Dr GRAZZIELA FIGUEREDO's Outputs (5)

Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management (2018)
Presentation / Conference Contribution
Faboya, O., Figueredo, G. P., Ryan, B., & Siebers, P.-O. (2018, November). Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management. Presented at The 21st IEEE International Conference on Intelligent Transportation Systems, Maui, Hawaii, USA

The uneven utilisation of modes of transport has a big impact on traffic in transport pathway infrastrutures. For motor vehicles for instance, this situation explains rapid road deterioration and the large amounts of money invested in maintenance and... Read More about Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management.

Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom (2018)
Journal Article
Figueredo, G. P., Agrawal, U., Mase, J., Mesgarpour, M., Wagner, C., Soria, D., Garibaldi, J. M., Siebers, P.-O., & John, R. (2019). Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Transactions on Intelligent Transportation Systems, 20(9), 3324-3336. https://doi.org/10.1109/TITS.2018.2875343

Although driving behaviour has been largely studied amongst private motor vehicles drivers, the literature addressing heavy goods vehicle (HGV) drivers is scarce. Identifying the existing groups of driving stereotypes and their proportions enables re... Read More about Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom.

Deep learning approaches to aircraft maintenance, repair and overhaul: a review (2018)
Presentation / Conference Contribution
Rengasami, D., Morvan, H., & Patrocinio Figueredo, G. (2018, November). Deep learning approaches to aircraft maintenance, repair and overhaul: a review. Presented at IEEE International Conference on Intelligent Transportation Systems

The use of sensor technology constantly gathering aircrafts' status data has promoted the rapid development of data-driven solutions in aerospace engineering. These methods assist, for instance, with determining appropriate actions for aircraft maint... Read More about Deep learning approaches to aircraft maintenance, repair and overhaul: a review.

How do travellers decide: a stochastic modelling approach to determine decision factor significance (2018)
Presentation / Conference Contribution
Olusola, F. T., Siebers, O., Ryan, B., & Figueredo, G. P. (2018, September). How do travellers decide: a stochastic modelling approach to determine decision factor significance. Presented at European Modeling and Simulation Symposium 2018 (EMSS2018), Budapest, Hungary

Many factors are involved in travellers' mode choice decision processes. Such factors include individuals' physical, cognitive, and emotional abilities, which play a significant role in travellers' attitude and mode usage patterns. Understanding how... Read More about How do travellers decide: a stochastic modelling approach to determine decision factor significance.

A genetic algorithm with composite chromosome for shift assignment of part-time employees (2018)
Presentation / Conference Contribution
Xue, N., Landa-Silva, D., Triguero, I., & Figueredo, G. P. A genetic algorithm with composite chromosome for shift assignment of part-time employees. Presented at 2018 IEEE Congress in Evolutionary Computation (IEEE CEC 2018)

Personnel scheduling problems involve multiple tasks, including assigning shifts to workers. The purpose is usually to satisfy objectives and constraints arising from management, labour unions and employee preferences. The shift assignment problem is... Read More about A genetic algorithm with composite chromosome for shift assignment of part-time employees.