Using Wearables for Travel Assistance

Christian Samsel, Igor Dudschenko, Wolfgang Kluth and Karl-Heinz Krempels

Information Systems, RWTH Aachen University, Aachen, Germany

Keywords:

Assistance, Travel Information, Navigation, Ubiqitous Computing, Wearables.

Abstract:

In the last decade, personal mobility has become more diverse and more complex. Public transportation net-

works have grown bigger and new travel modes, e.g., car sharing, have emerged. Thus the required electronic

travel assistance, usually provided by smartphone applications, has been well-established and is generally ac-

cepted. Unfortunately using a smartphone application to check the itinerary while travelling can be a hassle.

The traveller has to pull out the device, unlock it, start the application and ﬁnd the required information inside

the application. In the meantime he or she is distracted which causes a loose of time and also may lead to

dangerous situations, e.g., in trafﬁc. To improve this situation we developed a smartwatch application follow-

ing the Cascading Information Theory principle which assists the traveller by displaying all journey-related

required information on his or her wrist and notiﬁes him or her when necessary. The prototype of the applica-

tion was evaluated in an initial user test (n = 5) and improvement compared to a single smartphone application

was assessed. The evaluation results showed that users prefer a smartwatch/smartphone based solution over a

pure smartphone application and are distracted for a shorter timespan.

1 INTRODUCTION

Shifts in technology usage and globals trends, e.g.,

urbanization, change peoples mobility. Growing pub-

lic transportation networks and new transport modali-

ties, e.g., car sharing, give travelers more options and

therefore, make traveling more complex. Simplify-

ing the usage of such complex mobility services by

assisting the traveler can potentially improve the ac-

ceptance and therefore lower emissions (Chapman,

2007) (Camacho et al., 2012). A lot of applications

and projects, both stationary and smartphone based

have been established for mobility services around

the world and for various platforms (see Section 2).

Most of these applications focus on the preparation

of the trip. Traveler can compare different prices, de-

parture times and itineraries and commonly also book

the respective services. Although the planning of a

trip might be complex itself, it is usually conducted

in advance of the actual trip and the traveler is not

on any sort of pressure (he or she has enough time

and is in a familiar environment). In contrast, un-

dertaking a trip usually involves a lot of stress, es-

pecially when multiple mobility services, e.g., con-

necting trains or planes, are involved. Traveler are in

distracting and confusing environments, like train sta-

tions, have to carry luggage etc and meanwhile have

to check for, e.g., departure information, therefore

Travel Assistance applications are required. Travel

assistance applications allow a quick information ac-

cess to itinerary information and guide the traveler to

his or her destination.

Most current travel-related smartphone applica-

tion present a great amount of information (some of it

usually redundant and unnecessary) and have an ap-

pealing GUI. These applications usually perform well

in lab scenarios but lack usability in the real world.

To mitigate these issues the Cascading Information

Principle has been applied to mobile travel informa-

tion (Samsel et al., 2014) and proven feasible (Beul-

Leusmann et al., 2014). The Cascading Information

Principle suggests “to unveil information about the

game in as small amounts as possible to ensure the

user’s focus exactly on the desired objective. Thereby,

confusion and misdirection of players by providing

excess information is prevented and each iteration of

new data can be applied directly.”

Although, initially

developed in a game context, the concept also applies

to real world scenarios.

Wearables are smart devices which are usually

worn as garments or accessories. Current examples

are watches, bracelets, glasses, shirts and shoes. Al-

though very different in nature, all wearables have

http://techcrunch.com/2010/08/25/scvngr-game-

mechanics/

635

Samsel C., Dudschenko I., Kluth W. and Krempels K..

Using Wearables for Travel Assistance.

DOI: 10.5220/0005481306350641

In Proceedings of the 11th International Conference on Web Information Systems and Technologies (WEBIST-2015), pages 635-641

ISBN: 978-989-758-106-9

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

some common characteristics; They have low pro-

cessing power, none or very few input and output

methods like buttons or a display. Because of these

properties wearables are usually used as an extension

to an existing device, e.g., a smartphone. They allow

a quick information access or a simple interaction via

a single button press. It’s easier and faster to check

ones (smart) watch by turning the wrist, compared to

check the smartphone by pulling it out of a pocket /

purse, unlock it and maybe even start the respective

app.

Thus, we realized a wearable-based travel assis-

tance application, following the cascading informa-

tion principle and evaluated the application in a real

world ﬁeld test.

