user preferences, information transactions and location-based services: a study of urban pedestrian...

Computers, Environment and Urban Systems30 (2006) 726–740

www.elsevier.com/locate/compenvurbsys

User preferences, information transactionsand location-based services: A study

of urban pedestrian wayWnding

Chao Li ¤

Centre for Advanced Spatial Analysis, University College London, 1-19 Torrington Place,London WC1E 6BT, UK

Received 17 January 2005; accepted in revised form 15 July 2005

Abstract

Though research into location-based services (LBS) is being carried out across a number of disci-plines, user aspects of LBS remains a cross-cutting theme. In this paper, the research focuses on inves-tigating the user information requirements from LBS at individual level, with emphasis on theinteractive nature of information transactions between environments, individuals and mobile devices.Based on a proposed conceptual model, urban pedestrian wayWnding experiments have been imple-mented in an immersive virtual reality test environment. Automated and semi-automated methods ofdata collection have allowed an integrated picture of participant behaviour and information prefer-ences to be constructed and analysed. The results of this study show that there are clear user prefer-ences in information requirements in completing wayWnding tasks. However, changes in userpreferences during the wayWnding tasks do occur in response to levels of conWdence, diVerent spatiallayouts and the wayWnding situations individuals encounter. The outcomes indicate that the pro-posed conceptual interaction model and adopted implementation approach assist in understandinguser behaviour and information preferences for LBS.© 2006 Elsevier Ltd. All rights reserved.

Keywords: Location-based services; Pedestrian wayWnding; Interaction; Virtual environment

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C. Li / Comput., Environ. and Urban Systems 30 (2006) 726–740 727

1. Introduction

The rapid development of information and communication technologies (ICT) is pro-viding opportunities for innovation in location-based services (LBS). LBS are regarded asthe delivery of information and services tailored to the current or some projected locationand context of the user (Brimicombe & Li, 2006). LBS have been researched from variousperspectives across a range of disciplines such as mobile computing and networking, posi-tioning systems, distributed services and components, database and data content, Geo-graphical Information Science (GIScience) and human computer interaction. Ultimately,the utility of LBS will be measured by their ability to meet user needs. Thus one of thedeveloping research themes focuses on user aspects of LBS. User aspects have been consid-ered in designing, building and evaluating LBS applications and systems with the emphasison functionality in providing information and services. However, there has been littleresearch towards understanding what is useful and what is perceived as problematic from auser-perspective (Kjeldskov & Graham, 2003). On the other hand, there is a substantialbody of research on human–environment interaction from a cognitive perspective, whichhas emphasised individual spatial behaviour for acquiring and processing information(Golledge & Stimson, 1997; Kitchin & Blades, 2002). Yet to date there has been little con-sideration of technological elements in this interaction. In LBS research, such a technolog-ical element is present as an information source delivered through a mobile device.

The research presented in this paper considers user aspects of LBS from the perspectiveof the interaction and information transactions between three elements: environments,individuals and their mobile devices. A dynamic interaction model is proposed with thepurpose of understanding how users acquire information for completing spatial taskswhen using mobile devices within environments. To implement this conceptual model, anapproach has been developed using immersive virtual reality as test settings, simulatedLBS applications in mobile devices and automated and semi-automated data collectionmethods. In this way, details of the interaction and information transactions can be cap-tured in real time. Based on the proposed conceptual model and implementation approach,experimentation on pedestrian urban wayWnding has been designed and carried out inorder to investigate user preferences and information requirements using LBS. Twoaspects of such preferences have been studied in particular: diVerences in user preferencesfor types of information required (such as route information and map information) forcompleting wayWnding tasks and consistency of user preferences in response to wayWndingsituations along routes. User preferences have also been studied in relation to the sur-rounding spatial conWguration of the environment.

2. The user: spatial ability, interaction with environment and technology

2.1. User aspect of LBS

One aspect of LBS research into user needs investigates how to present spatial informa-tion and semantic content to users in order to meet their requirements. A number ofthemes are being researched in this aspect relating to visualisation, graphical modellingand the usability for mobile devices and services (Brunner & Neudeck, 2002; Reichenb-acher, 2003; Wintges, 2002). There are studies on the presentation of geometric and seman-tic information, as well as scale-dependency resulting from the requirements and

728 C. Li / Comput., Environ. and Urban Systems 30 (2006) 726–740

restrictions of mobile devices (Gartner, 2004). User interfaces can take a number of formsincluding graphical, text-based and auditory. The current primacy of graphical interfaces isbeing challenged by new developments in speech recognition and synthesis. Also multime-dia elements are viewed as improvements in communication. User needs regarding thenature of interface are likely to depend on context and may thus vary from one situation toanother.

