Investigating Transportation Equity in Maryland: An AI-Based Approach

Abstract: Unequal mobility and accessibility have been a key constraint in accessing jobs, education and healthcare and other opportunities across the nation. This is aggravated by differences in income, transport infrastructure, transit and indeed all modes, vehicle availability, class of workers and other variables which individually or collectively contribute to the commute inequity. Evaluating these can be challenging because there are types of equity and impacts to consider including horizontal and vertical commute equities and various ways to measure them. Horizontal equity assumes that people with similar needs and abilities should be treated equally; vertical equity assumes that disadvantaged groups should receive a greater share of resources.     The present research process involves examining and measuring commute equity as a dependent variable, which is determined by a function of independent variables such as vehicle availability, worker participation rates, travel time/time arriving, class/type of worker, mode choices, and other crucial components. Different variations of the regression model will be employed to analyze the relationship between the independent variables and commute equity. These regression models will serve as tools to quantify the impact of each independent variable on commute equity and gain insights into the factors contributing to transportation inequities. The accuracy of each regression model will be thoroughly examined to assess their predictive performance in estimating commute equity. The results obtained from each model will be described and analyzed in detail to provide a comprehensive understanding of the relationships between the independent variables and commute equity outcomes.    Based on the derived results, the research project will formulate informed recommendations aimed at guiding policymakers in improving inclusivity and accessibility within transportation systems. These recommendations will take into account the identified influential variables and their impacts on transportation equity, providing practical strategies to address inequality and enhance equity within the studied neighborhoods and beyond.