One strategy for addressing uncertain roadway conditions and travel times is to provide real-time travel information to drivers through variable message signs, highway advisory radio, or other means. However, providing such information is often costly, and decisions must be made about the most useful places to inform drivers about local conditions. This paper addresses this question, building on adaptive routing algorithms describing optimal traveler behavior in stochastic networks with en route information. Three specific problem contexts are formulated: routing of a single vehicle, assignment of multiple vehicles in an uncongested network, and adaptive equilibrium with congestion. A network contraction procedure is described which makes an enumerative algorithm computationally feasible for small-to-medium sized roadway networks, along with heuristics which can be applied for large-scale networks. These algorithms are demonstrated on three networks of varying size.