The remainder of this paper is structured as fol-

lows: In Section 2, related research and existing ap-

plications are discussed. Section 3 derives our ap-

proach by listing requirements to the system, whereas

Section 4 presents the working prototype implemen-

tation. The evaluation methodology and results are

presented in Section 5 followed by Section 6 conclud-

ing the paper.

2 RELATED WORK

This Section gives a brief overview on related scien-

tiﬁc work and existing applications.

Multiple approaches for pedestrians navigation

have been introduced. (Baus et al., 2002) established

a pedestrian navigation system with a hybrid solution

titled Project REAL, already predicting the evolution

of personal navigation systems (“Personal navigation

systems that extend beyond today’s use in cars will

play a major role in the future.”). The system is capa-

ble of automatically adapting to location changes and

presenting directions to the traveler on a variety of dif-

ferent devices. (Wenig et al., 2014) discuss different

approaches of combining maps and panoramic pho-

tographs for pedestrian navigation. They acknowl-

edge the problem of distraction by pointing out an in-

cident where a test participant disregarded a red trafﬁc

light while using the navigation system. (May et al.,

2003) suggest a landmark based approach, which rely

on orientation points like buildings as navigations

cues instead of distances or street names. (Chowaw-

Liebman et al., 2010; Heiniz et al., 2012) transfers

this idea to a turn-by-turn approach to manage navi-

gation inside large, complicated buildings using land-

mark representations for orientation rather than street

names. A different approach for navigation assis-

tance for pedestrians and public transport is Pulsemap

(Zargamy et al., 2013), which rely on the results in

Figure 1: The Qixxit android application in travel compan-

ion mode (only available in German).

(Pascoe et al., 2000). Pascoe et al. state that travelers

are distracted by audio and visual clues, which po-

tentially lead to dangerous situations. Zargamy et al.

approached this by using the vibrations of a wearables

device. Different vibrations lengths convey different

directions, e.g., 100ms denote “turn left”, whereas

200ms denote “turn right”.

Wearables, although a new technology, have been

deployed to various ﬁelds of assistance applications,

most notably to e-Health systems. (Jonas et al., 2014)

introduced wearable technology to assist nurses in

clinical care, whereas (Sun et al., 2014) present a

wearable platform aimed towards patients. In (Jiang

et al., 2014) the authors present a wearable glove for

service and maintenance personnel.

Qixxit

is the newest travel information platform

provided by Deutsche Bahn. It incorporates a travel

companion (travel assistance) mode presented in Fig-

ure 1. It displays the time until the departure of the

next connection, the respective train number and plat-

form number, loosely following the Cascading Infor-

mation principle.

3 APPROACH

This Section documents step-by-step the conceptual

development of the approach. Our approach is based

on the travel assistance concept introduced in (Samsel

et al., 2014). In this work only the Wearables related

extension is described.

http://www.qixxit.de

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3.1 Requirements

Before extending an existing information system with

a wearable device, the developer has to decide which

function the wearable device has to fulﬁll and which

functional or non-functional requirements have to be

met. Based on these factors a suitable device can be

selected. Key requirements are wearability, interac-

tivity, security, communication, battery runtime and

real-time processing (Lymberis, 2005; Meng et al.,

2011; Wei, 2014).

Wearability (R1) is the comfort of carrying a smart

device. The device should not obstruct the move-

ment of the user nor should the users appearance

been altered in a negative way. Ideally, neither

the user nor his or her surroundings should realize

that he or she is wearing a device. This require-

ment is important for travelers, as unobstructed

movement and discreetness are must-haves.

Interactivity (R2) is the ability of the system to offer

services to the user. This typically involves some

kind of input and output using, e.g., key presses,

a display and such. For an assistant application

conveying information to the user is required. Be-

cause of the distraction by the environment inter-

action should be possible with minimal cognitive

effort, so the device should offer a simple and in-

tuitive interface.

Security (R3) in context of wearables essentially

means the device and its communication channel

are protected from unauthorized access. As this

work is only a prototype, security is not a concern.

Communication (R4) is a strong requirement for

most wearable devices as these are mostly a part

of a bigger system. The communication is nowa-

days usually realized as wireless technologies

such as Wi-Fi or Bluetooth for short range com-

munications with other devices of the user or long

range communication like UMTS/LTE for a direct

connection to the internet. As an assistant appli-

cation running on a wearable device will typically

be used in conjunction with smartphone, a short

range communication technology is sufﬁcient.

Battery runtime (R5) is a critical factor for travel

related applications as a power supply is gener-

ally not available while traveling. With recent ad-

vances in battery technology, energy harvesting

and power saving (Gorlatova et al., 2013) we can

assume that current wearable devices are able to

support most trips runtime-wise, especially in ur-

ban scenarios.

