Coarse Preference Reporting in the Bottleneck Model: Approximate Strategyproofness and Efficiency

Abstract

A central operator schedules each vehicle's passage time through a bottleneck to achieve a dynamic system optimum (DSO). The assignment depends on each vehicle's preferred arrival time, which is private and must be elicited from each vehicle. Mechanisms that elicit exact preferences, such as the Vickrey-Clarke-Groves (VCG) mechanism, can achieve strategyproofness but involve relatively complex rules and a computational burden on the operator. We focus instead on coarse reporting, in which each vehicle selects from a finite menu of time slots of a common width. This discrete interface already structures reservation and appointment systems in practice, including managed lanes for automated vehicles, airport slot allocation, and delivery appointment windows. We design a slot-based DSO mechanism on this coarse interface, in which the operator implements DSO assignment based on the reported slots and charges a capacity shadow price as a toll, and evaluate its performance. We prove that both the worst-case misreporting gain and the expected efficiency loss decrease quadratically in the slot width. The efficiency loss decays in this way under binding capacity, while the worst-case misreporting gain requires an additional condition on the preferred arrival time distribution and the schedule cost function. Analyzing the no-toll case, we find that the misreporting incentive persists, however finely the slots are refined, indicating that the toll also serves to elicit truthful reports. Numerical experiments support these theoretical results and show that they continue to hold in parameter regions outside the sufficient conditions.