Background of Mobile Navigation

For thousands of years, human beings have needed to find their way to where

they needed to go, and stay oriented was a matter of life and death. One wrong turn

could lead to a bottomless cliff or a nasty death from starvation. As a result, different

techniques for wayfinding were developed and used by travelers over land and sea.

These include navigating by tracking the sun or stars’ position and celestial events as

landmarks to determine one’s position, or with the help of road signs, maps, compass,

and along with the navigating person’s cognitive effort to decide on which way to go.

As the technology innovates and expands at an exponential rate, the way people

live today has become more rapid and mobile than few decades ago. People generally

commute farther, and travel much more frequently to both familiar and unfamiliar

destinations. Regardless of the traveling distance, most activities that we do in our

daily lives are related to mobility in some way - we do activities such as work, study,

shop, eat, and sleep at different places. In order to do all these activities within the

limited time we have, a careful scheduling considering place, time, and order of the

activities is required. Location-Based Services provide solutions to this need as

information and supporting tool.

Location-Based Services (LBS) are information services that use information on

the geographical location of the mobile devices to provide various services to their

users. The term LBS generally can be applied to any application that uses the user’s

location - regardless of the user’s mobility. For example, Google Maps can be used on

either a desktop computer or a smartphone to search for places based the current

location of the system being used. The term mobile Location-Based Services (mLBS)

is preferred when referring to the LBS applications running on mobile devices.

Benefitting from the location awareness, connectivity, mobility and convenience

of mLBS, novel applications have been created to assist users for their geospatial

decision-making tasks in everyday lives. These applications are typically used to

provide information or entertainment. It can be used to find the location of an object

or a person to answer questions such as “Where is the nearest gas station?” or “Where

is my friend at?” Some other common mLBS applications include fleet management,

local advertisements, location-based games, and personalized weather.

There are many different interfaces for mLBS to communicate information

between the users and the application. In this thesis, I choose to focus on the mobile

cartographic interfaces. Cartographic interfaces are often used with other navigation

aids such as text, voice, and graphics to support effective communications in mLBS.

To distinguish with other mLBS, the term geolocation apps will be used for the

mobile applications that use cartographic interfaces in this thesis.

Geolocation apps are used as geospatial decision-making tools that support

people’s need with timely location sensitive information at anytime, anywhere. One of

the general usage scenarios of geolocation apps would be travellers arriving in an

unfamiliar city. The primary task for them often is to find out where they are and

which way to go. Although it is possible to ask someone or read a map for directions,

there is no guarantee for them to reach the desired destination without getting lost. It

is at this point that the need for geolocation apps becomes more significant.

The typical users for geolocation apps could be car drivers looking for navigation

guidance, customers looking for a business, or pedestrians searching for the most

efficient route to their destinations. While expecting geolocation apps can provide

effective solutions to these problems, there still remain many factors affecting their

feasibility in the real world practice. Some of the most important factors are the

differences in context of use and users (e.g. abilities, goals, personal preferences), the

limitations of mobile devices (e.g. small screen size, difficulty of data input,

processing power and network bandwidth), and the dynamic physical conditions (e.g.

noise, light level). These challenges must be carefully addressed when designing

geolocation apps.

Geolocation apps aim to solve the geospatial problems from their users. These

problems are often related to wayfinding. The very first step of these systems often is

to answer the orientation question “Where am I?” The concept here is simple - if one

doesn’t know where she or he is, how one can find the way that he or she wants to go.

Once obtained the user’s current location, questions such as “Where can I go?”, “How

can I get there?”, “How long does it take to get there?”, “How far away is it?”, and

“How will I know when I get there?” need to be addressed to achieve successful

navigation.

New technological advances such as mobile phones, internet, and Global

Positioning System (GPS) have transformed how we find our ways in the physical

environment [22]. Now that the GPS and internet have built into the mobile phones,

one can use it as one’s own personal wayfinding device [1]. With the position

information obtained and a digital road network model, the devices can calculate and

suggest an optimal route to the desired destination. A 2D digital street map is usually

used as the cartographic representation to display the route and the user’s current

location (see Figure 1.1). To navigate with this approach, users are required to

complete an orientation task to relate the digital map to their physical environment.

However, this can be especially difficult in crowded surroundings or urban areas

where the digital map cannot represent all the complexity and details in the 3D real

world.

Figure 1.1 2D digital map displays the route and the user’s current location.

To deal with this problem and enhance the overall navigation user experience,

companies like Google and Nokia have put their efforts to collect images along many

streets in the world. For example, Google, today’s leader and innovator in map and

navigation, sent out its 360 Degree Panoramic Camera mounted vehicles to

systematically harvest visual information [23], and the images collected can be used

in map applications to ease the burden of the users from relating artificial view on the

map to physical environment. These panoramic street-level views enable users to

virtually visit the place and explore surroundings without actually been there, thus

helping the users to recognize which road to make the turn and the destination more

easily.

Another challenge for mobile navigation is to optimize and refine the map for

use on the small screen. Traditional solutions used to presenting map information on

the desktops are not always feasible on mobile devices. Because of the limited screen

size, mobile phones can only display a relative small amount of information at once.

Simply scaling down the maps made for desktops is not practical, the result might be

difficult or even impossible to read [2, 3].

Zooming and panning are commonly used to overcome the limitation of small

screen display. However, this approach has some disadvantages. First, interacting with

the map becomes more time demanding and complicated. Second, zooming-in to get a

closer look of an area on the map results in a loss of the overview, also a large amount

of details will be omitted when the users zoom out the map. As mentioned before, the

mobile devices can only handle a limited amount of information; naively overloading

all details onto a mobile device’s screen can ruin its usability and readability. In the

case of zooming-out, the small-scale map may not include all information, and its

users may find it difficult to obtain a broader understanding of the situation.