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The distributional impacts of congestion pricing have been widely studied inthe literature and the evidence on this is mixed. Some studies find thatpricing is regressive whereas others suggest that it can be progressive orneutral depending on the specific spatial characteristics of the urban region,existing activity and travel patterns, and the design of the pricing scheme.Moreover, the welfare and distributional impacts of pricing have largely beenstudied in the context of passenger travel whereas freight has receivedrelatively less attention. In this paper, we examine the impacts of severalthird-best congestion pricing schemes on both passenger transport and freightin an integrated manner using a large-scale microsimulator (SimMobility) thatexplicitly simulates the behavioral decisions of the entire population ofindividuals and business establishments, dynamic multimodal networkperformance, and their interactions. Through simulations of a prototypicalNorth American city, we find that a distance-based pricing scheme yields thelargest welfare gains, although the gains are a modest fraction of tollrevenues (around 30\%). In the absence of revenue recycling or redistribution,distance-based and cordon-based schemes are found to be particularlyregressive. On average, lower income individuals lose as a result of thescheme, whereas higher income individuals gain. A similar trend is observed inthe context of shippers -- small establishments having lower shipment valueslose on average whereas larger establishments with higher shipment values gain.We perform a detailed spatial analysis of distributional outcomes, and examinethe impacts on network performance, activity generation, mode and departuretime choices, and logistics operations.

Evaluating congestion pricing schemes using agent-based passenger and freight microsimulation