Simplified Traffic Forecasting Process for Small Cities

Abstract

Urban transportation studies cost roughly 1 dollar/capita with approximately 50% of the expenditures consumed in the collection of data on travel habits. Many small cities, those 50 000 population and under, have limited budgets for data collection and analysis. In addition, the conventional urban transportation planning process is not only expensive but may be out of scale in terms of the order of magnitude of transportation decision-making in small cities.The simplified traffic forecasting process suggested in this paper requires a minimum amount of data collection and relies to some extent on travel parameters taken from cities of similar size and characteristics. Thus, the problem of costly home-interview surveys is avoided in addition to the fact that the model can be quickly updated by hand. The simplified model is based on the premise that travel time does not affect trip distribution to any extent due to the fact that significant differences in travel times between short and long trips are not perceived by the trip maker. The model was applied to the town of Fort McMurray which is the residential and operations base for the development of Alberta's Tar Sands. Comparisons of model output with traffic counts show that the simplified model gives reliable results.