Fuel taxes have been the main source of transportation funding in the US for the last nearly six decades. Recently, there have been increasing concerns regarding this funding mechanism because the revenue from fuel taxes cannot keep up with the increasing needs for transportation infrastructure repair and rebuild. To address the critical needs in transportation finance, the concept of mileage fee (MF) has received much attention lately as an alternative way to generate transportation revenue. Under this concept, drivers are charged based on the total number of miles traveled and where the travel took place. Compared with fuel taxes, MF can generate stable revenue regardless of fuel efficiency or alternative fuels which are one of the major reasons for decreasing or steady revenue from fuel taxes. While the current research on MF mainly focuses on the technologies, public acceptance (such as privacy issues), and other financial considerations, few studies looked at the system effects of such a concept. MF, similar to other major transportation policies (such as congestion pricing), is expected to have significant impacts on driver behaviors. Since drivers make their decisions individually who are however connected by the traffic network, MF policy may generate complicated network effects as a result of driver’ (potentially heterogeneous) responses. The implication is that, if not thoroughly investigated and properly designed, MF may produce unintended consequences that is not desirable from either the system manger’s or the public’s perspective.

We propose in this research to conduct a comprehensive investigation about the network effects of MF to facilitate the developments of the best MF policies. In particular, this project aims to answer the following questions:

• What are the possible schemes for implement MF?

• How to model and evaluate the network effects of different MF schemes?

• How to select the best MF scheme(s) to achieve the most desirable system objectives (such as to generate revenue, to minimize congestion or emissions)?

The proposed research will produce a set of tools such as the network analysis models to evaluate the network effects of MF policies, as well as recommendations on how MF policies should be selected and implemented successfully in practice. It will provide insights to the network effects of MF and the impacts of non-unique user responses to MF implementations. The information will further facilitate policy makers to make informed decisions regarding how to successfully implement MF policies in practice to achieve the most desirable objectives.