  The distributional impacts of congestion pricing have been widely studied in
the literature and the evidence on this is mixed. Some studies find that
pricing is regressive whereas others suggest that it can be progressive or
neutral 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 been
studied in the context of passenger travel whereas freight has received
relatively less attention. In this paper, we examine the impacts of several
third-best congestion pricing schemes on both passenger transport and freight
in an integrated manner using a large-scale microsimulator (SimMobility) that
explicitly simulates the behavioral decisions of the entire population of
individuals and business establishments, dynamic multimodal network
performance, and their interactions. Through simulations of a prototypical
North American city, we find that a distance-based pricing scheme yields the
largest welfare gains, although the gains are a modest fraction of toll
revenues (around 30\%). In the absence of revenue recycling or redistribution,
distance-based and cordon-based schemes are found to be particularly
regressive. On average, lower income individuals lose as a result of the
scheme, whereas higher income individuals gain. A similar trend is observed in
the context of shippers -- small establishments having lower shipment values
lose on average whereas larger establishments with higher shipment values gain.
We perform a detailed spatial analysis of distributional outcomes, and examine
the impacts on network performance, activity generation, mode and departure
time choices, and logistics operations.
