Modeling transit travel times for predicting equity improvements

Equity in accessibility through public transit services is an important and growing concern in many countries, including the USA. There is much research that suggests methods and procedures for defining and measuring this equity, but there is little research that investigates the potential impacts of transit system service adjustments on equity. Using survey data estimates for racial minority populations and spatial data for goods and services locations, this research demonstrates an opportunity to predict transit equity improvements through a case study with the transit provider in Eugene, OR. In this case study, regression analysis is used to determine the effects of varying the number of transit vehicles assigned to existing transit routes at various times of the day on the travel times of prospective riders. A commonly employed needs gap method is then used to define current equity levels and to compare to the predicted equity levels after vehicle reassignment. The results of the case study suggest that even relatively small, targeted service adjustments can positively impact the levels of access equity seen in a transit system. This research concludes that even while trade-offs in equity levels are likely unavoidable, overall net equity improvements are possible through conscientious, data-driven redistribution of public transit assets.