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Your search keyword '"Grant-Muller, S."' showing total 13 results
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13 results on '"Grant-Muller, S."'

1. Fogbanks: Future Dynamic Vehicular Fog Banks for Processing, Sensing and Storage in 6G

Author

Alahmadi, A. A., Musa, M. O. I., El-Gorashi, T. E. H., Elmirghani, J. M. H., Grant-Muller, S., Hutchison, D., Mauthe, A., Dianati, M., Maple, C., Lefevre, L., and Lason, A.

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

Fixed edge processing has become a key feature of 5G networks, while playing a key role in reducing latency, improving energy efficiency and introducing flexible compute resource utilization on-demand with added cost savings. Autonomous vehicles are expected to possess significantly more on-board processing capabilities and with improved connectivity. Vehicles continue to be used for a fraction of the day, and as such there is a potential to increase processing capacity by utilizing these resources while vehicles are in short-term and long-term car parks, in roads and at road intersections. Such car parks and road segments can be transformed, through 6G networks, into vehicular fog clusters, or Fogbanks, that can provide processing, storage and sensing capabilities, making use of underutilized vehicular resources. We introduce the Fogbanks concept, outline current research efforts underway in vehicular clouds, and suggest promising directions for 6G in a world where autonomous driving will become commonplace. Moreover, we study the processing allocation problem in cloud-based Fogbank architecture. We solve this problem using Mixed Integer Programming (MILP) to minimize the total power consumption of the proposed architecture, taking into account two allocation strategies, single allocation of tasks and distributed allocation. Finally, we describe additional future directions needed to establish reliability, security, virtualisation, energy efficiency, business models and standardization.

Published
2020

4. A composite resilience index for road transport networks

Author

El Rashidy, RAH and Grant-Muller, S

Abstract

This paper is concerned with the development of a composite index for the resilience of road transport networks under disruptive events. The index employs three resilience characteristics, namely redundancy, vulnerability and mobility. Two different approaches, namely, equal weighting and principal component analysis, are adopted to conduct the aggregation. In addition, the impact of the availability of real-time travel information for travellers on the three resilience characteristics and the composite resilience index is described. The application of the index on a synthetic road transport network of Delft city (Netherlands) shows that it responds well to traffic load changes and supply variations. The composite resilience index could be of use in various ways, including supporting decision makers in understanding the dynamic nature of resilience under different disruptive events, highlighting weaknesses in the network and assisting in future planning to mitigate the impacts of disruptive events.

Published
2019

6. EMPOWER. Deliverable no 5.1 EMPOWERING a reduction in use of conventionally fuelled vehicles using positive policy measures - Living Lab Plan

Author

Groenewolt, B., Hjalmarsson, A., Amelsfort, D. van, Hodgson, F., Grant-Muller, S., Sahala, S., and Weerdt, C.A. van der

Subjects
Mobility, HOI - Human Behaviour & Organisational Innovations, Traffic, Human & Operational Modelling, ELSS - Earth, Life and Social Sciences
Abstract

Through a literature and case study review ten key success factors to support the design and implementation of incentive-scheme based business models within EMPOWER promoting reduction of CFV use were identified, which will provide input to both other tasks within WP 3 as wells as tasks in other Work Packages.

Published
2016

8. A Neural Network Approach for Motorway OD Matrix Estimation from Loop Counts

Author

Mussone, L, Grant-Muller, S, and Chen, H

Abstract

A method has been developed to estimate Origin Destination (OD) matrices using a neural network (NN) model and loop traffic data collected from a UK motorway site (M42) as the primary input. The estimated ODs were validated against matched vehicle number plate data derived from the ANPR (Automatic Number Plate Recognition) cameras which were installed at all the slip roads between junctions 3a and 7 of the motorway. Key research questions were: whether it is realistic to use the full loop data, whether particular features of the data influenced modelling success, whether data transformation could improve modelling performance through variance stabilization and whether individual ODs should be estimated separately or simultaneously. The method has been shown to work well and the best results were obtained using a square root transformation of the training data and individual models for each OD.

Published
2010

12. Using the academic timetable to influence student trip-making behaviour

Author

Tomlinson, Andrew Mark, Chen, H., and Grant-Muller, S.

Subjects
388
Abstract

The university academic timetable is the framework which defines the rhythm of the term-time student activities that occur on campus. This thesis explores how the design of the academic timetable affects student trip-making behaviour to and from campus and is motivated by concerns around the environmental, social and economic sustainability of the campus-based university. The thesis investigates the current understanding of student trip-making behaviour and shows that whilst it is informally generally accepted that students may plan their trips to campus around the demands placed on their time by the academic timetable, this appointment based approach is not generally recognised in student trip models. The thesis demonstrates that it is the timetable which is the main driver of student travel demand, that changes to the timetable can influence trip-making behaviour, and that a policy of timetable compression, combined with a greater use of online resources could be employed to reduce student trips to/from campus and student presence on it, thereby making the university more environmentally sustainable. However, students with compressed timetables appear to be less engaged with their studies, and exhibit a greater degree of variation in terms of their attainment level compared with students whose timetables force them to be on campus on an almost full-time basis. Students appear to prefer timetables that limit the time they need to spend on campus, and the thesis suggests that addressing this mismatch between what students currently appear to want, and what seems to offer them the best potential academic outcome represents a major future challenge to the long term academic sustainability of the campus based university.

Published
2014

13. Modelling the reopen strategy from dynamic zero-COVID in China considering the sequela and reinfection.

Author

Wu S, Huang Z, Grant-Muller S, Gu D, and Yang L

Subjects
Humans, SARS-CoV-2, Post-Acute COVID-19 Syndrome, Reinfection, China epidemiology, COVID-19 epidemiology
Abstract

Although the dynamic zero-COVID policy has effectively controlled virus spread in China, China has to face challenges in balancing social-economic burdens, vaccine protection, and the management of long COVID symptoms. This study proposed a fine-grained agent-based model to simulate various strategies for transitioning from a dynamic zero-COVID policy with a case study in Shenzhen. The results indicate that a gradual transition, maintaining some restrictions, can mitigate infection outbreaks. However, the severity and duration of epidemics vary based on the strictness of the measures. In contrast, a more direct transition to reopening may lead to rapid herd immunity but necessitate preparedness for potential sequelae and reinfections. Policymakers should assess healthcare capacity for severe cases and potential long-COVID symptoms and determine the most suitable approach tailored to local conditions., (© 2023. The Author(s).)

Published
2023
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