Another user aspect in LBS research has focused on adapting content to user needs,which emphasises how to obtain and interpret the location and context information fromthe environment and from users. A number of models are discussed by Jiang and Yao (thisissue). Zipf and Jöst (this issue) are user-adaptive content for LBS applications to ascertainusers’ interest and preferences in areas such as map display with diVerent levels of general-isation and diVerent types of information. Brimicombe and Li (2006) outline a publisherand subscriber model to adapt information content based on location and context so as tomaximise its utility to the user. Furthermore, interactivity between a mobile computingdevice and its user has also been studied with consideration of the device’s ability to obtainand interpret contextual information for users’ beneWt (Dey, 2001; Schmidt & Van Laerho-ven, 2001). For instance, users’ perceived sense of control over the content within mobiledevices has been studied by providing devices with context-aware features at three levels ofinteractivity: personalization, passive context awareness and active context-awareness(Barkhuus & Dey, 2003).

2.2. Individual spatial ability, interaction with environment and mobile technology

There is a rich literature on individual spatial ability, spatial behaviour and cognitiveaspects of wayWnding (Allen, 1999; Golledge & Stimson, 1997; Gopal & Smith, 1990;Lloyd, 1989). Research has been carried out aimed at understanding people’s spatialbehaviour and diVerences among individuals. Much of this work has focused on thenature of cognitive maps as internal spatial representations, as well as how they are devel-oped and how information is retrieved from them for performing spatial activities. Whenencountering a new environment, people are likely to need a range of information forcompleting spatial tasks such as wayWnding. People acquire and develop their spatialknowledge through various experiences and processes which may include recognising andunderstanding characteristics of objects, localities and inter-relationship between ele-ments in environments. Spatial knowledge can be acquired in the form of three basic com-ponents as declarative, procedural and relational/conWgurational components, which areoften referred to as landmark knowledge, route knowledge and survey knowledge (Goll-edge & Stimson, 1997; Kuipers, 1978; Siegel & White, 1975; Thorndyke & Hayes-Roth,1982). Landmark knowledge refers to knowledge of those objects and/or places withmeaning or with signiWcance attached to them. Route knowledge is about the understand-ing of the process of how to walk/travel from one locality to another and which refers toknowledge about movements and mostly consists of procedural descriptions, some land-marks and path elements. Survey knowledge generally refers to the integrated knowledgeof the layout of a space and interrelationship of the elements within it. Some researchshows that the way in which spatial knowledge is developed and used in wayWnding variesamong individuals with diVerent levels of spatial ability and within particular environ-ments (Cornell, Sorenson, & Mio, 2003; Kato & Takeuchi, 2003; Malinowski & Gillespie,2001).


Interaction between people and the environment has been researched from cognitiveaspects over several decades. A range of conceptual models or schema have been estab-lished to understand how people structure and develop an inner representation throughrecording and processing information based on their perception of the real world andinferences about it (Downs, 1970; Gold, 1980; Golledge & Stimson, 1997; Pocock, 1973).On the other hand, the interaction between users and mobile technologies can be viewed asa new kind of human–computer interaction. Such interaction can be natural and impliciteven though it appears more engaging and tangible as an activity (Ishii & Ullmer, 1997;Schmidt, 2000). In traditional desktop-based human–computer interaction, the surround-ing environment is under-represented in the research. For the mobile human–computerinteraction, some attempt has been made to bring the surrounding environment into con-sideration, such as directly observing the phenomena and people (Oulasvirta, Kurvinen, &Kankainen, 2003). Yet to date, there has been no explicit focus upon the dynamic interac-tions between individuals, mobile technologies and environments, despite the rich pre-existing literature on human cognition and the obvious importance of this task for thedevelopment of LBS.

