Nov 25, 2020
End Date Nov 27, 2020
Online Publication Date Dec 25, 2020
Publication Date 2020
Deposit Date Apr 28, 2025
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Pages 22-27
Book Title 2020 3rd International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM)
ISBN 9781728157085
DOI https://doi.org/10.1109/elecom49001.2020.9297001
Keywords cycling safety , artificial neural network , infrastructure , real-time safety modelling
Public URL http://researchrepository.napier.ac.uk/Output/4247571
This output contributes to the following UN Sustainable Development Goals:

SDG 3 - Good Health and Well-Being

Ensure healthy lives and promote well-being for all at all ages

SDG 5 - Gender Equality

Achieve gender equality and empower all women and girls

SDG 10 - Reduced Inequalities

Reduce inequality within and among countries

SDG 11 - Sustainable Cities and Communities

Make cities and human settlements inclusive, safe, resilient and sustainable

SDG 13 - Climate Action

Take urgent action to combat climate change and its impacts

SDG 17 - Partnerships for the Goals

Strengthen the means of implementation and revitalize the global partnership for sustainable development






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