A Model of Risk-Sensitive Route-Choice Behavior and the Potential Benefit of Route Guidance

In this paper, we present a simulation-based investigation of the potential benefit of route-guidance information in the context of risk-sensitive travelers. We set up a simple two-route scenario where travelers are repeatedly faced with risky route-choice decisions. The risk averseness of the travelers is implicitly controlled through a generic utility function. We vary both the travelers' sensitivity toward risk and the equipment fraction with route-guidance devices and show that the benefits of guided travelers increase with their sensitivity toward risk

The Role of Spatial Interaction in Social Networks

This article addresses the role of spatial interaction in social networks. We analyse empirical data describing a network of leisure contacts and show that the probability to accept a person as a contact scales in distance with similar to d (-aEuro parts per thousand 1.4). Moreover, the analysis reveals that the number of contacts an individual possesses is independent from its spatial location and the spatial distribution of opportunities. This means that individuals living in areas with a low accessibility to other persons (rural areas) exhibit at average the same number of contacts compared to individuals living in areas with high accessibility (urban areas). Low accessibility is thus compensated with a higher background probability to accept other candidates as social contacts. In addition, we propose a model for large-scale social networks involving a spatial and social interaction between individuals. Simulation studies are conducted using a synthetic population based on census data as input. The results show that the model is capable of reproducing the spatial structure, but, however, fails to reproduce other topological characteristics. Both, the analysis of empirical data and the simulation results provide a further evidence that spatial interaction is a crucial aspect of social networks. Yet, it appears that spatial proximity does only explain the spatial structure of a network but has no significant impact on its topology

Enhancing MATSim with capabilities of within-day re-planning

This paper presents a framework for simulation of within-day re-planning for the MATSim project. Three major building blocks are presented, each of which represents specific aspects of driver behavior. These components comprise (i) the provision of descriptive information in the form of link travel costs, (ii) prescriptive information in the form of routes, and (iii) a model of driver satisfaction. An exemplary model is presented, which focuses on en-route re-planning under different types of information provision. In this model driver perception is constrained to link traversal costs and decisions are made by application of a standard shortest path algorithm. The satisfaction of a traveler is modeled with a scoring (utility) function that evaluates routes as well as activities travelers are aiming at. The framework's applicability is tested with a simple fictive network and a real-world network of Greater Berlin

Distributed intelligence in pedestrian simulations

In order to accurately simulate pedestrian behaviour in complex situations, one is required to model both the physical environment and the strategic decision-making of individuals We present a method for integrating both of these model requirements, by distributing the computational complexity across discrete modules. These modules communicate with each other via XML messages. The approach also provides considerable flexibility for changing and evolving the model. The model is explained using an example of simulating hikers in the Swiss Alps.SNF, NFP 48, Habitats and Landscapes of the Alp

A model for spatially embedded social networks

This paper presents a stochastic model for spatially embedded social networks based on the ideas of spatial interaction models. Analysing empirical data, we find that the probability to accept a social contact at a certain distance follows a power law with exponent -1.6. With a simulation where the spatial distribution of vertices is defined by a synthetic population of Switzerland, we can reproduce the edge length distribution observed in the empirical data as well as some other typical properties of social networks

Collecting data on leisure travel: The link between leisure contacts and social interactions

The aim of a new survey project is to collect data on the link between leisure contacts and leisure activities. The paper introduces briefly into former studies that applied the methods of social network analysis in transport planning. Using these projects as starting points the methodology and background of the new project are presented in detail. This is followed by first descriptive analyses checking how representative the data are for the Swiss population. The paper finishes by giving an outlook on further work and next steps to analyze the data

