Outputs (6)

Real-Time Nanoscopic Rider Safety System for Smart and Green Mobility Based upon Varied Infrastructure Parameters (2021)
Journal Article
Malik, F. A., Dala, L., & Busawon, K. (2022). Real-Time Nanoscopic Rider Safety System for Smart and Green Mobility Based upon Varied Infrastructure Parameters. Future Internet, 14(1), Article 9. https://doi.org/10.3390/fi14010009

To create a safe bicycle infrastructure system, this article develops an intelligent embedded learning system using a combination of deep neural networks. The learning system is used as a case study in the Northumbria region in England’s northeast. I... Read More about Real-Time Nanoscopic Rider Safety System for Smart and Green Mobility Based upon Varied Infrastructure Parameters.

Intelligent nanoscopic road safety model for cycling infrastructure (2021)
Presentation / Conference Contribution
Malik, F. A., Dala, L., & Busawon, K. (2021, June). Intelligent nanoscopic road safety model for cycling infrastructure. Presented at 2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Heraklion, Greece

This paper is concerned with the development of an intelligent nanoscopic safety model for cycling safety. The present models are primarily focused on motorists modelling at an aggregate level. In this work, a framework for safety analysis is propose... Read More about Intelligent nanoscopic road safety model for cycling infrastructure.

Intelligent Nanoscopic Cyclist Crash Modelling for Variable Environmental Conditions (2021)
Journal Article
Malik, F. A., Dala, L., & Busawon, K. (2022). Intelligent Nanoscopic Cyclist Crash Modelling for Variable Environmental Conditions. IEEE Transactions on Intelligent Transportation Systems, 23(8), 11178-11189. https://doi.org/10.1109/tits.2021.3101118

A cyclist is a vulnerable road user whose interaction with the road infrastructure depends on several factors, including variable environmental conditions of lighting and meteorological road surface. This paper is concerned with nanoscopic crash mode... Read More about Intelligent Nanoscopic Cyclist Crash Modelling for Variable Environmental Conditions.

Intelligent cyclist modelling of personal attribute and road environment conditions to predict the riskiest road infrastructure type (2021)
Presentation / Conference Contribution
Malik, F. A., Dala, L., & Busawon, K. (2021, July). Intelligent cyclist modelling of personal attribute and road environment conditions to predict the riskiest road infrastructure type. Paper presented at The 19th Annual Transport Practitioners' Meeting, Online

Infrastructure selection, design and planning play a pivotal role in creating a safe travel environment for road users, especially the vulnerable road user. In this work, it is aimed to develop a predictive intelligent safety model for the riskiest c... Read More about Intelligent cyclist modelling of personal attribute and road environment conditions to predict the riskiest road infrastructure type.

Modelling transport emission of an out of town centre to achieve emission reduction targets (2021)
Presentation / Conference Contribution
Malik, F. A., Bell, M., Dala, L., & Busawon, K. (2021, March). Modelling transport emission of an out of town centre to achieve emission reduction targets. Presented at 2021 6th International Symposium on Environment-Friendly Energies and Applications (EFEA), Sofia, Bulgaria

Transportation negatively affects the environment due to a high carbon footprint associated with travel. In this paper, we estimate the commuter travel emissions of an out-of-town centre and evaluate the modelled emission against the targets set out... Read More about Modelling transport emission of an out of town centre to achieve emission reduction targets.

Deep neural network-based hybrid modelling for development of the cyclist infrastructure safety model (2021)
Journal Article
Malik, F. A., Dala, L., & Busawon, K. (2021). Deep neural network-based hybrid modelling for development of the cyclist infrastructure safety model. Neural Computing and Applications, 33(18), 11603-11616. https://doi.org/10.1007/s00521-021-05857-3

This paper is concerned with modelling cyclist road safety by considering various factors including infrastructure, spatial, personal and environmental variables affecting cycling safety. Age is one of the personal attributes, reported to be a signif... Read More about Deep neural network-based hybrid modelling for development of the cyclist infrastructure safety model.