2.3. A conceptual interaction model

In this research, a conceptual model is proposed (Fig. 1) which focuses on the interac-tion and information transactions between environments, individuals and mobile devices.There are three basic elements in this interaction model: the physical, social and technolog-ical environment that is the real world; individuals who act and move within the environ-ment; the mobile device which acts as an information source and provides LBS toindividuals on the move. The environment in which individuals act provides both spatial

Fig. 1. A conceptual model of the interactions.


extent and context in terms of the various situations encountered; individuals acquireinformation and develop spatial knowledge from the environment. The mobile device pro-vides information and services that are tailored to the current or some projected locationwithin the environment and the context of the user. Individuals, as users of mobile devices,acquire and feedback information through the device whilst in or moving through theenvironment. This dynamic interaction model explicitly puts an emphasis on overt interac-tions between individuals, environments and mobile technologies, and focuses on informa-tion transactions between these three elements. With the knowledge of the complexcognitive processes carried out internally when individuals encounter environments, thisconceptual model takes a diVerent approach which is to investigate the real time, overt,observable interaction. For example, in a scenario of using LBS for wayWnding, individualsgain information about the environment from its distinctive physical features and on-going activities. When individuals are on the move, the information delivered via LBS-enabled mobile devices can be updated depending on their speciWc location. Thus by studyingthe details of these interactions and information transactions, we can gain an understand-ing and an insight into the level of information that is suYcient for their needs, desiredtypes of information and preferred modes of communication for completing wayWndingtasks. This contrasts with the research discussed above in that here it focuses on the aspectof individuals’ interaction with mobile devices and surrounding environment rather thanstudying the internal process of individuals.

3. Method

In this section, a method is introduced for implementing the conceptual interactionmodel to investigate user preferences in their information requirements. Studying the inter-action between environments, individuals on the move and mobile devices poses a numberof challenges. To begin with, a real-world environment usually encompasses a larger geo-graphical area for movement compared with a laboratory- or desktop-based situation. Areal-world environment is diYcult to control and can easily confound experiments of userbehaviour and interactions. For example, a real urban environment may vary during thetime period that experiments are conducted, in terms of weather conditions, seasonality ofvegetation, busyness and so forth. Thus the seemingly inWnite complexity of the real worldis likely to provide interruptions and disrupting stimuli that become a challenge in the con-duct of such experiments. In addition, location-based services are not yet widely used and itmay be diYcult for some individuals to understand their usefulness in relation to a fullrange of personal information requirements. Therefore, in this research, an immersive vir-tual reality (VR) based approach was proposed and implemented for capturing data in realtime on information transactions and individual behaviour in a dynamic environment. TheVR urban setting has been suggested as a controlled environment, in the sense that it pro-vides a consistent urban area for individuals to undertake their deWned tasks. Any interfer-ence which is not speciWed within the remit of the investigation can therefore be avoided.For instance, such interference could be congested streets on busy market days and diVer-ences between rainy and sunny weather. Furthermore, VR urban settings can produce highlevels of realism and environmental interactivity, whilst retaining a suYcient level of con-trol over the experiment (Li & Longley, 2006).

This VR-based method consists of a pre-experiment questionnaire, a task-based way-Wnding experiment and a post-experiment, de-brieWng questionnaire. The self-report style


pre-experiment questionnaire aims to gain an understanding of each individual’s spatialability, focusing on sense of direction, general spatial ability such as wayWnding and spa-tial anxieties. The construction of this questionnaire drew on previous research such asself-report measure of environmental spatial ability (Hegarty, Richardson, Montello,Lovelace, & Subbiah, 2002; Montello, Lovelace, Golledge, & Self, 1999) and measuringindividual’s ability for direction and orientation, preference for landmark, route or sur-vey-centred representations (e.g. Pazzaglia & de Beni, 2001). Also included in the ques-tionnaire are questions relating to individuals’ familiarity with a range of technologies.The pedestrian wayWnding experiment is designed as task-based to be carried out in a VRurban setting. During the experiment, a simulated LBS application could be accessed viaa PDA to assist individuals for their wayWnding tasks. The PDA usage was recordedalong with the track taken by individuals. Such data includes the type of informationaccessed (route instruction or map information), the mode of communication used andthe time at which the information is accessed. Data pertaining to overt participantbehaviour whilst completing wayWnding tasks is also collected through direct observa-tion. The fact that in VR the movement is directed by a joystick device rather than theindividual having real locomotion can be considered a limitation in replicating the realworld. Treadmills can be used, but the focus of the experiments is on ascertaining andmeasuring people’s wayWnding behaviour and strategy and whether this accord totheir reported real world behaviour. Responses to the post-experiment questionnaireshowed that wayWnding behaviour in VR did indeed accord with their usual real worldbehaviour.

