Development of an Accessibility Formulation to Measure Customers’ Evaluations of Demand Responsive Transit (DRT) Systems

PI: Chandra Bhat

Demand response transit (DRT) is a critical form of transportation for mobility-impaired, low income, elderly, and rural populations in Texas. There are 38 rural transit providers in Texas, and all of them contend with challenges specific to the characteristics of the area and the profile of their respective DRT markets. As populations in these rural communities age, or when elderly population from other areas move into these areas, the challenges will get amplified, potentially resulting in reduced mobility and stunted economic growth. In addition, the prevalence of multiple service providers with different agendas and jurisdictions further complicates the effective administration and optimization of DRT service. While the earlier DRT tool developed for the TxDOT-Public Transportation (TxDOT-PTN) Division helped in assessing the accessibility levels in a detailed manner, there are several limitations. The earlier tool could not handle multiple service providers, seasonal changes in demand patterns, different demand patterns and operating hours on different days of the week, and trips with one end outside the service area. Moreover, the models were estimated using data from only one DRT operating in Brownsville, Texas, and the models were applied using the dated 2000 Census data. In this project, we will classify the 38 DRT service providers into one of much fewer and distinct categories, and estimate models specific to each of these categories. The intent is that the existing DRT tool will be customized for each category, and then may be used by all DRT agencies within the category after modifications to fleet characteristics and demographic characteristics (but the behavioral model parameters embedded in the model will remain the same for agencies in each category). The tasks involved in this project include identifying participant transit providers, collecting and assembling available data, estimating new models of patron demand and scheduling, updating the existing DRT accessibility tool that can then be used for proactive DRT planning, conducting a DRT accessibility sensitivity analysis, and identifying final recommendations.