Dr Faheem Ahmed Malik F.Malik@napier.ac.uk
Lecturer
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
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 |
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