Design of a Multiperiod Tradable Credit Scheme under Vehicular Emissions Caps and Traveler Heterogeneity in Future Credit Price Perception

Abstract

The transportation sector is a major source of traffic congestion and greenhouse gas (GHG) emissions in urban areas. This study aims to design the system-optimal (SO) traffic management policy, i.e., multiperiod tradable credit scheme (MPTCS), for urban transportation infrastructure. Under this scheme, the central authority (CA) seeks to minimize the total system travel time while achieving a predetermined vehicular emissions standard in each period of a long-term horizon with a duration of multiple years. Because travel demand and supply are uncertain in transportation infrastructure over a long-term horizon, the CA cannot provide accurate forecasts of future credit prices (CPs) to travelers a priori, leading to traveler heterogeneity in perceiving these future CPs. It impacts travelers’ decisions about using credits or transferring them to the next period. Further, travelers perceive credit purchases in the market as monetary losses and selling credits as monetary gain. We formulate the SO MPTCS design as a bilevel model. The CA determines the credit charging and allocation schemes in the upper-level model to minimize total system travel time over a horizon constrained by the emissions standard for each period. The MPTCS equilibrium condition is formulated in the lower level where travelers decide about credit consumption and path choice to minimize their travel costs. Numerical experiments suggest that as the difference between travelers’ perception of future CPs and the actual CPs (set by the CA for various periods) increases, the effectiveness of the SO MPTCS design in minimizing total system travel time decreases unless this difference is explicitly factored in the design. Also, if the CA increases emissions standards under the SO MPTCS design, the travel costs increase.