Modeling and managing network crowding and congestion in mass transit with a revenue-neutral fare incentive scheme

Abstract

This study develops a user departure time equilibrium model in a many-to-many transit network and evaluates a revenue-neutral fare incentive scheme where passengers incur a surcharge during the peak hour and obtain a reward during off-peak hours. In the user equilibrium model, passengers’ departure time choices are based on the generalized trip costs including crowding costs, queuing costs, schedule delay costs, in-vehicle costs and uniform fare costs. Equilibrium conditions are derived where passengers with the same OD incur identical equilibrium costs. A sequential algorithm is proposed to solve the user equilibrium. A bi-level optimization model is further developed to optimize the proposed incentive strategy based on the network equilibrium model. Case studies are conducted with Copenhagen M2 metro line where results yield the distributions of passengers with different OD in each service run and indicate the reduction of total equilibrium costs with the incentive strategies. We also found that upstream station passengers may incur higher trip costs with the incentive strategies as they have priority to occupy the vehicle space and thus pricing strategies imposes constraints to their choices. The proposed model and incentive schemes can provide tractable references for users and transit authorities in managing demand and relieving commuting congestions.