The way we walk

For the current project we decided to use a combination of qualitativeinterpretative and quantitative-statistical methods following the concept of “across-method” triangulation [12] in order to minimise the specific limitations each applied method is restricted to.

Approaching a Typology of Pedestrian Behaviour

The current approach contains of two phases of empirical data collection including observation and inquiry techniques. Figure 1 shows the design of the current study, including two phases of empirical data collection followed by hypothesis testing and the development of a model of pedestrian mobility types.

The first heuristic phase is to hypothesise and identify basic types of pedestrian route choice behaviour and movement patterns based on motion data collected by technology based tracking techniques. In the following deductive phase the initial typology is tested using a combination of localisation technologies (outdoor: GPS; indoor: Bluetooth) and detailed semi-standardised interviews. Results of both empirical phases are subsequently related to each other in order to identify specific spatial behavioural styles for the provisional categories.

a) Heuristic Phase: Tracking

The first phase of the empirical study has been conducted in Vienna in 2007. As investigation fields a shopping centre for the indoor observations and two major shopping streets for monitoring outdoor behaviour have been chosen in order to avoid the occurrence of behavioural differences caused by different context situations. In this phase the main empirical method used for data collection consisted of unobtrusive observation (also known as “shadowing” or “tracking”).

Observation procedures started with a random selection of unaccompanied walking pedestrians and following the individual as long as possible while mapping her or his path on a digital map, recording the specific point in time and the coordinates within the map for each point of the path. After completing an observation (e.g. when the subject left the observation area or the observer lost sight of the subject), additional notes concerning visible attributes of the subjects were taken (gender, age, appearance). Figure 2 shows an example of a typical trajectory including detected stops and velocities.

The analysis procedures performed on the collected data included qualitativeinterpretative methods and multivariate analysis methods (factor analysis, cluster analysis). The following section describes initial results of the analysis of indoor and outdoor tracking datasets.

b) Experimental Results

In total, 111 individuals with a balanced gender and age ratio have been observed (outdoor: 57; indoor: 54). The collected trajectories have been analysed according to the velocity computed between each marked point in the observed path; additionally locations and durations of stops within the trajectories have been detected. Subsequently, histograms of each trajectory have been compiled, showing the proportial amount of time an individual walked at a velocity within a specific speed interval. A comparison of all histograms indicates differences in spatiotemporal behaviour in indoor and outdoor observations. Figure 3 shows that subjects observed in the indoor environment spend significantly more time standing e.g. in front or inside a shop (speed interval 1: 0-0.1 m/s) and walk in general at lower speed than subjects observed in the outdoor area.

Figure 3: Histograms of all outdoor (a) and indoor (b) observations

Clustering analysis performed on both datasets form outdoor and indoor observations produced rather diverse results. While the analysis of the outdoor data showed eight discriminative clusters, the analysis of indoor observations resulted in only three homogeneous clusters of motion behaviour. This difference might be explained by the greater diversity of potential goals pedestrians might be pursuing in the outdoor environment: On a shopping street people passing by are not necessarily there for shopping (but e.g. on their way to or from work), whereas a person entering a shopping centre usually plans to buy something.

As an example the results of the indoor analysis are now explained in more detail, as the context situation (shopping) can be assumed to be more homogeneous than outdoors. The three clusters of motion behaviour can be interpreted as “swift shoppers”, “convenient shoppers”, and “passionate shoppers”:

Swift shoppers

This group consists of 60% male and 40% female participants who are relatively young compared to the other groups. They walk at comparably high speed (on average 1.2 m/s) and stop rarely and for a very short time (7 seconds on average, up to a maximum duration of 1 minute).

Convenient shoppers

Almost two thirds of this group are male shoppers (64%). The average age lies between 35 and 40 years and is higher than in the comparison groups. They stop more frequently (on average 1.4 times per observation) and hence show a lower average speed (0.6 m/s). Stops last approximately 2.5 minutes (up to 8 minutes).

Passionate shoppers

Two thirds of this group are females (67%), aged around 30 to 35 years. They stop quite frequently (about 3.6 times per observation) and for a comparatively long time (4.7 minutes on average, maximum 17 minutes). This results in a very low average speed of 0.2 m/s.