Previous estimates of the magnitude of highway congestion costs have employed equations relating the external cost imposed on motorists by an additional vehicle to the speed of traffic flow or the ratio of traffic flow to the maximum capacity of the road. While those equations may be accurate for rural roads and expressways, they may be less accurate on city streets where delays at intersections are a dominant factor in congestion costs. This study replaces single speed-volume equations with a traffic simulation model that replicates the queuing of vehicles at traffic lights, the dispersion of platoons of vehicles as they move from one intersection to another, and the interaction of intersecting traffic flows on an urban street network. The model is used with actual Toronto road and traffic data to produce new estimates of congestion costs on specific streets during the morning rush hour. The model produces a surprisingly high average congestion cost during the morning rush hour and a poor correlation of the results with those that would be estimated for the same traffic flows by the single equation models. The simulation technique allows the calculation of congestion costs on a street-by-street basis, generating the detailed information that would be necessary for a complex congestion pricing scheme. TRAFFIC CONGESTION IN URBAN AREAS has long been recognized as a technological external diseconomy causing serious urban problems. Highway engineering studies show that over a range of traffic flow levels observed on city streets an increase in the volume of traffic flow will reduce the speed of that flow for all motorists. While the additional driver perceives the impact of this lower speed upon himself, he is not faced with the social costs of the time lost to all other motorists as a result of his entering the road. The private cost of using the road, as perceived by the added motorist is thus below the social cost, often by a large amount. It has been shown that if the marginal external social cost of an additional vehicle-mile can be calculated and a toll is charged to all motorists equal to this marginal external cost, a Pareto improvement in the efficiency of using the road can be achieved.2 Mohring [10] has estimated the magnitude of such tolls as a function of the volume/capacity ratio of the highway, a measure of capacity utilization. Johnson [6] calculated a similar set of tolls as a function of the speed of movement of traffic on the road. Walters [15] estimated the elasticity of costs with respect to speed or time of travel. Smeed [13] calculated congestion costs as a function of speed and of the volume/capacity ratio.