Soziale Netzwerke und kooperatives Mobilitätsverhalten

Ein Großteil des Verkehrsaufkommens und der Verkehrsleistung ist allein dem Freizeitverkehr zuzuordnen. Der Forschungsstand in der Modellierung des Freizeitverkehrs ist allerdings weniger fortgeschritten als in der Modellierung des Pendlerverkehrs. Dies ist unter Anderem dadurch zu begründen, dass der Freizeitverkehr eine sehr heterogenes Segment darstellt und die Datengrundlage deutlich geringer ist. Studien zu Freizeitaktivitäten legen nahe, dass Freizeitaktivitäten nicht allein durch den Zweck der Erholung oder Unterhaltung motiviert sind, sondern auch durch das Bedürfnis des physischen Kontakts zu Personen aus dem sozialen Netzwerk motiviert sind. In der Verkehrswissenschaft stellt die Rolle sozialer Netzwerke einen Themenkomplex dar, der immer mehr an Bedeutung gewinnt. Diese Dissertation leistet einen Beitrag zu diesem Forschungsthema, in dem sie die Frage beantwortet, in wie weit das soziale Netzwerk für die Modellierung des Freizeitverkehrs relevant ist. Zu diesem Zweck werden drei Arbeitspakete behandelt: (i) Analyse eines sozialen Netzwerks von Freizeitkontakten, (ii) Modellierung und Simulation eines räumlich eingebetteten sozialen Netzwerks und (iii) Modellierung und Simulation eines Ortswahlmodell für Freizeitaktivitäten unter Einbeziehung eines sozialen Netzwerks. Das erste Arbeitspaket basiert auf einem sozialen Netzwerk von Freizeitkontakten, welches in der Schweiz zwischen 2009 und 2011 erhoben wurde. Dieses Netzwerk wird insbesondere hinsichtlich seiner räumlichen Struktur untersucht. Ein wesentliches Ergebnis dieser Untersuchung ist, dass die Wahrscheinlichkeit eine Person in Distanz als sozialen Kontakt zu akzeptieren mit dem Potenzgesetz ~ d^−1.4 skaliert. Auf Grundlage weiterer Beobachtungen wird die Hypothese aufgestellt, dass die Topologie des Netzwerks unabhängig von der räumlichen Struktur ist. Obige Hypothese wird durch Simulationsstudien zweier Netzwerkmodelle unterstützt. In einem naiven Modell wird nur die Wahrscheinlichkeit eine Person in einer gegebenen Distanz zu akzeptieren vorgegeben, woraus sich dann die Topologie und die räumliche Struktur des Netzwerks ergeben. In einem Verbundmodell wird der Prozess welcher die Topologie beschreibt und jener der die räumliche Struktur beschreibt in zwei unabhängigen Schritten modelliert. Simulationsergebnisse des naiven Modells zeigen eine deutliche Korrelation zwischen Topologie und räumlicher Struktur, welche jedoch nicht in den empirischen Daten identifiziert werden kann. Dagegen kann das Verbundmodell die empirischen Beobachtungen hinsichtlich Topologie, räumlicher Struktur und Korrelation beider Aspekte korrekt reproduzieren. Dies ist ein Indiz dafür, dass die Topologie und die räumliche Struktur eines sozialen Netzwerks aus zwei weitgehend unabhängigen Prozessen resultieren. Im letzten Arbeitspaket werden zwei Simulationsmodelle zur Ortswahl im Freizeitverkehr gegenüber gestellt. Die Modelle unterscheiden sich dahingehend, dass im ersten Modell Entscheidungsprozesse unabhängig ablaufen während im zweiten Modell Entscheidungsprozesse kooperativ ablaufen. Wer mit wem kooperiert wird durch das soziale Netzwerk bestimmt. Beschränkt man die Analyse auf eine makroskopische Betrachtung, d.h. auf die Distanzverteilungen und Zeitstruktur, so können beide Modelle so kalibriert werden, dass sie die empirischen Beobachtungen reproduzieren. Hinsichtlich einer mikroskopischen Analyse ist das zweite (kooperative) Modell dem ersten Modell in seiner Erklärungskraft deutlich überlegen. Zusammengefasst ist die Beantwortung der Frage nach der Relevanz sozialer Netzwerke in der Modellierung des Freizeitverkehrs zweigeteilt: Einerseits kann ein Modell ohne soziale Netzwerke hinsichtlich einer makroskopischen Betrachtung so kalibriert werden, dass es die gleichen Resultate wie ein Modell mit sozialen Netzwerken liefert. Andererseits repräsentiert es somit nur eine statistische Approximation mit vergleichsweise limitierter verhaltenstechnischer Grundlage. Dies stellt die Prognosefähigkeit des Modells in Frage. Ein Modell mit Berücksichtigung sozialer Netzwerke bietet dagegen eine plausible und intuitive verhaltenstechnische Grundlage, welche auch mikroskopische Prozesse erklären kann.Leisure travel represents the dominating travel segment with respect to number of trips and mileage. In Germany, about one third of trips is related to leisure travel. Models for the forecasting of travel demand, however, usually focus on commuter travel and treat leisure travel, if at all, as a homogeneous travel segment, which is assumed to be similar to commuter travel. Yet, studies on leisure activities show that they differ considerably from other activities, especially with respect to distances travelled and activity duration, and generally feature more heterogeneity. Leisure activities are not only for the purpose of