By using this method, individuals’ behaviour could be closely observed either directly byinvestigators or through automated means, and which would be much more diYcult to doin a real world environment. The behaviour of individuals could then be analysed on amuch more equivalent basis. In addition, individuals’ movements could be recorded by theVR tracking system accurately and frequently. This can be supplemented with backgroundinformation obtained through the self-reported questionnaires.

4. The wayWnding experiment

4.1. The test environment setup

The aim of the test environment is to provide realistic stable settings in which individu-als can use LBS through mobile devices to assist them in completing wayWnding tasks, andduring which user interaction and information transactions can be observed and recorded.Therefore, a test environment was set up which comprised of three main parts: a VR urbanmodel, a mobile device providing simulated LBS applications and software for recordingindividual behaviour and interaction with LBS.

Firstly, a VR urban model was created for this experiment. The layout of this urbanmodel was characterised by an irregular layout with the features of a traditional markettown (Fig. 2). Both spatial layout and objects types have been modelled based on a realUK town centre. The area covered was approximately 32,500 square metres, with about780 buildings. The VR urban model was constructed using Virtual Reality Markup Lan-guage (VRML) and implemented in an immersive projection technology VR lab, theCAVE (Cruz-Neira, Sandin, DeFanti, Kenyon, & Hart, 1992). The implemented VR urbansetting allowed individuals to ‘walk around’ at street level with realistic views.


Secondly, a mobile device was used to relay dynamic information to individuals as asimulated LBS application. The mobile device can be a PDA or a mobile phone; and theinformation delivered via it can take a number of forms, which can include written text,the spoken word, graphical symbols, photographs, 2D maps, 3D maps, as well as videoclips, VR scenes and audible tones. In this experiment setting, the mobile device used wasa PDA with modes of communication currently restricted to text, voice and 2D maps. Asimulated LBS application with Web style browser interface, which can be accessedthrough the PDA, was created to assist individuals for their wayWnding tasks. Withregard to the constraints on display of content for small screens, only essential informa-tion content was presented with the dual consideration of readability and easy naviga-tion through the pages. The content of wayWnding assistance was designed to provide achoice of route instructions and maps of the area. The route instructions were given intext and voice mode, whilst the maps were shown at two levels of detail. The Wrst levelwas set up as a sketch map of the area layout with choice of clickable landmarks andstreet names; and the second level was set up as a scrollable zoomed area map giving allthe details.

Thirdly, a range of software was used for recording individuals’ actions and reactionsduring the wayWnding tasks. A combination of software was built to record experiment

Fig. 2. Study area in the experiment.


data automatically and semi-automatically, which were implemented in the VR system, thePDA and a standalone laptop. The geographic location with a time stamp of each individ-ual was recorded through a tracking device which was linked to the Intersense IS900 sys-tem in the VR system. For recording the information accessed through the PDA and themode in which it was accessed by individuals, cookies were created within the contentpages in the PDA. In addition to these automated measurements, a semi-automatedmethod was used: an interface was programmed with diVerent groups of clickable buttonsto record observations into an Access database.

4.2. The wayWnding experiment procedure

A task-based pedestrian wayWnding experiment was set up and carried out in the testenvironment described in the previous section. A total of twenty six participants, twelvefemales and fourteen males, volunteered to take part in the experiment. The mean age ofthe participants was 33, age ranging from 23 years to 52 years. Participants’ occupationincluded university researcher, Ph.D. student, Police oYcer, lecturer, project manager andartist with a range of disciplines such as GIScience, geography, planning, computer science,architecture, social science, arts and humanities. All participants had knowledge of usingthe Internet and searching travel information via the Web.

Prior to the experiment, a self-reported questionnaire (discussed in Section 3) was givento the participants to complete. The experiment started with a training session given to allparticipants in a purpose built training urban setting. The training session aimed to famil-iarise participants with navigating in a VR environment and using a PDA for accessingwayWnding information. The participants were required to wear stereo glasses and use ajoy-stick like device to move around in the VR environment. Some devices and an experi-ment scene are shown in Fig. 3. Following the training session, the participants wererequired to complete a range of wayWnding tasks in the main urban setting (shown in mapform in Fig. 2). The tasks were to Wnd a number of pre-described destinations. All partici-pants were instructed to begin at a car park (marked P in Fig. 2) as the starting point andthen Wnd Wve diVerent destinations sequentially before returning to the car park (see Table1). All the participants had no previous knowledge of the place on which the VR modelwas based. A PDA was provided for use as a wayWnding assistant, which included routeinstructions in both text and voice modes, as well as maps of the area. The exact currentposition of participant was not displayed on the PDA in this study; however, the car parkas starting point could be clearly identiWed by the participants. The participants couldchoose any information from the PDA at any time according to their preferences andneeds in completing the wayWnding tasks.

