The outbreak of coronavirus disease 2019 (COVID-19) has led to significant challenges for schools, workplaces and communities to return to operations during the pandemic, while policymakers need to balance between individuals safety and operational efficiency. In this paper, we present a mixed-integer programming model for redesigning routes and bus schedules for the University of Michigan (UM)s campus bus system, to prepare for students return in the 2020 Fall semester. To ensure less than 15-minute travel time for all routes and to enforce social distancing among passengers, we propose a hub-and-spoke design and utilize real data of student activities to identify hub locations and reduce the number of bus stops used in the new routes. The new bus routes, although using only 50% or even fewer seats in each bus, can still satisfy peak-hour demand in regular semesters at UM. We sample a variety of scenarios that cover variations of peak demand, social-distancing requirements, broken-down buses or no-shows of drivers, to demonstrate the system resiliency of the new routes and schedules via simulation. Our approach can be generalized to redesign public transit systems with social distancing requirement during the pandemic, to reduce passengers infection risk.
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