# 3D Space-Time Visualization of Player Behaviour  in Pervasive Location-Based Games

Authors: Paul Coulton; Will Bamford; Keith Cheverst; Omer Rashid
Journal: International Journal of Computer Games Technology
 (2008)

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## Abstract

Location-based games not only offer new experiences for the players, but also present new challenges for researchers in terms of analyzing player behaviour. Whilst many ethnographical studies have presented useful qualitative insights into this area, there is the potential to both improve support for these studies and to provide more effective representations of the quantitative data that can often be extracted from the game itself in a manner that enables greater understanding. In this paper, we illustrate how combined spatial and temporal information can be represented using the human geographers'  technique ofspace-time paths to provide 3D visualizations of a player's or players' movement. Our analysis of a particular location-based game shows how a richer understanding of overall game play is obtained and highlights the possibilities for using the technique for a whole range of location-based services to provide a more complete view of complexities of journeys. Further, we discuss how these techniques can be utilized more generally by ethnographers who study the behaviour of mobile actors.


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## Body

## 1. Introduction

Location-based gaming allows users to play games that
incorporate knowledge of their physical location and landscape, and then
provides them with the ability to interact with both real and virtual objects
within that space. These games are often created to answer various research
questions, not only for games researchers but also for those interested in
related topics such as technologies for ubiquitous computing platforms, human
computer interaction, or collaborative behaviour. In terms of analyzing these
games, various techniques have been used to provide both qualitative and quantitative
analysis. Ethnographical techniques have been used successfully [1] to provide insights
into how users interact, both with each other and the game space, for
information that is often not explicitly represented in the game events
recorded in the system, such as a discussion of tactics or the verbal
directions from an online game controller [2]. Benford et al. highlighted in 2002 that “there was no agreed format for
logging or suites of analyzing tools” [3] for studying system data
quantitatively, and in the years since little seems to have changed. Further,
in a recent paper by Crabtree et al. [4] they defined both the need for tools
and their required characteristics to better support ethnographical study of
pervasive and ubiquitous systems particularly in mobile environments. This is
not to say tools have not been considered and, indeed, in the aforementioned
paper by Benford et al., they discuss using an indexed 3D recording of a
performance that can be replayed and analyzed. Whilst this would provide a
useful system, it requires a great deal of computational support and for some
games that do not incorporate a complex virtual world, such as those that are
principally mobile phone based, it is difficult to implement. Other less
complex 2D systems [3, 5] have also been proposed but, as with the previous
system, they principally provide a replay of the action at instances in time rather
than an overall perspective on the spatial and temporal movement of the players
in the game. In order to enable this perspective, in this paper we highlight
the use of space-time paths which were originally proposed by the Swedish
geographer Hägerstrand in 1970 [6] as a means of quantitatively
analyzing human migration patterns.A space-time path illustrates how a
person navigates their way through the spatial-temporal environment. The
physical area is reduced to a two-dimensional plane with these dimensions
representing a person’s top-down position (e.g., longitude and latitude). Their
location and destination are represented as zero-dimensional points. Time is
represented by the vertical axis. These three dimensions combine to form a world
representing a specific portion of space-time. The path of a
stationary individual will appear as a vertical line between the starting and
ending times at a specific location. If an individual moves between two
geographical locations at a constant velocity, the graph will show a line with
a fixed trajectory which joins the start and end points. The slower an
individual travels, the greater the line’s vertical gradient. Therefore,
vertical gradient of the plot is inversely proportional to the user’s
ground-based velocity.In Figure1, we illustrate both a 2D spatial plot and
a 3D space-time path for an actor walking around the campus at Lancaster University—the data was collected at one-second intervals
using a modified version of Locoblog [7]. It is evident in this figure that whilst
the 2D plot provides us with details of the particular locations visited, it
provides no specific information relating to the actor’s movement along the
path itself, in other words it provides information about the route and nothing
about the particulars of the journey. The view that the journey itself should
form part of the study of mobility has recently gained popularity amongst
sociologists studying transportation and is transforming the view that the time
on the move should be considered as “lost” and of less relevance than the
locations themselves [8].2D path and 3D
space-time path of a journey around Lancaster University
campus (7th of
April 2007).
(a)(b)Representing spatial and temporal
data and its relationship to cognitive processes is beyond the scope of this
paper. However, by observing the 3D space-time path shown in Figure1, we
believe it provides a greater sense of the actor’s movement and a clearer
picture of the direction of travel, the speed of movement, and any places,
where the actors paused or delayed their travel.Although the space-time path does
not provide the fine detail of a particular journey, it could be annotated with
data from an ethnographical study, such as photos, audio, video, and text from
the user themselves to produce a more holistic representation. In this paper,
we will illustrate how space-time paths can be used as means of analyzing
player behaviour for the mobile mixed-reality location-based game PAC-LAN [9].
However, this technique can be applied generically across a variety of location-based
applications irrespective of the location sensing technology or the underlying
communications.


