Staggered School Schedules for the morning commute problem - An MFD-based Optimization Approach

This paper deals with the morning commute problem when two classes of commuters co-exist in an urban transportation network. While each school starts at the same time, traffic flow enters the network simultaneously, leading to the formation of a peak demand value that the network cannot fully accommodate. The task becomes more challenging when commuters head to their workplace after reaching their respective school. To tackle this issue, we propose the School Demand Allocation Paradigm (SDAP), which allows schools to have different starting times. Subsequently, we deploy an optimization framework, the target of which is to determine the optimal pair of the shifted school start time for each school that maintains operation under free-flow conditions. We utilize a macroscopic MFD-based traffic model, which can account for the coupling of the classes mentioned above. The effectiveness of the proposed approach is verified through macroscopic simulations.