Vermessungsdaten - OpenStreetMap - In-Situ-Experimente. Die Datengrundlage von URWalking

Fußgängernavigationssysteme benutzen für die Zielführung idealerweise auffällige Objekte (Landmarken). Die Nachteile bisheriger Verfahren zur Gewinnung dieser Objekte können durch die Erfassungin alltäglichen Navigationssituationen mit Hilfe einer Smartphone-Applikation umgangen werden. Im Folgenden werden nötige Vorarbeiten zur Umsetzung einer solchen Anwendung beschrieben: Zunächst müssen verschiedene Datenbestände auf ihre Eignung hin geprüft werden. Anschließend müssen diese Daten integriert und deren Heterogenität auf verschiedenen Ebenen überwunden werden

Empirically Measuring Salience of Objects for Use in Pedestrian Navigation

Humans usually refer to landmarks when they give route directions to pedestrians. One of the reasons why current mobile pedestrian navigation systems do not yet mimic this mode of communication is the lack of available data sources. The usefulness of a crowd-sourced data acquisition approach to overcome this problem has long been mooted. However, to date no empirically sound way of measuring the salience of objects by means of surveys exists. GOAL Given this background, this doctoral work has three goals: 1. To achieve a sound way of measuring salience and its subdimensions, i.e. visibility in advance, cognitive salience, prototypicality, structural salience, and visual salience based on taking dimensions revealed in earlier studies systematically and simultaneously into account. 2. To find subgroups of visual features among the large number of visual attributes known from the literature. 3. To find the most important subdimensions of salience by means of estimating two different structural equation models. Model I is based on assumptions of independence among subdimensions, whereas model II reflects hypotheses of mediation. Taken as a whole, achieving these goals will foster both, the advancement of theories of salience and landmark acquisition methods. METHODOLOGY A large scale, in-situ experiment was implemented, trying to overcome weaknesses of earlier attempts made to estimate salience. An appropriate sample size of buildings and non-buildings was calculated a priori (nobj = 360). Objects were randomly selected based on their geographical coordinates and randomly grouped into nr = 55 routes. Participants were required to rate objects by means of a survey. The questions were derived from empirical evidence found in earlier studies. Each route was walked by two different participants (n = 112), id est (i.e.) two ratings per object were collected for data analysis. FINDINGS Model I and model II were analyzed using PLS Path Modeling and consistent PLS Path Modeling, respectively. The measurement models proposed showed a good fit, although some weaknesses were identified for prototypicality and cognitive salience. Geometrical aspects as well as features like (visual) age turned out to have a stronger impact on visual salience than color. Model I did not yield reasonable structural model results based on consistent Partial Least Squares Path Modeling. Model II, however, showed that visual salience had a very high impact on visibility in advance which, in turn, heavily influenced structural salience. An analysis of the predictive capabilities of model II revealed important, but rather small effects. VALUE OF WORK This doctoral work adds to salience models as well as to its empirical, survey-based, in-situ measurement. The results of the mediation analysis as well as the predictive capabilities of model II suggest that important subdimensions of salience are missing in current theories. Emotional salience and familiarity are identified as two candidate constructs. The structural relationships found during the analysis of model II provide, in combination with the measurement model results, a sound basis to choose important features for surveys which are usable to gain crowd-sourced salience ratings. Furthermore, several important aspects for future studies are identified. These include heterogeneity analyses for different subgroups of users of pedestrian navigation systems as well as local environments different to the historic one used in this study