During the wayWnding experiment, each participant’s location within the urban settingwas tracked with a time stamp through a tracking device on the stereo glasses worn by theparticipant. Thus the entire route of each participant was recorded in a time-location for-mat of (t, x, y). Head height and head movements were also logged in a format of (z, pitch,yaw, roll). These data were captured automatically once every second. The exact position ofan individual at any time could thus be re-traced through the detailed tracking data. ThePDA usage data were captured during the experiment. On each occasion that participantsused the PDA to acquire information, the pages accessed along with the access time wererecorded through the cookies (discussed in the Section 4.1). Furthermore, the time whenparticipants looked at PDA for information was recorded by the investigator using the


observation recording program. Additional observations were recorded for each partici-pant throughout the experiment. These observations included where participants got lostor needed help, the completion time of individual tasks, any rotation of the PDA in thehand (as if turning the map around) and so on. Participants were encouraged to speakaloud their thoughts and feelings as they progressed through the tasks.

Fig. 3. Some elements of the test environment: (a) VR devices, (b) wayWnding scene.

Table 1Destinations of the wayWnding tasks

Destination

Start P—car park1 Castle2 —Church

3 Mkt—market square4 Superstore5 Pub—public houseFinish P—car park


5. Results and discussion

Data from the experiments can be classiWed into four main categories:

• movement tracking with time of each participant: Mi(t,x, y);• PDA usage: Pi(t, Ptype, Pmode, Paccess);• observational data: Oi(t, BPDA, Btcomplete, Bmove, BconWdence);• supplementary data on participant self-reported spatial ability: SBi(Ssd, Smu, Sgsb, Ssa);

where iD1–26 participants; t is time recorded in seconds; Ptype, Pmode and Paccess arerespectively the type of information acquired from the PDA, the mode by which it wasacquired and the way in which it was accessed (either click for new information or lookagain at the same information); BPDA, Btcomplete, Bmove and BconWdence are respectivelyusage of PDA (such as rotation of the device and looking at PDA), the completion ofindividual tasks, movement characteristics (e.g. looking for street name, hesitation ormaking decision), the level of conWdence expressed during the wayWnding tasks; Ssd,Smu, Sgsb and Ssa respectively represent the self-reported sense of direction, map use,general spatial ability (such as estimating distance and wayWnding), aspects of spatialawareness.

The above data were integrated using the common time Weld t to form a time series. Thusgeographical coordinates were added to the PDA usage data and the observation data.Through integrating diVerent data sets, additional variables could be calculated such ascompletion time, distance travelled, route taken, when and where information was required,when and where errors occurred. Additionally, individual and aggregated routes could bemapped and studied. Thus, the integrated data set was able to capture many pertinentaspects of LBS usage for wayWnding tasks and an analysis of user preferences. Whilst someof these aspects are illustrated in the results that follow, not all Wndings are presented here.

Fig. 4 illustrates one of the results of PDA usage which have been derived from integrat-ing movement data Mi(t, x, y), information usage data from device Pi(t,Ptype, Pmode, Paccess)and observational data Oi(t, BPDA, Btcomplete, Bmove, BconWdence). The example taken here isfrom a participant’s wayWnding route for which PDA usage, including the type of informa-tion accessed and the mode used, is plotted along the route according to the time and loca-tion of when and where PDA was used to obtain information. The destinations for eachwayWnding task are shown numbered 1–5 with start and Wnish points at a car park. In com-pleting the wayWnding tasks to destinations 1 and 2, the text mode route instructions werepreferred and the participant was conWdent with the environment and the tasks. When thewayWnding tasks and the surrounding areas got more diYcult for the participant, mapsboth in sketch format and detailed zoom-in format were used along with text route instruc-tions, as shown in the enlarged area that is Fig. 4b. In normal circumstances, the partici-pant’s preference was for route instructions given in text format. However, when thewayWnding tasks got more diYcult and the street layout less straightforward for this par-ticipant, the preference pattern was altered with other types of information introduced toassist in decision making or ascertain locations. This also occurred when the participantfelt lost. Although this example has been qualitative in its explanation, it is provided toshow the depth of information on the interactions and preferences that can be derivedfrom the experiments carried out in this type of test environment. From the data on otherparticipants, this pattern in the change of preference is by no means unique. Furthermore,


though individuals start with clear user preferences in the information required, there is atendency for these preferences to change depending on their overall level of conWdence inmaking decisions.

