Sigrun Beige

Long-Term and Mid-Term Mobility Decisions During the Life Course: Experiences with a Retrospective Survey

Long-term and mid-term mobility of people involves on the one hand decisions about their residential locations and the corresponding moves. At the same time, the places of education and employment play an important role. On the other hand the ownership of mobility tools, such as cars and different public transport season tickets, is a complementary element in this process, which also binds substantial resources. These two aspects of mobility behaviour are closely connected to one another. A longitudinal perspective on these relationships is available from people’s life courses, which link different dimensions of life together. Besides the personal and familial history, locations of residence, education and employment as well as the ownership of mobility tools can be taken into account. These life course dimensions are usually not independent from one another. Events in one area are frequently connected to changes in other areas. At the same time, this longitudinal approach provides the possibility to observe developments over time. In order to study the dynamics of long-term and mid-term mobility decisions, a longitudinal survey covering the 20-year period from 1985 to 2004 was carried out at the beginning of 2005 in a stratified sample of municipalities in the Zurich region, Switzerland. The paper shows that there exists a strong interrelation between the two examined aspects of long-term and mid-term mobility. The residential mobility is influenced by the ownership of the different mobility tools, and vice versa. Thereby the mobility tool ownership remains comparably stable over longer periods of time. Concerning the ownership of the various mobility tools, the analyses indicate that car ownership and public transport season ticket ownership substitute one another. During the life course car ownership is highest among those who are 35 to 55 years old today. At the same time, men have noticeably more frequently a car at their disposal than women of the same age. Concerning the ownership of national and regional season tickets, the opposite trend is visible. Open Access Article

Who gets the key first? Car allocation in activity-based modelling

ABSTRACT Decisions concerning household car ownership and the corresponding usage by the household members have significant implications on vehicle usage, fuel consumption and vehicle emissions. In this context, long-term and short-term choices which are strongly interrelated with one another play an important role. The long-term aspects involve the number of vehicles and their different types owned by a household as well as the assignment of a main driver, acting as the primary user, to each vehicle. The short-term dimension is represented by the vehicle allocation within a household at a daily level. In order to better understand the vehicle allocation process in the household context, the paper at hand investigates the importance of the short-term and long-term aspects in this process and explores several approaches to model them. For this purpose, four different methods for car allocation within a household, which strongly differ in their complexity, are implemented into a microscopic agent-based travel demand model and subsequently evaluated. The respective approaches are the following: (1) random car allocation, (2) car allocation by age, (3) car allocation by main driver assignment, and (4) car allocation by household optimization. Given a population of a bigger region that is described by a set of attributes, these various models determine which person of a household uses one of the available cars within the household for his/her daily trips. The simulations show that all four implementations of car allocation result in good representations (with deviations of less than 10%) of observed travel behaviour, their results being closer to each other than initially expected. Model (4), which optimizes car allocation for the entire household, shows the best results when compared to real-world data, while model (3) allows for the adaptation of changes in car ownership and/or socio-demographic and socio-economic attributes of the population.

Embedding intermodal mobility behavior in an agent-based demand model

Abstract Intermodality is the combination of different modes of transport along a single, seamless trip. It is assumed to reduce the amount of emissions generated by transport and being healthier for the users than conventional monomodal trips using passenger cars due to incorporating active modes of transport. In parallel, it promises to be competitive with passenger cars in terms of travel time. For determining the effects of measures that target at increasing the rate of intermodal trips, demand models that replicate the possibility to combine different modes of transport are needed. Herein, the extension of the agent-based demand model TAPAS for incorporating intermodal trips is presented. The given preliminary results show that the system is capable to compute the correct number of intermodal trips.