  The traditional demand-responsive paratransit system plays an important role
in connecting people to health care, particularly those who are carless,
low-income, senior, underinsured/uninsured, or who have a disability. However,
the existing paratransit system usually has low service quality due to long
waiting times, low operation frequencies, and high costs. In order to improve
the service quality, we propose to design a new demand-responsive paratransit
system that offers public, Uber-like options for non-emergency medical
transportation. Mixed integer programming models are thus developed to optimize
the system operations with the objectives of minimizing user waiting times for
riders as well as operating costs for operators. The results produced in this
paper will assist local departments of transportation and transit agencies as
they consider operational strategies to meet non-emergency medical transport
needs.