In addition to analyse individual preferences, studies have been made of aggregateddata from all participants in relation to the spatial conWguration of the test area. By aggre-gating PDA usage data from all participants along their wayWnding routes, a density mapof usage is presented in Fig. 5 in relation to all possible routes in the area. This shows thehigh density of PDA usage associated with the beginning of each successive task whereparticipants acquired the information necessary to plan their routes. However, it also high-lights other areas of heavy PDA usage situated at the various decision points, such as roadjunctions and roundabouts. In addition, PDA usage is also high in those places where par-ticipants feel they need to re-conWrm their location and route choice. For instance, onlonger stretches of road there does appear to be a threshold distance at which participantsaccess the PDA in order to reassure themselves.

According to the frequency with which each participant used the PDA for text, voiceor map information, the 26 participants were classiWed into three groups (Groups 1–3) asdetermined using Ward’s method (Fig. 6(a)). Group 1’s behaviour on the wayWndingtasks was dominated by accessing route information as text from the PDA. A portion oftheir aggregate density map is given in Fig. 6(b). This shows a single wayWnding taskfrom destination 4 (the Superstore) to 5 (the Pub in the lower left hand corner). Apartfrom route planning activities giving high densities at both destinations, this class of par-ticipants tended to acquire information from the PDA at junctions where changes ofdirection were required. There appears to be a lack of survey knowledge of the overallarea as most of this group had considerable diYculty around a dead-end road in thecentre of Fig. 6(b) where they were supposed to follow a road which took a right bend.Although the other groups experienced some diYculty here, participants in thosegroups required much less PDA usage to complete the task. Group 2’s behaviour on the

Fig. 4. PDA usage along a wayWnding route. (a) PDA usage along the whole route, (b) PDA usage for an enlargedarea around destination 3.


wayWnding tasks was dominated by accessing map information from the PDA at a lowerlevel of frequency (Fig. 6(c)). This group appears to have quickly developed good surveyknowledge of the area and performed the tasks relatively conWdently. The highest densi-ties of PDA usage are at the destinations where the next task needed to be planned, withonly light usage for re-assurance along the route. Group 3’s wayWnding behaviour is alsodominated by accessing map information from the PDA but with much higher frequencyand more often in between destinations as reXected in the density map in Fig. 6(d). Anumber of participants were also becoming confused by the dead-end road. Throughthese types of analyses, it has been possible to identify broad patterns of user preferencesfor information and relate this to the spatial layout of routes and wayWnding diYcultiesthey pose.

Fig. 5. Density map of aggregated points of PDA use.


6. Conclusion

In this paper, the research on a proposed conceptual model and the implementationmethod has been discussed. This conceptual interaction model has brought together threemain elements: individuals, environments and mobile technologies. The focus of the modelis on the explicit dynamic interaction and information transactions between the three

Fig. 6. Aggregate density maps for three diVerent PDA usage groups: (a) Ward’s classiWcation tree for threegroups, (b) Group 1 dominated by use of text route information, (c) Group 2 dominated by low use of map infor-mation, (d) Group 3 dominated by high use of map information.


elements. Based on this dynamic interaction model, information requirements for LBS, atindividual level, have been investigated. This model has been implemented in an immersiveVR test environment that provides a controlled setting in which all participants are on anequal footing. A pedestrian urban wayWnding experiment was carried out to study userpreferences in information requirements by using a simulated LBS application. Resultsdemonstrate that there are clear user preferences either on route instructions or on diVer-ent types of map information. However, there is no deWnite consistency for a single pre-ferred type of information throughout a series of wayWnding tasks. The change in userpreferences during the wayWnding tasks occurs in response to levels of conWdence, diVerentspatial layouts, surrounding and wayWnding situations which individuals encounter. Thiswould indicate that LBS applications with multi-mode information would be moreeYcient in assisting individuals to complete wayWnding tasks. The outcomes also indicatethat the proposed conceptual interaction model and adopted implementation approachwould assist in understanding individuals’ behaviour in wayWnding. Experimentation andanalysis are on-going. Future research will expand the test environment to include moremodes of communication, diVerent contexts and controlled distractions such as avatarsand vehicles. Participants groups will be widened to a broader range of age groups and life-style backgrounds.

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