Matthias Kowald

An agent-based random-utility-maximization model to generate social networks with transitivity in geographic space

Stochastic actor-based approaches receive increasing interest in the generation of social networks for simulation in time and space. Existing models however cannot be readily integrated in agent-based models that assume random-utility-maximizing behavior of agents. We propose an agent-based model to generate social networks explicitly in geographic space which is formulated in the random-utility-maximizing (RUM) framework. The proposed model consists of a friendship formation mechanism and a component to simulate social encounters in a population. We show how transitivity can be incorporated in both components and how the model can be estimated based on data of personal networks using likelihood estimation. In an application to the Swiss context, we demonstrate the estimation and ability of the model to reproduce relevant characteristics of networks, such as geographic proximity, attribute similarity (homophily), size of personal networks (degree distribution) and clustering (transitivity). We conclude that the proposed social-network model fits seamlessly in existing large-scale micro-simulation systems which assume RUM behavior of agents.

Insights into a spatially embedded social network from a large-scale snowball sample

Abstract Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals’ characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

Within-Day Replanning of Exceptional Events

Typical software used in the simulation of traffic behavior focuses on scenarios describing common situations, such as an ordinary working day without remarkable incidents. To simulate such scenarios, iterative approaches are used. They assume that the people simulated adapt to previous iterations’ results. Such iterative approaches produce meaningful results for various scenarios only when typical, repetitive situations are modeled. However, a scenario may also contain incidents that occur randomly, and thus substantially increase a models complexity. In such scenarios, an iterative approach would produce illogical and even erroneous results. Within-day replanning is an attempt to handle such scenarios. This paper describes problems that arise when an iterative simulation approach is applied to a scenario with exceptional events. The within-day replanning technique is introduced and implemented in the multiagent transport simulation framework, allowing simulated agents to replan the routes between their activities while they are traveling. By doing this, agents can take current traffic conditions into account, an important requirement for scenarios containing unpredictable incidents such as road accidents. The implementation capability is demonstrated by conducting experiments in which capacities of several arterial roads in the city center of Zurich, Switzerland, are reduced as the result of an exceptional event. It is demonstrated that agents affected by those events are able to reduce their travel times if they replan their routes by using within-day replanning.

Individuals’ spatial social network choice: model-based analysis of leisure-contact selection

Leisure travel holds an important share of the overall amount of travel. However, efforts in transport planning to model and explain leisure travel have been rather limited for a long time. Only recently, a subcommunity of researchers began to use the methods of social network analysis. Existing research in this area, however, has focused on social interaction behaviour of individuals given their social networks. The selection of friends underlying the generation of social networks has received less attention. To fill this gap, our aims in this study are a descriptive analysis of leisure network data, and specification and estimation of a utility-based friendship-decision model. Data on connected personal leisure networks are obtained by using the personal network approach in an extended survey framework. Results offer insights into the decision of who is in contact with whom and which combinations of attributes have either an increasing or decreasing effect on the utility of a leisure relationship. The model can be used to simulate social network generation in an agent-based travel-demand simulation and with that enable the consideration of relevant behavioural patterns in the simulation of leisure trips.

Die Verbindung zwischen Verkehrsplanung und sozialen Netzwerken

Die Verkehrsplanung versucht die Entscheidung von Personen wahrend der Ausfuhrung von Aktivitaten des taglichen Lebens zu beschreiben, zu verstehen und zu modellieren (Ortuzar und Willumsen 2001). Das zugrunde liegende Paradigma dabei ist, dass das Individuum versucht, seine Bedurfnisse zu befriedigen, wahrend es seinen Nutzen durch die Ausubung von Aktivitaten maximiert. Dazu mussen unterschiedliche Orte aufgesucht werden. Dabei werden in der Verkehrsplanung hauptsachlich die Raumnutzungsstrukturen, welche Aktivitaten ermoglichen, die generalisierten Kosten der Nutzung der verfugbaren Infrastrukturen, welche Zugang zu den Raumnutzungsstrukturen schaffen und die Eigenschaften der Personen als Randbedingungen betrachtet. Lange Zeit waren Aspekte sozialer Interaktionen keine Erklarungsansatze fur das Verkehrsverhalten. Dies lag vor allem an den Schwierigkeiten, solche Daten zu erheben und der Darstellung von Verkehr als zonenaggregierte Herkunfts-Zielortflusse, welche fur die Bedurfnisse der Raumplanung als zufriedenstellend prazise angesehen wurden.