Stephan Müller

Improvement of the volume-delay function by incorporating the impact of trucks on traffic flow

In current transportation modelling, travel time is the most important factor in decisions regarding transport modes, destinations and routes. The calculation of travel time is deployed by volume-delay functions (VDFs), a sub-model of route assignment procedure, using the correlation between increasing numbers of vehicles on a road and the roads restrictive capacity. By investigating existing VDFs, a clear gap is seen, demonstrating that current functions are not suited to reflect the empirically known large impact of trucks on passenger car travel times. This issue becomes crucial when transport models are used to reflect future scenarios where goods transportation is expected to increase greatly, and when transport models combine passenger and commercial traffic. This paper presents a new VDF which successfully includes trucks’ impact on traffic flow in the case of Germany and, with slight deviations, for North America. The function is developed using ideal-type data for German motorways. The differences between German and US data and their implications for VDFs are also discussed.

Analysing the Connection Between Gross Value Added of Industries and Freight Transport Demand—The Merit of Supply and Use Tables in the Identification of Relevant Economic Activities for Freight Transport Demand

A widely excepted axiom is that transport demand is driven by economic activity. Consequently there is much research on the connection between the economy and freight transport. It is also accepted that highly aggregate indicators like the GDP are not suitable for forecasting purposes of specific commodities. In this paper we analyse the connection between distinct industries and commodities. Four contentions are proved for the case of Germany based on publicly available data from 1999 to 2007: (1) gross value added (GVA) is a suitable variable to derive the amount of freight transported in a country; (2) supply and use tables help in identifying the economic activities with relevance for the transport demand of specific commodities; (3) the consideration of dynamics in GVA development is paramount for freight generation, more than the dynamics of the economic structure (i.e. the change in relevant industries for specific commodities); (4) economic activities on the consumer side of commodities (receiving industry) explain best the freight generation. These four findings are of interest for freight modelling and forecasting. They also contribute to the discussion regarding coupling and decoupling of transport from economic growth by showing that for a majority of commodities a close tie between freight transport and economic growth of specific industries exists.