Applying the stated requirements to the available de-

vice classes listed in Section 1 the optimal device

Figure 2: Paper prototype for for pedestrian-navigation and

public transport navigation.

is found rather easily. R1 prevent smart glasses as

these heavily interfere with the appearance of the trav-

eler. R2 exclude simple wearables devices like e-

textiles (shirts, shoes etc) or accessories (bracelets

etc) as these usually don’t have any way of interac-

tion. The only remaining class is the smart watch.

Smart watches are unobtrusive to wear but still have

enough interaction and communication capabilities to

fulﬁll assistance related functions.

For this work, the Sony SmartWatch 2

was cho-

sen as platform as it appeared to have the best de-

velopment environment in terms of functionality and

API stability at that time.

3.2 Graphical User Interface

Based on the required information for travel assis-

tance which have been derived in (Samsel et al., 2014)

a paper prototype for the smart watch has been cre-

ated. For pedestrian navigation information about di-

rection, distance and street name are required. For

public transport assistance information about depar-

ture and arrival station, vehicle information and de-

parture and arrival times are required. Figure 2

shows the corresponding view for pedestrian and pub-

lic transport.

4 IMPLEMENTATION

This Section demonstrates the actual prototype appli-

cation.

The prototype was developed using Android Stu-

dio

and the Sony Add-On SDK

. It consists of

two components with different functions; The smart-

phone component (shown in Figure 3) is responsi-

ble for the communication with the backend (using

Wi-Fi/UMTS) and the user input. Its map view also

serves a fall back for the navigation. The smartwatch

http://www.sonymobile.com/de/products/accessories/

smartwatch-2-sw2/

https://developer.android.com/sdk/

http://developer.sonymobile.com/knowledge-base/

sony-add-on-sdk/

UsingWearablesforTravelAssistance

637

Figure 3: Example route parsed and visualized by the Route

Activity.

component displays the actual routing instructions.

The interaction between both components is handled

by the Sony Add-On SDK using Bluetooth.

4.1 Smartphone Component

The Smartphone component consists of three differ-

ent activities. The settings activity can be accessed

via pressing the hardware-button, allows changing of

static parameters, e.g., Server URI or standard zoom

level of the used map. The main activity waits for a

destination to be entered by the user. The activity than

sends a request to the backend and requests current

geolocation coordinates. Upon receiving the current

location of the user, the activity starts the route ac-

tivity by pressing a Plan-Button and sending the des-

tination address and the current location of the user.

The route activity sends a request to backend with in-

put information from the main activity and parses the

information provided by a backend. Afterwards the

activity initializes and visualizes the parsed result on

a map (see Figure 3), by using markers at each nav-

igation step. Subsequently it calculates the distance

between the user and the next waypoint, and alarms

the user as soon as he or she is in the direct vicin-

ity of the next waypoint. The calculated distance be-

tween the user and the next waypoint is also visual-

ized by a static progress bar and a text ﬁeld provid-

ing the exact value. The distance between the user

and the next waypoint will be calculated each time the

GPS-routine is called. Each bar blanks out if the user

comes 50 meter closer to the waypoint. Also this ac-

tivity sends gathered information about the next way-

point and the user location to the Smartwatch.

Figure 4: Application prototype demonstration.

4.2 Smartwatch Component

The main functionality of the smartwatch is to visual-

ize the content received from the smartphone compo-

nent. Upon successfully receiving the information, a

vibrator is started to inform the user that he is in the

direct vicinity of the next waypoint. The Smartwatch

uses all information for the route and visualizes them

in a similar manner as the Smartphone does, but with-

out using the Map due to performance and visibility

issues. The Smartwatch component also shows the

distance to the next waypoint and uses a progress bar

to visualize the value.

The compass functionality was not added to the

applications since the compass/magnetic ﬁeld sensor

support from Sony’s SmartWatch 2 has been removed.

The compass functionality of the Smartphone could

not been used either, since this would require that

the user aligns his or her smartphone in his or her

pocket/purse to the direction he is facing.

4.3 Routing Backend

To enable pedestrian and public transport assistance,

a routing solution is mandatory. We opted for the

open source routing planning framework OpenTrip-

Planner (OTP)

. OTP features intermodal trip plan-

ning with support for public transport, pedestrian nav-

igation and even support for rental bikes. OTP is a

Java application and consists of a server which per-

forms routing and supplementary services offered via

RESTful API.

