Transport and Land Use Integration
Integrated Transport and Land Use Modelling
Cities around the world are experiencing increasing urban sprawl and dependence on private vehicles, posing challenges for planning healthy communities, and reducing traffic congestion, emissions, and adverse health effects. It is well known that location choices and travel choices are interdependent decisions. Decision-making processes concerning equitable and sustainable transport choices, and land use development has become more complex than ever. Effective transport and land use planning in an integrated manner is required to trigger a shift towards balanced urban growth and sustainable travel choices for the current population and generations to come. Integrated transport and land use modelling assists in predicting the evolution of urban form and transport. These large-scale models are particularly useful for testing regional-level long-range complex land use and transport policies, such as testing how higher mixed land use and densification of urban core changes mode share, examining whether transit-oriented development increases transit ridership or not. Recently, the domain of the integrated modelling has been extended towards emission and energy estimation.
In this line of research, we are working towards developing an integrated Transport Land Use and Energy (iTLE). The iTLE is an agent-based microsimulation tool for urban systems. It is conceptualized following the life-course perspectives and theories to address the evolution of multi-domain decision interactions over the life-course of the agents. The model system has five core modules: baseline synthesis, population life-stage transition, residential location transition, vehicle ownership transition, and activity-based travel. Currently, a prototype version of the iTLE is in place for Halifax for a 15-year period from 2006-2021. The prototype iTLE predicts the housing pattern, population demographics, neighbourhood configuration, and vehicle ownership and transaction pattern over time and space.