Quantification and forecasting of regional commercial traffic volumes based on aggregated national data

Abstract

The increasing volume of traffic in agglomeration areas makes it necessary to take better account of commercial traffic in transport planning and traffic control and to implement new solutions for the sustainable handling of commercial traffic. For this purpose, commercial transport demand models are used, which in turn are attributed with empirical data. However, the determination of key figures of economic traffic in a planning region is very complex and time-consuming. This article therefore presents a method for quantifying and forecasting regional commercial traffic volumes based on aggregated national data. It is applied exemplarily for the Munich Metropolitan Region. The method comprises the extrapolation of national sample data, the updating of outdated national behavioral data, the forecast for a target year and the cutting out of the quantity structure for the planning region. The data used are freely available. They include vehicle diaries, demographic statistics, vehicle registration statistics and employment statistics. Three categories are considered in the data: Economic sectors, vehicle types and settlement patterns. The modelling approach is validated by forecasting historical data and comparing it with verified data. Furthermore, the results are validated by reproducing key figures from independent data sources, whereby the deviations are mostly in the range of 0-10 %.