Distributive justice impact assessment using activity-based modeling with path retention
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Sustainable transportation policies seek to change people’s travel behavior by modifying the travel environment. However, the impacts of many such policies are complex and difficult to evaluate. Policy benefits and burdens may take the form of changes in transportation costs, changes in travel time, changes in energy or pollutant burden, etc. In traditional equity assessments, the distribution of costs and benefits across traditional demographic groups, such as low-income household, minority groups, individuals that do not or cannot own personal vehicles, etc. are often considered. Being able to provide an unbiased assessment of how these benefits and burdens are likely to be distributed across demographic groups of interest serves as the starting point for distributive justice (and environmental justice) analysis in transportation planning and policy assessment. The research objectives of this dissertation are to develop a modeling framework within an advanced activity-based travel demand model that can be used to assess the distribution of transportation cost and benefits across communities of interest and implement a data structure and variable tracking system that can be implemented within and across various modeling tools to ensure that data needed for equity assessment transfer between models, and that outputs from combined models can be used to assess equity impacts. The findings are that the ABM with path retention can be used to assess the distributive impact in terms of benefits and costs such as mobility, energy use, and emissions. Demographic groups of any cut can be assessed and compared effectively using the framework (provided that the travel demand model carries the required demographic variables), providing policy makes more valuable information before decision making especially for potential equity assessment. The framework can also be linked to other models such as dispersion models for other distributive equity impacts assessment in the future.