The standard method for predicting traffic flows on urban road networks, called static traffic assignment, is based on the principle that drivers seek their own least cost routes from their origins to their destinations. This principle corresponds to a network user equilibrium in which all used routes have equal costs and no unused route has a lower cost, for every origin-destination pair. Under somewhat mild assumptions, the network equilibrium problem can be formulated as a convex optimization problem with linear constraints, and solved with an iterative algorithm. The precision and speed of such solutions has increased remarkably during the past ten years. Although the total flows on links of the urban road network are uniquely determined in the solution of this formulation, route flows and link flows of cars and trucks are not. An additional assumption, called the condition of proportionality, is invoked to determine these route and link flows uniquely and in a behaviorally plausible manner. This assumption is also the basis for solving these problems in a new algorithm, Traffic Assignment by Paired Alternative Segments (TAPAS). In this paper, the findings of computational experiments pertaining to two network representations are presented. The network representations pertain to restrictions on the use of certain links of the network by trucks in an assignment of cars and trucks. The findings are presented in a way that transportation planning professionals may find helpful in understanding the importance of network representations, multiple-class assignments and the condition of proportionality to their travel forecasting practice.