## 2. PAC-LAN

PAC-LAN is a novel version of the classic video game Pac-Man,
in which human players use the Alexandra Park accommodation complex at Lancaster University as the game maze [9]. The
player who takes the role of the main PAC-LAN character collects game pills
(using a Nokia 5140 mobile phone equipped with a Nokia Xpress-on RFID reader
shell) which are in the form of yellow plastic discs fitted with adhesive RFID
tags placed around the maze. Four other players take the role of the “Ghosts” (Mr. Blue, Mr. Red, Mr. Orange, and Mr. Pink) who attempt to hunt down the PAC-LAN
player.The mobile phone game client is implemented on the Java 2 microedition
(J2ME) platform which is connected to a central server using a general packet radio
service (GPRS) connection. The server relays to the PAC-LAN character client
his/her current position along with the position of all Ghosts based on the
pills collected as shown in Figure2.Figure 2
PAC-LAN client.The game pills are used by the Ghosts to obtain the PAC-LAN
character’s last-known position and to reset their kill timer which, if
expired, will prevent them from “killing” PAC-LAN. In this way, the ghosts must
regularly interact with the server which is then able to relay their position
to PAC-LAN. The Ghosts can “kill” the PAC-LAN character by detecting him/her
via an RFID tag fitted to their costume (assuming their kill timer has not expired).
Once PAC-LAN is killed, the game is over and the points for the game are
determined by calculating the number of game pills collected and time taken to
do so. When PAC-LAN tags one of the red power pills, indicated by all Ghost
icons changing to white on the phone screen, he/she is then able to kill the
Ghosts, and thus gain extra points, using the same RFID detection process.
“Dead” Ghosts must return to the central point of the game maze where they can
be reactivated into the game.It should be noted that PAC-LAN uses an implied, rather than
measured, method of location positioning [2] in that the players’ positions
are obtained through their interaction with an object (game pill) at a known
location.


