  As public transport operators try to resume their services, they have to
operate under reduced capacities due to COVID-19. Because demand can exceed
capacity at different areas and across different times of the day, drivers have
to refuse passenger boardings at specific stops. Towards this goal, many public
transport operators have modified their service routes by avoiding to serve
stops with high passenger demand at specific times of the day. Given the urgent
need to develop decision support tools that can prevent the overcrowding of
vehicles, this study introduces a dynamic integer nonlinear program that
proposes service patterns to individual vehicles that are ready to be
dispatched. In addition to the objective of satisfying the imposed vehicle
capacity due to COVID-19, the proposed service pattern model caters for the
waiting time of passengers. Our model is tested in a bus line connecting the
university of Twente with its surrounding cities demonstrating the improvement
in terms of vehicle overcrowding, and analyzing the potential negative effects
related to unserved passenger demand and excessive waiting times.
