Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.780223
Title: Semantic-based framework for the generation of travel demand
Author: Albiston, Gregory L.
ISNI:       0000 0004 7965 9122
Awarding Body: Nottingham Trent University
Current Institution: Nottingham Trent University
Date of Award: 2019
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Abstract:
Traffic and transportation have a wide-ranging impact on the daily lives of the human population and society. Activity-based travel demand generation models and traffic simulators are tools that have been developed to investigate traffic and transport problems and assist in developing solutions. The closer modelling of human behaviour, the emergence of new technologies and the availability of more detailed datasets is leading to greater modelling complexity. The robustness of conclusions in investigations is supported by comparison of multiple techniques and models yet variations in the platform, data requirements and dataset availability present barriers to their breadth. This thesis investigates the development of a Semantic Web framework for activity-based travel demand generation. It is proposed that the application of a knowledge-based approach and development of an orchestrating framework will enable a loosely coupled modular architecture. This approach will reduce the burden in preparing and accessing datasets through the construction of a platform-independent knowledge-base and facilitate switching between modules and datasets. The principal contributions of this work are the application of a knowledge-based approach to travel demand generation; the development of a Semantic-based framework to control the configuration of the process and the design; and demonstration of the Semantic based framework through the implementation and evaluation of the modular travel demand generation process, including integration with two third-party traffic simulators. The investigation found that the proposed approach can be successfully applied to model and control the travel demand generation process. Multiple configurations were explored, including utilising network communications, and found that this had a noticeable impact on execution duration but also the potential for mitigation through distributed computing. This presents the opportunity for an online infrastructure of datasets and module implementations for travel demand generation that users can select and access through the framework. This infrastructure would remove the need for ad hoc interfaces; data format conversion or platform dependence to facilitate the process of traffic modelling becoming quicker and more robust.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.780223  DOI: Not available
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