Overview
The main objective of this project was to conduct travel survey in Frauenfeld and the surrounding areas in Canton Thurgau from August until December 2003.
Within the project, a six week travel survey has been conducted among 230 persons from 99 households in Frauenfeld and the surrounding areas in Canton Thurgau from August until December 2003. The design of the survey was built on the questionnaire used in the German project Mobidrive, but it was developed further set of questions. All trip destinations of the survey have been geocoded. Route alternatives for private motorised transport and public transport have been calculated.
Moreover, the collected data have been compared with the National Travel Survey 2000 (Mikrozensus zum Verkehrsverhalten 2000).
In order to check for possible fatigue effects of the amount of reported trips, several GLM (Generalised Linear Model) and poisson regression models have been estimated besides descriptive analysis.
Funding
Results
The analyses of the variability and of the rhythm as well as that of the imiovation have revealed that travel behaviour is highly conditioned by habits and routines. Nevertheless, new trip destinations are added continuously, particularly for leisure travel. The majority of trips have been planned at least one or more days in advance. Moreover, it could be shown that the rhythms and therefore the temporal structure are partly dependent on the socio-demographic characteristics of the respondents, although it is just one determinant within the demand structure. The activities themselves can be divided into groups with daily, bi-daily and weekly rhythms and without a temporal structure.
In addition, the spatial dimension and distribution of trip destinations as well as the extent of activity spaces over the reporting period has been analysed through confidence ellipses, a two-dimensional version of the well-known confidence interval, and kernel density estimates of activity density.
The data base generated within the project is an important prerequisite to better understand and model the complex connection of transport supply, activity planning and execution as well as destination, mode and route choice. With this knowledge it is possible to better assess the effects of measures, particularly those which have a direct impact on daily routines.