OpenTripPlanner includes a graph builder tool

which parses any provided General Transit Feed

Speciﬁcation (GTFS) data feed and determines the

required map excerpt. The required map data is

then automatically downloaded from OpenStreetMap.

To support public transport navigation we converted

timetable data supplied by the local mobility service

provider into the GTFS format.

http://opentripplanner.com

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5 EVALUATION

To evaluate the application respectively the approach

a user-oriented ﬁeld test was conducted.

5.1 Methodology

The prototype application introduced in Section 4 was

assessed in a ﬁeld test to determine the general feasi-

bility of the approach and to identify both technical

and usability problems with the prototype application

itself. The ﬁeld test comprised a introduction to the

general handling of the smartwatch and smartphone,

a introductory scenario and two tasks which had to be

solved by navigating using the application. The pur-

pose of the scenario was to give the test participants a

contextual framing to balance out the different back-

grounds of the participants.

Scenario: “Assume you are a student using a smart-

phone and smartwatch, owning a student ticket and

using public transportation frequently. You work for

the student union and you often have contact to other

students with a variety of different ﬁelds of study.”

Task 1: “You start your day with the ﬁrst lecture in

Audimax. During the lecture you receive an email

with the notiﬁcation that your next tutorial had to be

moved to another building. Unfortunately, you do

not know the exact location of the building, but you

received the address of the building. You want to

know, how to get as soon as possible to the unknown

destination. The address you received via email is

Rochusstrasse 14 in Aachen.”

Task 2: “After your tutorial, you realize that you still

need to hand in an internship report for your friend.

Your friend is studying mechanical engineering and

is currently working in Hamburg. He has to hand in

his report today and he gave you his internship re-

port yesterday. You know the address of the destina-

tion, but you do not know the exact location of the

building. You planned your trip yesterday, but with

the moved tutorial you are not sure how to get to the

destination now. The address of your destination is

Sandkaulstrasse 9 in Aachen.”

During the test, participants were instructed to ap-

ply the thinking aloud method which means to com-

ment on their interaction with the application. For

lowering the cognitive load, task instructions were

handed over only after completing or terminating the

previous task. Verbal comments were brieﬂy noted

and the number of interactions with smartwatch and

smartphone were logged. The feedback of partici-

pants was collected with a questionnaire based on the

Computer System Usability Questionnaire (CSUQ)

(Lewis, 1995; Lewis, 2002): CSUQ has a total of 19

questions, which are grouped into four different prop-

erties. The Usability evaluates out of questions 1 to

8, the Information Quality evaluates out of questions

9 to 15, the Interface Quality evaluates out of ques-

tions 16 to 18 and the overall rating evaluates out of

all properties and an additional question 19. Lewis et

al. suggested to use a Likert scale for the question-

naire. In this work a Likert scale was used, with a

range of: 1 (strongly disagree) to 5 (strongly agree).

Five test participants took part in the evaluation.

All ﬁve were male. Their age was M = 25.8 years

(M = mean value), SD = 3.63 (SD = standard devia-

tion). Four of them were students, one was a research

assistant. All participants stated they are enthusiastic

about technology, particularly computing.

5.2 Results

The three questions with the highest user rating mean

were: Question 16 (M = 4.8, SD = 0.45, ”The in-

terface of this system was pleasant.”), Question 7

(M = 4.6, SD = 0.89, ”It was easy to learn to use

this system.”) and Question 6 (M = 4.4, SD = 0.55, ”I

felt comfortable using this system.”). The three ques-

tions with the lowest user rating mean were: Ques-

tion 9 (M = 1.4, SD = 0.89, ”The system gave er-

ror messages that clearly told me how to ﬁx prob-

lems.”), Question 11 (M = 1.75, SD = 1.5, ”The infor-

mation (such as on-line help, on-screen messages and

other documentation) provided with this system was

clear.”) and Question 10 (M = 3.2, SD = 0.84, ”When-

ever I made a mistake using the system, I could re-

cover easily and quickly.”). The other questions had a

mean rating between 4.2 and 3.8. The best rated ques-

tions pointed out that the groups Interface Quality and

Usability scored best and the group of Information

Quality scored worst. The Usability was rated with

M = 4.14, SD = 0.81, the Information Quality was

rated with M = 3.07, SD = 3.3, the Interface Quality

was rated with M = 4.2, SD = 0.77 and the Overall

Rating was M = 3.83, SD = 1.08.

