Semantic-based assembly framework for the generation of travel demand

Abstract

This work applies a knowledge modelling approach in the design of a framework for the generation of travel demand for traffic simulation applications. The proposed framework is based on interchangeable modules that integrate the main stages of travel demand modelling supported by an engineered knowledge base. This approach is intended to promote greater behavioural diversity, incorporate more diverse contextual data, facilitate access to online datasets, and support users to undertake and validate investigations across a range of models and implementations. The framework provides the user with direct control to modify the schema, control the selection of data, select alternative modules to execute, and the potential to remotely retrieve data and execute modules. The framework is investigated through a prototype, which generated travel demand across a full day and performed simulation utilising two third-party traffic simulators based on the configuration by the user schema. The problem of travel demand generation was separated into discrete task modules with identification of features for alternative design or further modularisation. The prototype evaluation generated multimode travel demand that was successfully tested on third-party traffic simulators and evidenced the fitness of semantic technologies in building simulator-agnostic interchangeable framework modules that satisfy the need for configurable travel modelling. The findings of the paper also contribute to the understanding of the challenges in utilising Semantic Web technologies for implementing travel demand generation. It is proposed that the framework provides a basis to develop new and existing approaches to travel demand generation to improve modelling outcomes and adoption.