TRAFFIC FORECASTING FOR SMALL- TO MEDIUM-SIZED URBAN AREAS
operations - traffic, ridership - commuting, ridership - forecasting, ridership - forecasting, ridership - demand, place - urban
Urban areas, Travel models (Travel demand), Travel forecasting, Travel demand, Transportation industry, Transportation, Transport, Traffic forecasting, Traffic flow, Small towns, Roads, Road networks, Resource allocation, Regulatory policy, Probability, Probabilistic analysis, Policy, Policies, Networks, Improvements, Impact studies, Households, Government policy, Employment, Automobile ownership
A recently developed methodological package that can be readily applied to forecast the traffic-related impacts of a wide range of transportation-facility-related improvements is described. The package uses some of the most advanced transportation analysis techniques to predict traffic flows and measure the performance of specific highway links and the network as a whole. Also, an attempt is made to keep the data requirements to a minimum. The flexible package can assess impacts of a wide range of policy alternatives. For example, the travel demand forecasting module, based on disaggregate probabilistic choice models, offers the ability to evaluate the traffic impacts of factors ranging from changes in household automobile ownership levels to changes in zonal service employment densities. This offers small- to medium-sized urban areas valuable traffic flow forecasts that can be used as a basis to allocate scarce financial resources.
Abu-Eisheth, S, MANNERING, F, (1986) TRAFFIC FORECASTING FOR SMALL- TO MEDIUM-SIZED URBAN AREAS, ITE Journal, Volume 56, Issue 10, p. 37-42.