Besides the usability assessment using the CSUQ,

participants gave detailed feedback on the prototype’s

visualization and features by writing down comments

in the questionnaire and uttering them during the eval-

uation. Many positive comments were made on the

prototype in general. One participant stated: ”I really

liked that the Smartwatch displayed the distance to

the next waypoint while navigating by foot.” Another

participant stated: ”I really liked the vibration notiﬁ-

cations.” In addition, they acknowledged the minimal-

istic design of the applications, the integrated map and

the automatic step-by-step support during the journey.

Further negative comments addressed the Information

UsingWearablesforTravelAssistance

639

Figure 5: The mean value and the corresponding standard

deviations, of the collected user ratings for all CSUQ ques-

tions. The values have a range from 1 (strongly disagree) to

5 (strongly agree).

Quality of the application. Test participants criticized

that the information about the cardinal directions after

deboarding from public transport or starting their nav-

igation, wasn’t helping to ﬁnd the directions they had

to go to. One participant also said: ”I wasn’t really us-

ing the progress bar, if I needed the information about

the distance I always used the [displayed] value.”

The participants used for the ﬁrst route, the Smart-

phone application seven times in total (M = 1.4,

SD = 0.55) and for the second route 11 times in to-

tal (M = 2.2, SD = 0.84). The Smartwatch has been

used 54 times in total (M = 10.8, SD = 1.92) for the

ﬁrst route and for the second route 86 times in total

(M = 17.2, SD = 4.15).

5.3 Discussion

The worst rated questions are easily explainable since

this prototype did not implement any error messages

or additional information (such as on-line help or

other documentation). In fact, these questions were

better rated than thought, since some users just didn’t

run into errors while evaluating the application. If

one removes the three questions about error mes-

sages and on-line help or other documentation, the

Information Quality rating increases to M = 4, SD =

0.65 and the Overall rating increases to M = 4.13,

SD = 0.72. Overall, the participants preferred us-

ing the Smartwatch instead of the Smartphone, which

is shown by the number of interactions (Smartwatch

M = 10.8/M = 17.2 vs. Smartphone M = 1.4/M =

2.2). The smartphone component can be considered

as a backup solution for complex situation in which

the smartwatch is not sufﬁcient, e.g., if the partici-

pants did not know in which cardinal direction they

had to go or if they were not sure if they are still on

the right track. During the evaluation one could ob-

serve that the progress bar was not used by the major-

ity of the participants. Most of the participants did not

look at the smartwatch while navigating, they rather

performed one navigation step and afterwards went

forward until the next vibration signal appeared to de-

liver the next navigation step. Some users also stated

that they would like to use a compass for the cardinal

directions directly on the smartwatch (was not possi-

ble due to technical restrictions).

6 CONCLUSION

This paper presented an approach for assisting trav-

elers on their public transport-based journey using a

wearable device. The prototype was realized follow-

ing the cascading information principle using a Sony

SmartWatch 2 and using OpenTripPlanner as routing

backend. The prototype application was evaluated in

a real world ﬁeld test to gain insights about the fea-

sibility of the approach and usability issues with the

speciﬁc implementation. The results showed that gen-

eral approach of using a wearable in addition to a

smartphone for navigation is beneﬁcial compared to

only using a smartphone.

Future Work

Although, this work showed that the approach is fea-

sible, there is still some work remaining. The feed-

back provided by the participants revealed that show-

ing the distance to the next intermediate point is not

useful; while walking participants had problems ap-

proximating the distance and while riding a bus, it is

irrelevant. Instead, it is supposedly better to calcu-

late the remaining time based on the walking speed

or using realtime trafﬁc information for public trans-

port. (May et al., 2003) suggested another approach

for navigation, by adding information about their sur-

roundings (e.g.: Turn left at the cross-way with the

trafﬁc light.). This approach could be used to avoid

to use cardinal directions, but would require a huge

amount of underlying data. Potentially the Cascading

Information principle might be transferable to wear-

ables applications in different domains, but this is

beyond our scope. The user test itself, with a rela-

tive low number of participants, can hardly give any

quantitative feedback. Consequently in a further itera-

tion of the development cycle the evaluation should be

conducted with a higher number of participants. Last

but not least, the presented application is just avail-

able for a single platform, for Sony SmartWatch. For

a productive usage, more wearable platforms have to

be supported.

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ACKNOWLEDGEMENTS

The authors would like to thank the participants of

the user study for their patience and time. The au-

thors would also like to thank ASEAG AG and IVU

Trafﬁc Technologies AG for supplying the required

timetable data. This work was founded by German

Federal Ministry of Economics and Technology for

project Mobility Broker (01ME12135A).

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