  We model and study the problem of assigning traffic in an urban road network
infrastructure. In our model, each driver submits their intended destination
and is assigned a route to follow that minimizes the social cost (i.e., travel
distance of all the drivers). We assume drivers are strategic and try to
manipulate the system (i.e., misreport their intended destination and/or
deviate from the assigned route) if they can reduce their travel distance by
doing so. Such strategic behavior is highly undesirable as it can lead to an
overall suboptimal traffic assignment and cause congestion. To alleviate this
problem, we develop moneyless mechanisms that are resilient to manipulation by
the agents and offer provable approximation guarantees on the social cost
obtained by the solution. We then empirically test the mechanisms studied in
the paper, showing that they can be effectively used in practice in order to
compute manipulation resistant traffic allocations.
