Using Tradable Credits for Revenue-Neutral Pricing of a Bottleneck with Heterogeneous User Preferences and Value of Time

Abstract

In this research, we develop an optimal credit-based pricing scheme for a single bottleneck with time-dependent demand and heterogeneous user preferences. For this purpose, we first propose an analytical model for dynamically pricing the bottleneck. Accounting for the independent distributions of the schedule penalty factors and the value of time of the commuters can significantly improve the accuracy of the pricing strategy. Moreover, implementing such a strategy using a revenue-neutral credit-based pricing scheme allows the value of the credits to be determined by the interaction between the users in the equilibrium condition of the market. Hence, there would be no need to charge all commuters over the peak period. Instead, the proposed strategy allocates the money raised from the “credit buyers” to subsidize the commutes of the “credit sellers” in order to incentivize the commuters to form a uniform distribution of arrival times over the peak period. Using tradable credits to design a revenue-neutral pricing strategy for the bottleneck can raise public support by improving the social welfare of the users. The proposed credit-based pricing strategy also have broad applications for optimizing the urban networks using the concept of the macroscopic fundamental diagram (see Amirgholy et al., 2017).