## 3. Analyzing Player Behaviour

To illustrate the use of space-time paths in location-based
game analysis, we will not try to encompass the numerous games of PAC-LAN which
have been played thus far [9] but rather consider a specific game which took
place on the morning of 10th of February 2006. The players, in this case, were five males from Lancaster University between the ages
of 22 and 27 shown in Figure 3.Figure 3
PAC-LAN trial team for 10th of February.None of the players had previous experience of the game nor had
any of them used an RFID-enabled mobile phone. Furthermore, only Mr. Pink was
familiar with the game’s real-world environment (he lived in the accommodation
area which forms the game’s maze). The game in question was shorter than
average at 16 minutes and 30 seconds (the average game duration was 26 minutes),
although the action was fairly typical of a first play experience.In terms of mapping the game, we have created a Java class
that uses the JBDC connector library to link the database of our game server to
Matlab. This method not only provides a quick and easy method for producing the
space-time paths, but also allows us to generate them in real-time as the game
progresses. Once the paths are generated, Matlab allows us to manipulate them
in 3D space, as shown in Figure4, which is useful for extracting detail and
allows various combinations of players to be selected.Rotating space-time paths for PAC-LAN and Mr. Blue.
(a)(b)(c)(d)In all the Figures
used for the game analysis of PAC-LAN, we have not represented the axes of the
spatial plane in meters or degrees and minutes but rather in terms of the
pixels as they would appear on the phone screen map. For example, the actual
game maze area is approximately 350 meters squared and the mobile phone map of
this maze is represented as a128×128 pixel bitmap. Therefore, each pixel edge represents a length of approximately 2.74 meters.Figure4 illustrates that at the start of the game, the path
taken by Mr. Blue bears relatively little correlation to that of PAC-LAN but as
the game progresses it can clearly be observed that Mr. Blue starts to track
the movements of PAC-LAN.In Figure5, we show the space-time paths of all four
Ghosts together with that of PAC-LAN. It is worth noting that unlike other
location-based implementations of Pac-Man, such as Human Pac-Man [4] or
Pac-Manhattan (www. Pac-Manhattan.com), there are no online controllers and
each player acts on his/her own initiative within the game [9].Space-time paths of PAC-LAN compared to each of the four Ghosts.
(a)(b)(c)(d)From this, we can see those space-time paths of Mr. Blue
appear to closely correlate with PAC-LAN, whilst Mr. Orange’s path is similar
but with greater divergence at more points. Conversely, Mr. Red generally
appears to have run around fairly aimlessly, as Mr. Pink does although he
confined himself to a much smaller spatial area.To ascertain the effectiveness of the space-time path,
consider Figure6 which presents a running correlation of the paths taken by
each of the Ghosts relative to that of the PAC-LAN players. From this figure, it
can be seen that the paths taken by Mr. Blue and Mr. Pink are more closely
correlated than either Mr. Orange or Mr. Red. However, from the previous
analysis of the space-time paths it was observed that Mr. Pink’s path was less
correlated to PAC-LAN. This apparent discrepancy is due to the fact that the
correlation merely provides a simple distance measure and because Mr. Pink
remained fairly central in the game maze he maintained a good correlation.Figure 6
Running correlation of the Ghosts’ paths through the game relative to that
of PAC-LAN.This actual player activity can best be illustrated through Figure7 which shows each player’s movement as a circle whose radius is the mean
displacement centered around his/her average position to give some sense of how
adventurous each player was during the game. Whilst this gives a view of
general activity it does not provide the detail of the space-time path.Figure 7
Players’ mean displacement from their averaged position.Our observations during the game and the video footage
confirm what was observed in the space-time paths. This is not to say that we
should rely on purely quantitative analysis, in fact, the qualitative
observations and discussions revealed that Mr. Red was not as aimless in his
movements as it may at first have appeared; rather, he claimed his primary
strategy during the game was to ambush PAC-LAN, and his patterns of movement
reflect this (PAC-LAN was indeed caught in such a maneuver).


## 4. Conclusions

In this paper, we have presented human geographers’
space-time paths as an effective means of analyzing player behaviour in
location-based games. We believe that this technique has significant potential
for representing actors’ spatial and temporal movements in many location-based
scenarios, and, if coupled with qualitative data, can provide significant
advantages when analyzing emerging computing environments. We are already
working with sociologists and geographers to create versions of Locoblog that
will aid them in ethnographic studies, and with the forthcoming visualization
tool it will provide significant opportunities for behavioural analysis of
mobile actors. In respect of meeting the requirement of tools to be used in ethnographical
study, we believe it addresses many of the more salient points identified by
Crabtree and Rouncefield [1] of capture, extraction, synchronization, and representation.
The current generation of mobile phones is capable of recording text, image, video,
and voice, and it also provides
an effective means of capture when coupled with an application such as Locoblog.
By recording the data to the phone card in standard formats, it can then be
easily extracted and combined as required. In terms of synchronization, the GPS
unit provides a universal timestamp with which we can synchronize the often multiple
sources of mobile information and this time is available even when there are
insufficient satellites to provide a positional fix. Finally, in terms of
representation, the space-time map presents a very powerful method of representing
combined spatial and temporal behaviour.



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*Source: 192153-2008-07-01.xml*