Freight Truck Trip Generation Modelling at Regional Level

Abstract

Freight truck trip generation is a crucial part of a 4-stage model, especially in regional freight model development. Data needed to construct trip generation equations are ususally gathered at company level using the trip diary. Although this approach seems to be most suitable it may not cover all trips made by freight vehicles in analysed area. On the other hand, response rate may be unsatisfactory. Thus other methods of trip generation estimation should be explored. Based on results of roadside surveys O-D matrices for freight vehicles were estimated. In the next step, using large set of traffic measurements on national and regional roads, O-D matrices were calibrated. In order to calculate trip generations a step backwards was made. Additionally, the results of comprehensive travel studies and secondary data were used. Developed data sets were used to estimate trip generation equations, applying linear and nonlinear regression as well as artificial neural networks (ANN). The aim of this paper is to develop freight truck trip generation equations at regional level using different data sources, secondary data and indirect approaches.