recreation and entertainment but also do meet friends and acquaintances. For instance, going to a restaurant is not only motivated by the necessity to get something to eat, it is also, if not predominantly, motivated by the need to socialise with other people. Thus, it is not only the question of "where", "when", and "what" but also of "with whom". The answer to the question of "with whom" is given by the social network. The role of social networks represents a subject that gains increasing attention in transport research. This dissertation contributes to this research field by answering the question to what extend social networks are relevant for the modelling of leisure travel demand. For that purpose, three work packages are treated: 1. Analysis of a social network of leisure contacts. 2. Modelling and Simulation of a spatially embedded social network. 3. Modelling and Simulation of a location choice model for leisure activities that accounts for a social network. The first work package is based on a social network of leisure contacts surveyed between 2009 and 2011 in Switzerland. This network is analysed with special focus on its spatial structure. A key finding of the analysis is that the probability to accept a person in distance d as a social contact scales with the power-law ~d^-1.4. This law holds for the entire distance scale and is independent from the location of the decision maker. Based on further observations, the hypothesis is proposed that the topology is independent from the spatial structure of the network. For instance, the number of contacts per person does not depend on the location and is thus independent from the accessibility of other contact opportunities. The above hypothesis is supported by simulation experiments with two network models. In a naive model, only the probability with which a person in distance d is accepted is given from which then the topology and spatial structure of the network emerges. In a composite model, the processes that governs the topology and the one that governs the spatial structure are modelled as two independent steps. Simulation results of the naive model show a strong correlation between topology and spatial structure, which, however, is not identified in the empirical data. To the contrary, the composite model reflects the empirical observations with respect to topology, spatial structure, and correlations between both aspects. This indicates that the topology and the spatial structure of a social network result from two almost independent processes. In the last work package, two location choice models for leisure activities are compared. In the reference model, the decision making process is modelled as independent from other actors. In the cooperative model, actors are organised in activity groups with which they conduct joint activities. The composition of activity groups is defined by the social network. In the reference model, trip distances are controlled by the marginal utility of performing an activity. In the cooperative model, trip distances can be additionally controlled by an extra utility the actors gain for joint activities. Restricting the analysis to a macroscopic perspective, that is, to trip distance distributions and activity timing, both models can be calibrated so that they both reflect the empirical observations. With respect to a microscopic perspective, the cooperative model features much more explanatory power compared to the reference model. For instance, the empirical observation that if the number of activity participants increases, the average distance to the joint activity decreases, can only be reproduced by the cooperative model. In summary, the answer to the relevance of social networks in leisure travel demand models is twofold: On the one hand, a model without social networks can be calibrated so that it yields the same results as a model with social networks. On the other hand, the reference model represents just a statistical fit with a limited behavioural basis. This renders the forecasting power of the model questionable. A model that accounts for social networks, however, is based on a sound and intuitive behavioural basis and is moreover able to reflect microscopic processes

A model of risk-sensitive route-choice behaviour and the potential benefit of route guidance

In this paper, we present a simulation-based investigation of the potential benefit of route-guidance information in the context of risk-sensitive travelers. We set up a simple two-route scenario where travelers are repeatedly faced with risky route-choice decisions. The risk averseness of the travelers is implicitly controlled through a generic utility function. We vary both the travelers' sensitivity toward risk and the equipment fraction with route-guidance devices and show that the benefits of guided travelers increase with their sensitivity toward risk