Staggered work schedules for congestion mitigation: A morning commute problem*

In urban networks, traffic congestion can be curbed by deconcentrating the temporal distribution of the travel demand. In this paper, we propose an optimal staggered work schedules problem to minimize the network total travel time and prevent the schedule delay in the trips of commuters over morning peaks in a bicentric network. The objective is to optimize the work start times of individual firms with minimum deviations from their initial schedules while taking into account that commuters choose their departure time selfishly to minimize their travel cost. We formulate the optimal work schedule problem in a bicentric network as a multi-objective optimization program that simultaneously minimizes the total travel time and the schedule deviation for the firms while satisfying near-equilibrium temporal conditions. The time-varying congestion dynamics are modeled using macroscopic fundamental diagrams. We solve the optimization problem for a test network and analyze the sensitivity of the Pareto solution to the policy parameters of the model. We assess the accuracy and effectiveness of the proposed method using an individual-level trip-based macroscopic simulation model. The numerical results demonstrate that implementing the proposed optimal staggered work schedules strategy accounting for commuters' departure trip time choice can significantly reduce the traffic congestion in urban networks.